AER 9.3 by Radcliffe Cardiology

Arrhythmia & Electrophysiology Review Volume 9 • Issue 3 • Autumn 2020

Volume 9 • Issue 3 • Autumn 2020

www.AERjournal.com

Differential Diagnosis of Wide QRS Tachycardias Demosthenes G Katritsis and Josep Brugada

His–Purkinje Conduction System Pacing: State of the Art in 2020 Ahran D Arnold, Zachary I Whinnett and Pugazhendhi Vijayaraman

Rhythm Control in Heart Failure Patients with Atrial Fibrillation William Eysenck and Magdi Saba

Electrophysiology in the Era of Coronavirus Disease 2019 Vijayabharathy Kanthasamy and Richard J Schilling

Left ventricular septal pacing* Capture of the left side of the IVS, without capture of the conduction system

Selective left bundle branch pacing Capture of the LBB alone, without capture of local myocardium

Sharp ABL Sharp EGM ABL EGM Sharp ME Sharp EGMME EGM

Non-selective left bundle branch pacing Simultaneous capture of the LBB and local left ventricular septal myocardium

S-LBBP

LVSP

Sharb ABL Sharb EGM ABL EGM No or blunt No or MEblunt EGMME EGM

NS-LBBP

S-HBP Selective His bundle pacing Capture of the His bundle alone, without capture of local myocardium Left bundle branch

His

dle bran

AV node Annular plane

Anodal capture Ring electrode captures the right side of IVS Simultaneous LBB capture by tip electrode

RVSP

ABL d ABL d

Micro 1–2 Micro 1–2

MiFi 1–2MiFi 1–2

Micro 2–3 Micro 2–3

MiFi 2–3MiFi 2–3

Anodal capture

Micro 3–1 Micro 3–1

Right ventricular septal pacing* Left bundle branch block morphology Site of approach for left bundle pacing

Myocardium-only pacing* Only the local myocardium is captured No capture of conduction system

ABL distABL dist

NS-HBP

MOP

II aVL

Right bun

Non-selective His bundle pacing Simultaneous capture of both the His bundle and local myocardium

II aVL

MiFi 3–4MiFi 3–4 Mid-septal capture* Morphology observed during traversal of IVS while attempting left bundle pacing

ABL p ABL p

Mid-septal capture

50 mm/s 10 mm/mV

Conduction System Pacing

The Effect of Shifting Precordial Electrodes

EGM showing fragmented bridging of the remaining gap on the PVI circle

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Volume 9 • Issue 3 • Autumn 2020

www.AERjournal.com Official journal of

Editor-in-Chief Demosthenes G Katritsis Hygeia Hospital, Athens

Section Editor – Clinical Electrophysiology and Ablation

Section Editor – Arrhythmia Mechanisms / Basic Science

Section Editor – Atrial Fibrillation

Johns Hopkins Medicine, Baltimore, MD

Royal Papworth and Addenbrooke’s Hospitals, Cambridge

Section Editor – Implantable Devices

Section Editor – Arrhythmia Risk Stratification

Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool

Pier D Lambiase

Section Editor – Imaging in Electrophysiology

Virginia Commonwealth University School of Medicine, Richmond, VA

Institute of Cardiovascular Science, University College London, and Barts Heart Centre, London

Stanford University Medical Center, CA

Hugh Calkins

Ken Ellenbogen

Editorial Board

Andrew Grace

Gregory YH Lip

Sanjiv M Narayan

Joseph G Akar

Carsten W Israel

Douglas Packer

Yale University School of Medicine, New Haven, CT

JW Goethe University, Frankfurt

Mayo Clinic, St Mary’s Campus, Rochester, MN

Charles Antzelevitch

Warren Jackman

Carlo Pappone

Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK

IRCCS Policlinico San Donato, Milan

Sunny Po

Pierre Jaïs

Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK

Lankenau Institute for Medical Research, Pennsylvania, PA

Angelo Auricchio Fondazione Cardiocentro Ticino, Lugano

Carina Blomström-Lundqvist Uppsala University, Uppsala

Johannes Brachmann Klinikum Coburg, II Med Klinik, Coburg

Josep Brugada Hospital Sant Joan de Déu, University of Barcelona, Barcelona

Pedro Brugada

University of Bordeaux, CHU Bordeaux

Roy John Northshore University Hospital, New York, NY

Prapa Kanagaratnam

Edward Rowland Barts Heart Centre, St Bartholomew’s Hospital, London

Frédéric Sacher

Imperial College Healthcare NHS Trust, London

Bordeaux University Hospital, Electrophysiology and Heart Modelling Institute, Bordeaux

Josef Kautzner

Richard Schilling

Institute for Clinical and Experimental Medicine, Prague

Barts Health NHS Trust, London

University of Brussels, UZ-Brussel-VUB

Roberto Keegan

Afzal Sohaib

Alfred Buxton

Hospital Privado del Sur, Bahia Blanca, Argentina

Imperial College London and Barts Health NHS Trust, London

Beth Israel Deaconess Medical Center, Boston, MA

Karl-Heinz Kuck

William Stevenson

Asklepios Klinik St Georg, Hamburg

Vanderbilt School of Medicine, Nashville, TN

Cecilia Linde

Richard Sutton

David J Callans University of Pennsylvania, Philadelphia, PA

A John Camm St George’s University of London, London

Shih-Ann Chen National Yang Ming University School of Medicine and Taipei Veterans General Hospital, Taipei

Harry Crijns Maastricht University Medical Center, Maastricht

Sabine Ernst

National Heart and Lung Institute, Imperial College London, London

Karolinska University, Stockholm

Francis Marchlinski University of Pennsylvania Health System, Philadelphia, PA

John Miller Indiana University School of Medicine, Indiana, IN

Fred Morady Cardiovascular Center, University of Michigan, MI

Royal Brompton & Harefield NHS Foundation Trust, London

Andrea Natale

Hein Heidbuchel Antwerp University and University Hospital, Antwerp

Texas Cardiac Arrhythmia Institute, St David’s Medical Center, Austin, TX

Gerhard Hindricks

Mark O’Neill

University of Leipzig, Leipzig

St Thomas’ Hospital and King’s College London, London

Panos Vardas Heraklion University Hospital, Heraklion

Marc A Vos University Medical Center Utrecht, Utrecht

Hein Wellens University of Maastricht, Maastricht

Katja Zeppenfeld Leiden University Medical Center, Leiden

Douglas P Zipes Krannert Institute of Cardiology, Indiana University School of Medicine, Indianapolis, IN

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Published by Radcliffe Cardiology. All information obtained by Radcliffe Cardiology and each of the contributors from various sources is as current and accurate as possible. However, due to human or mechanical errors, Radcliffe Cardiology and the contributors cannot guarantee the accuracy, adequacy or completeness of any information, and cannot be held responsible for any errors or omissions, or for the results obtained from the use thereof. Published content is for information purposes only and is not a substitute for professional medical advice. Where views and opinions are expressed, they are those of the author(s) and do not necessarily reflect or represent the views and opinions of Radcliffe Cardiology. Radcliffe Cardiology, Unit F, First Floor, Bourne End Business Park, Cores End Road, Bourne End, Buckinghamshire SL8 5AS, UK © 2020 All rights reserved ISSN: 2050-3369 • eISSN: 2050–3377

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Established: October 2012 | Frequency: Quarterly | Current issue: Autumn 2020

Aims and Scope

Ethics and Conflicts of Interest

• Arrhythmia & Electrophysiology Review is an international, English language, peer-reviewed, open access quarterly journal that publishes articles on www.AERjournal.com. • Arrhythmia & Electrophysiology Review aims to assist time-pressured physicians to stay abreast of key advances and opinion in heart failure. • Arrhythmia & Electrophysiology Review comprises balanced and comprehensive articles written by leading authorities, addressing the most pertinent developments in the field. • Arrhythmia & Electrophysiology Review provides comprehensive updates on a range of salient issues to support physicians in continuously developing their knowledge and effectiveness in day-to-day clinical practice.

The journal follows guidance from the International Committee of Medical Journal Editors and the Committee on Publication Ethics. We expect all parties involved in the journal’s publication to follow these guidelines. All authors must declare any conflicts of interest.

Structure and Format • Arrhythmia & Electrophysiology Review publishes review articles, expert opinion articles, guest editorials and letters to the editor. • The structure and degree of coverage assigned to each category of the journal is the decision of the Editor-in-Chief, with the support of the Editorial Board.

Abstracting and Indexing Arrhythmia & Electrophysiology Review is abstracted, indexed and listed in PubMed, Crossref, Emerging Sources Citation Index, Scopus, Google Scholar and Directory of Open Access Journals. All articles are published in full on PubMed Central a month after publication. Radcliffe Group is an STM member publisher.

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Online All published manuscripts are free to read at www.AERjournal.com. They are also available at www.radcliffecardiology.com, along with articles from the other journals in Radcliffe Cardiology’s cardiovascular portfolio – Interventional Cardiology Review, Cardiac Failure Review, European Cardiology Review and US Cardiology Review.

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Contents

Foreword In search of Homo Deus

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Demosthenes G Katritsis DOI: https://doi.org/10.15420/aer.2020.38

Electrophysiology and Ablation Atrial Fibrillation Structural Substrates: Aetiology, Identification and Implications

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Ahmed M Al-Kaisey, Ramanathan Parameswaran and Jonathan M Kalman DOI: https://doi.org/10.15420/aer.2020.19

A New Era in Zero X-ray Ablation

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Giuseppe Mascia and Marzia Giaccardi DOI: https://doi.org/10.15420/aer.2020.02

Impact of Micro-, Mini- and Multi-Electrode Mapping on Ventricular Substrate Characterisation

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Benjamin Berte, Katja Zeppenfeld and Roderick Tung DOI: https://doi.org/10.15420/aer.2020.24

Cardiac Pacing His–Purkinje Conduction System Pacing: State of the Art in 2020

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Ahran D Arnold, Zachary I Whinnett and Pugazhendhi Vijayaraman DOI: https://doi.org/10.15420/aer.2020.14

Clinical Arrhythmias Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology

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Rutger R van de Leur, Machteld J Boonstra, Ayoub Bagheri, Rob W Roudijk, Arjan Sammani, Karim Taha, Pieter AFM Doevendans, Pim van der Harst, Peter M van Dam, Rutger J Hassink, René van Es and Folkert W Asselbergs DOI: https://doi.org/10.15420/aer.2020.26

Differential Diagnosis of Wide QRS Tachycardias

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Demosthenes G Katritsis and Josep Brugada DOI: https://doi.org/10.15420/aer.2020.20

Rhythm Control in Heart Failure Patients with Atrial Fibrillation

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William Eysenck and Magdi Saba DOI: https://doi.org/10.15420/aer.2020.23

COVID-19 Electrophysiology in the Era of Coronavirus Disease 2019

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Vijayabharathy Kanthasamy and Richard J Schilling DOI: https://doi.org/10.15420/aer.2020.32

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Foreword

In Search of Homo Deus

Citation: Arrhythmia & Electrophysiology Review 2020;9(3):112. DOI: https://doi.org/10.15420/aer.2020.38 Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

f you search “artificial intelligence” in PubMed today (16 October 2020), you end up with 110,855 results! It is more than obvious

that advanced computing is entering our lives – perhaps not yet as much as Yuval Noah Harari has predicted in his book Homo Deus, but definitely to an extent that our medical practice is substantially affected, as van de Leur and colleagues discuss in this issue of the journal. Is this the end of the human mind era and the dawn of the reign of computers, Orwell’s 1984 reborn under cover, or just another achievement of rational, scientific thought bestowed upon us by the Enlightenment? I personally believe that progress is inevitable, and human efforts should be aimed at mastering and controlling rather than negating it. We cannot be like the oath-based Luddites who used to destroy textile machines during the Industrial Revolution. In general, technology and scientific innovation are the only way to address the continually increasing environmental, social and health challenges to humanity. We should embrace the products of our own minds, certainly under the critical eye of Aristotelian inquiry, and use them for the benefit of the many. Artificial intelligence is another potentially powerful endeavour, which, when properly studied and developed through experience, should be an indispensable tool towards scientific progress. Computer science has led us on an exciting journey since 1969, when Apollo 11 reached the moon with a computer memory of 32 kilobytes! Indeed, “everything flows”, as Heraclitus taught us more than 2,500 years ago. Demosthenes G Katritsis Editor-in-Chief, Arrhythmia & Electrophysiology Review Hygeia Hospital, Athens, Greece

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Access at: www.AERjournal.com

Electrophysiology and Ablation

Atrial Fibrillation Structural Substrates: Aetiology, Identification and Implications Ahmed M Al-Kaisey,1,2 Ramanathan Parameswaran1,2 and Jonathan M Kalman1,2 1. Department of Cardiology, Royal Melbourne Hospital, Melbourne, Victoria, Australia; 2. Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia

Abstract Atrial remodelling in AF underlines the electrical, structural and mechanical changes in the atria of patients with AF. Several risk factors for AF contribute to the development of the atrial substrate, with some evidence that atrial remodelling reversal is possible with targeted intervention. In this article, the authors review the electrophysiological changes that characterise the atrial substrate in patients with AF risk factors. They also discuss the pitfalls of mapping the atrial substrate and the implications for developing tailored ablation strategies to improve outcomes in patients with AF.

Keywords AF, atrial substrate, atrial remodelling, reverse remodelling, low-voltage area, electroanatomic mapping Disclosure: RP is supported by a National Health and Medical Research Council (NHMRC) research scholarship. JMK is supported by a NHMRC practitioner fellowship, and has received research and fellowship support from Biosense Webster, St Jude Medical and Medtronic. AMAK has no conflicts of interests to declare. Received: 22 April 2020 Accepted: 20 July 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):113–20. DOI: https://doi.org/10.15420/aer.2020.19 Correspondence: Jonathan M Kalman, Department of Cardiology, Royal Melbourne Hospital, Grattan St, Parkville, VIC 3050, Australia. E: jon.kalman@mh.org.au Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

AF is the most common sustained cardiac rhythm disorder and is associated with increased morbidity and mortality. Since the first description of AF initiation by triggers from pulmonary veins sleeves, pulmonary vein isolation (PVI) has become the standard ablation strategy in patients with AF.1 However, freedom from the arrhythmia, particularly in non-paroxysmal AF, remains suboptimal, and it is now clear that, in these patients, AF is maintained by an atrial substrate beyond the pulmonary veins. Although electrical remodelling may be reversible with termination of the arrhythmia, the development of atrial substrate due to fibrosis contributes to the progression of the AF phenotype from paroxysmal to persistent AF, leading to an arrhythmia that is more refractory to intervention.2 It is clear from animal and human studies that prolonged AF can cause this structural change. Moreover, it is also apparent that a range of risk factors associated with AF, including age, obesity, heart failure (HF), valvular heart disease, hypertension (HT), sleep apnoea and alcohol intake, may also progress atrial remodelling. The rise in the prevalence of cardiovascular risk factors (particularly driven by ageing populations and the obesity epidemic) has been associated with an increase in the prevalence of AF and AF-related hospitalisations.3 In this review, we focus on insights from electrophysiological mapping studies in cohorts with AF risk factors. We discuss substrate mapping and its implications for AF management and outcomes, and also focus on potential pitfalls.

introducing the seminal concept that ‘AF begets AF’.4–6 In response to either induced AF or rapid atrial pacing, a reduction in the atrial effective refractory period (ERP) occurs with an increase in the spatial heterogeneity of ERP and loss of normal ERP rate adaptation, all resulting in progressively longer durations of AF. In this model, termination of the arrhythmia results in remodelling reversal, suggesting that sinus rhythm may beget sinus rhythm. However, human studies of early intervention to re-establish sinus rhythm do not fully support this concept; the re-establishment of sinus rhythm has not been found to prevent the progression of AF in the majority of patients.7,8 Ongoing work has indicated that, beyond acute electrical remodelling, structural remodelling also occurs and is not necessarily fully reversible. This socalled second factor has been shown to occur as a result of longer durations of AF. However, the multiple conditions associated with AF also appear to promote significant structural remodelling.

Abnormal Atrial Substrates and Structural Remodelling in Conditions Predisposing to AF It is well known that certain cardiac conditions and risk factors (i.e. age, obesity, HT, HF, structural heart disease, sleep apnoea and alcohol intake) are associated with AF, likely through both different and interacting mechanisms. In the next section, we review the evidence describing the nature of atrial structural remodelling in these conditions, even prior to the development of AF (Figure 1).

The Second Factor: Structural Remodelling is Required for AF Maintenance

The Role of Atrial Stretch

Early studies of animal models have demonstrated that AF promotes acute electrical remodelling, which in turn leads to further AF, thereby

The impact of acute atrial stretch on electrical remodelling has been studied in animal models and in humans. Despite variability in

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Electrophysiology and Ablation Figure 1: Electroanatomical Maps and Electrophysiological Parameters in Different AF Substrates

Control

Fractionated potential Double potential Scar >5mV

Disease

<0.5mV Age Atrial volumes

Hypertension Heart failure n/a

Sleep apnoea

Lone AF

Mitral stenosis

Obesity

Alcohol

n/a

Bipolar voltage

Area voltage <0.5

Atrial conduction velocity Electrogram fractionated

Electroanatomical maps from various AF substrates are shown with bipolar voltage scaled from red for <0.05 mV to purple for > 5mV (except alcohol maps, which are scaled from <0.05 to >0.5 mV). Points with fractionated or double potentials or scar are annotated with red, blue and grey dots, respectively. n/a=not available. Sources: Kistler et al. 2004,38 Dimitri et al. 2012,33 Stiles et al. 2009,41 Mahajan et al. 201830 and Voskoboinik et al. 2019.36 Adapted with permission from Elsevier. Medi et al. 2011.25 Adapted with permission from Wiley. Sanders et al. 2003.22 Adapted with permission from Wolters Kluwer. John et al. 2008.14 Adapted with permission from Oxford University Press.

the reported effect on atrial ERP, evidence from these studies consistently demonstrates conduction slowing, conduction block and increased frequency of AF.9â&#x20AC;&#x201C;11 In studies of atrial stretch related to loss of atrioventricular (AV) synchrony, Sparks et al. demonstrated evidence of both electrical and mechanical remodelling.12,13 Although refractoriness showed a variable increase, there was conduction slowing, sinus node impairment and a decrease in parameters of atrial contractile function. These changes developed over 3 months and were fully reversible with the return of AV synchrony.

Valvular and Congenital Heart Disease The nature of atrial remodelling due to pressure and volume overload associated with either valvular heart disease or congenital heart defects has been studied for a number of different pathologies. Common to these is the development of significant atrial dilatation, creating one of the critical determinants for the maintenance of AF and structural remodelling. In mitral stenosis, John et al. demonstrated the presence of abnormal atrial structural and electrical substrate in patients with symptomatic mitral stenosis referred for balloon valvuloplasty when compared to a control cohort.14 Biatrial mapping demonstrated significantly reduced biatrial voltage, reduced conduction velocity and prolonged ERPs. As expected, patients with mitral stenosis were more susceptible to AF induction with programmed extra stimuli. Such remodelling was found to be more profound in the left atrium (LA) than the right atrium (RA). Balloon valvuloplasty resulted in significant improvements in conduction and in

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bipolar voltage, either acutely or by 3 months of follow-up, indicating that even chronic remodelling may be, in part, reversible.15 Roberts-Thompson et al. studied patients with symptomatic mitral regurgitation referred for valve repair using epicardial plaque mapping in the operating room.16 Their high-density mapping study demonstrated the presence of conduction slowing, conduction heterogeneity with regions of conduction slowing and lines of block particularly in the posterior left atrium. Patients with mitral regurgitation had more advanced remodelling than a comparison group with normal mitral valves undergoing coronary bypass surgery. Morton et al. performed right atrial mapping in patients with atrial septal defect (ASD) before and late after surgical closure.17 Electroanatomic maps of the RA demonstrated the presence of atrial conduction abnormalities, both generally and at the crista terminalis, sinus node dysfunction and atrial dilation, when compared to controls. In their study, closure of the ASD, while associated with significant reduction in atrial size, did not lead to recovery of conduction abnormalities, indicating partial reverse remodelling in this population. In a subsequent study, Roberts-Thomson et al. demonstrated similar atrial remodelling in the LA of ASD patients, indicating that the remodelling process is not confined to the RA in an ASD population.18

Congestive Heart Failure The interaction between HF and AF has been studied in both animals and humans. Li et al. described remodelling â&#x20AC;&#x2DC;of a different sortâ&#x20AC;&#x2122; in a

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Mapping AF Structural Substrates canine model of ventricular tachypacing.19 This was characterised by an increase in conduction heterogeneity associated with interstitial fibrosis that resulted in an increase in AF inducibility. Other studies have demonstrated similar findings.20 Five weeks after HF reversal, neither fibrosis nor AF inducibility were found to demonstrate significant resolution.21 Sanders et al. demonstrated slowing of atrial conduction, low-voltage areas (LVAs), a greater number of fractionated electrograms and abnormal sinus node function in patients with congestive HF (CHF) when compared to a control population.22 Patients with CHF demonstrated increased AF inducibility. More recently, Prahbu et al. performed high-density electroanatomic mapping of both atria in two cohorts of patients: persistent AF with normal left ventricular systolic function (left ventricular ejection fraction [LVEF] >55%) and persistent AF with idiopathic cardiomyopathy (LVEF <45%).23 HF was associated with significantly reduced biatrial bipolar tissue voltages, greater voltage heterogeneity and significantly more biatrial electrogram fractionation compared to no HF, suggesting the impact of HF on structural remodelling above and beyond the effect of AF itself. When patients were restudied 2 years after catheter ablation with maintenance of sinus rhythm and significant improvement or normalisation of LV function, remodelling reversal was found to be incomplete.24 There was a reduction in complex signals and patchy regional increases in voltage, but no improvement in atrial conduction, again indicating that advanced remodelling is unlikely to reverse (Figure 2).

Figure 2: Electroanatomic Maps of the Right Atrium at Baseline and 2 years Follow-up Post-AF Ablation

Right Atrial Electro-Anatomical map Baseline

SVC

Follow up

0.03 mV Bi 5.51 mv

Unadjusted bipolar voltage

0.10 mV Bi 6.65 mv

SVC

Lateral RA

IVC

IVC 0.06 mV Bi 1.00 mv

SVC

D Bipolar voltage ≥1.0mV

SVC

Lateral RA

IVC Fractionated signal

0.06 mV Bi 1.00 mv

IVC

Baseline and follow-up bipolar voltage maps of the RA demonstrating an increase in bipolar voltage and a decrease in fractionation in the posterior-septal segment(s). A,B: Posterior– anterior projection with lateral rotation at baseline; C,D: the same view at follow-up. A,C: Unadjusted automatic bipolar voltage. B,D: Bipolar voltage maps adjusted to 0 to 0.5 to 1.0 mV. Low voltage is represented by red. Fractionated signals are marked with a turquoise arrow and circle. IVC=inferior vena cave; SVC=superior vena cava. Source: Sugumar et al. 2019.24 Reproduced with permission from Elsevier.

Systemic Hypertension Medi et al. performed RA electroanatomic mapping in patients with HT (but no AF) and in controls.25 HT was associated with extensive conduction abnormalities, particularly in the posterior RA at the crista terminalis. In addition, an increased number of LVAs and AF inducibility were noted, despite prolonged ERPs compared to controls. To the best of our knowledge, no studies have evaluated the impact of HT on LA remodelling; however, studies in patients with HF and preserved ejection fraction are ongoing.

Obesity Emerging data have indicated that obesity and increased pericardial fat are associated with a more advanced atrial substrate. A number of animal studies have demonstrated the impact of progressive weight gain on the atrial substrate and inducibility of AF.26,27 Abed et al. demonstrated the progressive change in electrical and structural remodelling in a group of 30 sheep fed a high-calorie diet over an 8-month period.26 Increasing weight was associated with increasing LA volume, fibrosis, upregulation of inflammatory markers, decreased conduction velocity and an increase in conduction heterogeneity. Such changes were found to be associated with an increase in both inducible and spontaneous AF. In a subsequent study, the same group demonstrated that these changes were most marked in the posterior left atrium and were associated with fat infiltration and fibrosis. Other animal studies noted that a high-fat diet could increase AF duration due to slow atrial conduction and reduced pulmonary vein refractoriness without necessarily accompanying obesity.28,29 Mahajan et al. compared atrial electroanatomic maps and epicardial adipose tissue in obese patients with the same data from a non-obese cohort.30 Obesity was found to be associated with an increase in all measures of epicardial adipose tissue (EAT), with a predominant distribution adjacent to the posterior left atrium and the atrioventricular groove. Obese patients had reduced global conduction velocity, increased fractionation and increased LVAs. LVAs were predominantly seen in the posterior and/or

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

inferior LA, matching the location of EAT on cardiac magnetic resonance (CMR) imaging. Another study of the impact of obesity on atrial remodelling also found significant conduction slowing at the pulmonary vein-to-LA junction.31

Obstructive Sleep Apnoea Obstructive sleep apnoea (OSA) is known to be associated with AF.32 Dimitri et al. characterised the atrial substrate among a cohort of patients undergoing AF ablation who either had OSA (apnoea hypopnea index >15) or no OSA.33 Patients with OSA had lower atrial voltage, prolonged conduction times and greater percentage of complex fractionated electrograms, but there was no difference in atrial ERP. Similar findings were recently described by Anter et al. in their cohort of 86 patients (n=43 with OSA and n=43 without OSA) undergoing PVI for paroxysmal AF.34 However, they also reported a higher prevalence of non-pulmonary vein triggers in OSA compared to controls, indicating that the development of AF in this population may be due to autonomically mediated triggers interacting with chronic substrate.

Alcohol Alcohol has recently emerged as an important modifiable risk factor in AF, and both binge and habitual drinking seem to increase the vulnerability to AF through its impact on atrial remodelling. Qiao et al. performed voltage mapping in 122 patients undergoing PVI for paroxysmal AF, and classified them according to their daily alcohol consumption history.35 Heavy drinkers had more LVAs and more AF recurrences compared to moderate drinkers and alcohol abstainers. Importantly, both heavy alcohol consumption and LVAs were independent predictors of AF recurrence. Similar findings were recently found in Voskoboinik et al.’s study of the atrial substrate among alcohol consumers.36 The authors performed high-density electroanatomic mapping of the LA in 75 patients undergoing PVI for AF. Patients were classified as lifelong non-drinkers, mild drinkers (2–7 drinks/week) and

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Electrophysiology and Ablation Figure 3: Rate- and Direction-dependent Variation in Mapped Substrate Marked Variation In Mapped Substrate Patient 2

Patient 1 0.50mV Bi

1.30mV

0.50mV Bi

1.30mV

Patient 3 0.50mV Bi

1.30mV

1.71mV/46ms 1.31mV/42ms

CSD600ms Pacing

remodelling reflected the high prevalence of these conditions in an apparent lone AF population. An alternate hypothesis is that AF is secondary to a primary underlying fibrotic cardiomyopathy, as proposed by Kottkamp et al.42 Human histological and imaging studies evaluating fibrosis in lone and non-lone AF populations have found comparable fibrosis distribution between the two groups,43,44 supporting the idea of a primary fibrotic cardiomyopathy. However, a detailed exclusion of the above causes of remodelling was not performed.

1.60mV/50ms

0.78mV/72ms 0.96mV/75ms

CSD300ms Pacing

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Electroanatomic maps demonstrating significant progressive increase in low-voltage areas (LVAs; <0.5 mV) typically targeted in adjective scar homogenisation ablation strategies according to different pacing methods in three different patients (area in red). Complex fractionated electrograms from corresponding regions in patient 3 (right side, a 72-year-old man with early persistent AF) are longer, with lower voltages in response to each subsequent pacing strategy. Impact of pacing cycle length and wavefront direction in the potential atrial area included in substrate ablation is highlight. AP= anteroposterior; CSD = distal coronary sinus; LSPV = left superior pulmonary vein; PA = posteroanterior. Source: Wong et al. 2019.55 Reproduced with permission from Elsevier.

moderate drinkers (8–21 drinks/week). When compared to alcohol abstinence or mild alcohol consumption, moderate alcohol consumption was associated with significantly lower global atrial voltage, slower conduction velocities and an increased proportion of both complex atrial potentials and LVAs. Moderate drinking, together with age and female sex, were found to be independent predictors for low voltage. Ongoing studies are addressing the question of whether atrial remodelling may reverse with abstinence, and a recent randomised study indicated that abstinence reduces AF recurrence.37

Age It is well known that the prevalence of AF increases with age. A number of animal and human studies have demonstrated the presence of an abnormal electrical substrate in older cohorts, independent of changes in the atrial ERP.38–40 Kistler et al. performed high-density electroanatomic mapping of the RA in 41 patients with no history of AF.38 Patients were stratified into three groups according to age: <30 years, 30–60 years and >60 years. Ageing was associated with regional conduction slowing, anatomically determined conduction delay at the crista terminalis, areas of low voltage, impaired sinus node function, and an increase in atrial ERP.

Lone AF and Fibrotic Cardiomyopathy The term ‘lone AF’ has been variably defined over decades of use, but broadly, can be taken to imply AF in the absence of structural heart disease or HT. In a detailed mapping study, Stiles et al. demonstrated the presence of abnormal atrial substrate in patients with paroxysmal lone AF compared to a control group, even when studied distant to an AF episode.41 Paroxysmal AF patients were found to have atrial dilatation, lower mean voltage, prolonged atrial conduction times, impaired sinus node function and increased atrial ERP compared to the control group. However, in their study, more contemporary causes of atrial remodelling, such as obesity, sleep apnoea and alcohol intake, were not clearly excluded, and it is possible that the observed

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How Best to Define Abnormal Atrial Substrate: Pitfalls On electroanatomic mapping, the assumption inherent in the findings of low voltage, slowed conduction and complex signals is that structural change is present, the hallmark of which is fibrosis.45 Human histological studies have confirmed the presence of atrial fibrosis in patients with AF, and the fibrosis extent correlated with AF duration.43,46,47 However, to date, there is no direct correlation confirming the relationship between atrial substrate on mapping and histological fibrosis. The widely applied definition of abnormal atrial bipolar voltage (<0.5 mV representing LVAs and <0.05 mV representing scar) derives from mapping with an ablation catheter bipole and has never been fully validated in humans.22 The indices have been used to successfully predict outcomes when used to define LVA in patients with paroxysmal or persistent AF.48–50 Furthermore, complex fractionated electrograms and abnormal conduction during sinus rhythm tend to correspond to LVAs, suggesting that they may represent areas of histological fibrosis.51,52 However, multiple potential pitfalls exist when simply using voltage as a marker of atrial remodelling and fibrosis. For example, atrial wall thickness varies markedly between different atrial regions (e.g. trabeculated compared with smooth-walled atrium), and also from patient to patient. It is highly probable that normal voltage also varies considerably and may defy a simple cut-point definition. Moreover, these values were described when using an ablation bipole for mapping. The start of the century has witnessed the introduction of multielectrode mapping catheters for electroanatomic mapping.53 Compared with linear, single-point conventional mapping catheters, multielectrode mapping catheters have the combination of smaller electrode size, smaller interelectrode distance and multiple splines. This allows for recording electrograms from a significantly smaller underlying tissue diameter with multiple orientations. This translates to higher mapping resolution that can identify heterogeneity within the area of low voltage, localising channels of surviving bundles. Moreover, the smaller electrode and closer interelectrode spacing means less signal averages and cancellation effects, which may translate to higher recorded bipolar voltage amplitude with shorter electrogram duration.53,54 However, the criteria for bipolar low voltage using multielectrode mapping catheters has not been systematically revisited. It is also important to note that both the distribution and extent of LVAs on electroanatomic mapping is critically dependent on the directionally and rate of wavefront prorogation. Wong et al. demonstrated that a change in pacing site or cycle length could change the region defined as low voltage by up to 30% (Figure 3).55 The nature of the rhythm is also of critical importance. Several early studies demonstrated that regions of low bipolar voltage and complex fractionated electrograms recorded during AF frequently correspond with areas of normal atrial bipolar voltages in sinus rhythm.52,56 However, recent studies using omnipolar mapping, indicating that electrode orientation is a key determinant of recorded bipolar voltage,

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Middle-aged man with a history of permanent pacemaker insertion in 2004 for sick sinus syndrome. He underwent circumferential pulmonary vein isolation in July 2005 for symptomatic high-burden AF. He remained AF free over the following 13 years, but gained 12 kg, developed hypertension and moderate obstructive sleep apnoea during that period. Recurrence of symptomatic high-burden AF in February 2018 was documented. Redo procedure demonstrated enduring isolation in all four pulmonary veins; however, repetitive atrial ectopic activity initiating AF in the posterior wall (PW) was noted. Following isolation of the PW, the patient remained arrhythmia free over a 12-month period. ABL = ablation catheter; CPVI = circumferential pulmonary vein isolation; CSd = distal coronary sinus; CSp = proximal coronary sinus; HBE = His bundle electrogram; LA = left atrium.

have raised the possibility that mapping during AF may provide an improved evaluation of underlying substrate. In an elegant study using omnipolar mapping with a grid catheter, Haldar et al. showed that bipole orientation has a significant impact on bipolar electrogram (EGM) voltages obtained during sinus rhythm (SR) and AF.57 In that study, omnipolar EGMs were able to extract maximal voltages from AF signals not influenced by directional factors, wavefront collision or fractionation. Other techniques to identify substrate have focused on signal characteristics. Approaches beyond the traditional identification of complex fractionated electrograms have included targeting spatiotemporal dispersion of electrograms; targeting regions of prolonged and continuous fractionation; various approaches to determine the site of highest activation frequency, such as dominant frequency; or using activation gradients, such as in the stochastic trajectory analysis of ranked signals mapping approach.58â&#x20AC;&#x201C;61 In addition to mapping techniques, multimodality imaging can provide a non-invasive assessment of the abnormal atrial substrate in patients with AF.62 In addition to atrial size and morphology, mechanical and structural remodelling parameters can be obtained via strain imaging and late gadolinium enhancement CMR imaging (LGE-MRI). LGE-MRI has been proposed as a more effective way in which to identify regions of atrial fibrosis, and a considerable body of work indicates that this may be feasible. However, not many departments have been able to replicate these data, particularly for the reliable identification of more subtle interstitial fibrosis.62 A key problem is how to accurately define the number of standard deviations (SD) from the mean reference signal intensity, which most closely describes accurate scar volume. In an animal ablation study, the point at which CMR imaging and histological scar volume were equal was in the steepest portion of the graph, which meant any small change in SD (chosen by definition) would create a corresponding large difference between CMR imaging and histological

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measured volumes.63 Chen et al. studied the correlation between delayed enhancement on CMR imaging and LVAs on electroanatomic mapping in 16 patients with persistent AF.64 There was a mismatch between delayed enhancement areas and LVAs; delayed enhancement was present in 61% of LVAs, whereas low voltage was present in 28% of delayed enhancement areas. In another recent multimodal examination of AF substrate, Zghaib et al. demonstrated that LGE-MRI, high-density mapping and point-by-point mapping with the ablation catheter demonstrated good correlation in delineating electroanatomical AF substrate, providing some enthusiasm for the routine use of CMR imaging.65 Given the current challenges in technique and reproducibility, and the lack of prospective studies, the current role for LGE-MRI in the management of patients with non-paroxysmal AF remains limited to a relatively small number of centres with extensive experience in the technique. Data from the prospective Delayed-Enhancement MRI Determinant of Successful Radiofrequency Catheter Ablation of Atrial Fibrillation-II (DECAAF-II) study are eagerly awaited.62

Implications of Accurately Identifying the Atrial Substrate Numerous studies have indicated that advanced atrial substrate is a risk factor for recurrence following AF ablation.48,49,66,67 In addition, preliminary and observational studies suggest that isolation or homogenisation of these abnormal regions significantly improves postablation arrhythmia-free survival.59,69,70 Schreiber et al. implemented the concept box isolation of fibrotic areas and studied its impact when added to traditional PVI on AF-free survival among 92 patients with fibrotic atrial cardiomyopathy, as defined by voltage mapping.71 This approach was associated with a 69% arrhythmia-free survival at 16 Âą 8 months. In a single-centre randomised study, Kircher et al. examined whether targeting LVAs in addition to PVI was more effective than PVI plus linear ablation in patients with paroxysmal and persistent AF.72 At

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Electrophysiology and Ablation Figure 5: Time-dependent Atrial Remodelling and Development of AF “Lone” AF Remodelling Development of AF risk factors

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12 months, the LVA ablation group had better arrhythmia-free survival compared to the PVI plus linear ablation group (68% versus 42%, p=0.003). More recently, Yang et al. randomised 229 patients with nonparoxysmal AF to either low-voltage, zone-guided ablation or standard stepwise ablation (including linear ablation), but did not show a significant improvement in arrhythmia-free survival at 18 months (74% versus 71%, p=0.32).73 However, procedure times, total ablation time and fluoroscopy times were significant shorter using the LVA-guided approach. Further multicentre studies are needed to better define the role of LVA-guided substrate ablation in the management of patients with persistent AF. A prospective multicentre randomised study is currently ongoing to examine the efficacy of atrial fibrosis (based on MRI-LGE)-guided ablation intervention in the treatment of patients with persistent AF (DECAAF-II, NCT02529319).

Progression and Regression of the Atrial Substrate In many patients with AF, there is gradual progression from shortlasting paroxysmal AF to more frequent and persistent AF (Figure 4).74,75 This progression is, at least in part, driven by the evolution of the atrial

Haïssaguerre M, Jaïs P, Shah DC, et al. Spontaneous initiation of atrial fibrillation by ectopic beats originating in the pulmonary veins. N Engl J Med 1998;339:659–66. https://doi. org/10.1056/nejm199809033391003; PMID: 9725923. Iwasaki YK, Nishida K, Kato T, Nattel S. Atrial fibrillation pathophysiology: implications for management. Circulation 2011;124:2264–74. https://doi.org/10.1161/ circulationaha.111.019893; PMID: 22083148. Patel NJ, Deshmukh A, Pant S, et al. Contemporary trends of hospitalization for atrial fibrillation in the United States, 2000 through 2010: implications for healthcare planning. Circulation 2014;129:2371–9. https://doi.org/10.1161/ circulationaha.114.008201; PMID: 24842943. Wijffels MC, Kirchhof CJ, Dorland R, Allessie MA. Atrial fibrillation begets atrial fibrillation. A study in awake chronically instrumented goats. Circulation 1995;92:1954–68. https://doi.org/10.1161/01.cir.92.7.1954; PMID: 7671380. Elvan A, Wylie K, Zipes DP. Pacing-induced chronic atrial fibrillation impairs sinus node function in dogs: electrophysiological remodeling. Circulation 1996;94:2953–60. https://doi.org/10.1161/01.cir.94.11.2953; PMID: 8941126. Morillo CA, Klein GJ, Jones DL, Guiraudon CM. Chronic rapid atrial pacing. Structural, functional, and electrophysiological characteristics of a new model of sustained atrial fibrillation. Circulation 1995;91:1588–95. https://doi.org/10.1161/01. cir.91.5.1588; PMID: 7867201. Cohen M, Naccarelli GV. Pathophysiology and disease

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substrate as a result of underlying risk factors and the arrhythmia itself. As such, the hypothesis emerged that both risk factor management and rhythm control might arrest the progression and perhaps reverse the remodelling of the atrial substrate in AF (Figure 5).76,77 The data are mixed. Animal studies of structural remodelling reversal have shown variable results, but established replacement fibrosis has not resolved.78 In humans, AF ablation did not result in reverse remodelling at 6 months, with some evidence of further progression.79 Studies of risk factor management have indicated a significant propensity for reverse remodelling in animal studies. In humans, risk factor management has resulted in fewer recurrences of AF after ablation, and reversal of AF progression.37,76,80 Patients with weight loss frequently regress from a persistent to paroxysmal phenotype and progress in the opposite direction much less frequently.82

Conclusion The abnormal atrial substrate plays a key role in the perpetuation of AF. While developing an ablation strategy targeting the atrial substrate seems logical, the current mixed results may reflect uncertainties as to how best to identify the critical arrhythmogenic substrate. Future improvements in mapping and imaging technology will certainly improve our understanding of the atrial substrate, and potentially pave the way for the development of tailored ablation therapies to improve arrhythmia outcomes.

Clinical Perspective • Structural remodelling plays an important role in the development and clinical progression of AF. • Beyond the impact of AF itself on structural remodelling, multiple associated conditions contribute to the development of abnormal atrial substrate. • Further improvements in current atrial substrate imaging and mapping modalities are required to improve our understanding of structural remodelling to better guide substrate-based ablation strategies. • Promising emerging work suggests an important role for risk factor management in arresting or reversing atrial remodelling and in improving AF outcomes. Further work is required to define the broader efficacy of this approach.

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AF ablation guided by spatiotemporal electrogram dispersion without pulmonary vein isolation: a wholly patient-tailored approach. J Am Coll Cardiol 2017;69:303–21. https://doi.org/10.1016/j. jacc.2016.10.065; PMID: 28104073. 59. Jadidi AS, Lehrmann H, Keyl C, et al. Ablation of persistent atrial fibrillation targeting low-voltage areas with selective activation characteristics. Circ Arrhythm Electrophysiol 2016;9:e002962. https://doi.org/10.1161/circep.115.002962;

PMID: 26966286. 60. Sanders P, Berenfeld O, Hocini M, et al. Spectral analysis identifies sites of high-frequency activity maintaining atrial fibrillation in humans. Circulation 2005;112:789–97. https://doi. org/10.1161/circulationaha.104.517011; PMID: 16061740. 61. Honarbakhsh S, Hunter RJ, Ullah W, et al. ablation in persistent atrial fibrillation using stochastic trajectory analysis of ranked signals (STAR) mapping method. JACC Clin Electrophysiol 2019;5:817–29. https://doi.org/10.1016/j.jacep.2019.04.007; PMID: 31320010. 62. Ghannam M, Oral H. Mapping and imaging in non-paroxysmal AF. Arrhythm Electrophysiol Rev 2019;8:202–9. https://doi. org/10.15420/aer.2019.18.1; PMID: 31463058. 63. Harrison JL, Jensen HK, Peel SA, et al. Cardiac magnetic resonance and electroanatomical mapping of acute and chronic atrial ablation injury: a histological validation study. Eur Heart J 2014;35:1486–95. https://doi.org/10.1093/eurheartj/ eht560; PMID: 24419806. 64. Chen J, Arentz T, Cochet H, et al. Extent and spatial distribution of left atrial arrhythmogenic sites, late gadolinium enhancement at magnetic resonance imaging, and lowvoltage areas in patients with persistent atrial fibrillation: comparison of imaging vs. electrical parameters of fibrosis and arrhythmogenesis. Europace 2019;21:1484–93. https://doi. org/10.1093/europace/euz159; PMID: 31280323. 65. Zghaib T, Keramati A, Chrispin J, et al. Multimodal examination of atrial fibrillation substrate: correlation of left atrial bipolar voltage using multi-electrode fast automated mapping, pointby-point mapping, and magnetic resonance image intensity ratio. JACC Clin Electrophysiol 2018;4:59–68. https://doi. org/10.1016/j.jacep.2017.10.010; PMID: 29520376. 66. Marrouche NF, Wilber D, Hindricks G, et al. Association of atrial tissue fibrosis identified by delayed enhancement MRI and atrial fibrillation catheter ablation: the DECAAF study. JAMA 2014;311:498–506. https://doi.org/10.1001/jama.2014.3; PMID: 24496537. 67. Vlachos K, Efremidis M, Letsas KP, et al. Low-voltage areas detected by high-density electroanatomical mapping predict recurrence after ablation for paroxysmal atrial fibrillation. J Cardiovasc Electrophysiol 2017;28:1393–402. https://doi. org/10.1111/jce.13321; PMID: 28884923. 68. Kottkamp H, Berg J, Bender R, et al. Box isolation of fibrotic areas (BIFA): a patient-tailored substrate modification approach for ablation of atrial fibrillation. J Cardiovasc Electrophysiol 2016;27:22–30. https://doi.org/10.1111/jce.12870; PMID: 26511713. 69. Rolf S, Kircher S, Arya A, et al. Tailored atrial substrate modification based on low-voltage areas in catheter ablation of atrial fibrillation. Circ Arrhythm Electrophysiol 2014;7:825–33. https://doi.org/10.1161/circep.113.001251; PMID: 25151631. 70. Yang G, Yang B, Wei Y, et al. Catheter ablation of nonparoxysmal atrial fibrillation using electrophysiologically guided substrate modification during sinus rhythm after pulmonary vein isolation. Circ Arrhythm Electrophysiol 2016;9:e003382. https://doi.org/10.1161/circep.115.003382; PMID: 26857907. 71. Schreiber D, Rieger A, Moser F, Kottkamp H. Catheter ablation of atrial fibrillation with box isolation of fibrotic areas: lessons on fibrosis distribution and extent, clinical characteristics, and their impact on long-term outcome. J Cardiovasc Electrophysiol 2017;28:971–83. https://doi.org/10.1111/jce.13278; PMID: 28635186. 72. Kircher S, Arya A, Altmann D, et al. Individually tailored vs. standardized substrate modification during radiofrequency catheter ablation for atrial fibrillation: a randomized study. Europace 2018;20:1766–75. https://doi.org/10.1093/europace/ eux310; PMID: 29177475. 73. Yang B, Jiang C, Lin Y, et al. STABLE-SR (Electrophysiological Substrate Ablation in the Left Atrium During Sinus Rhythm) for the treatment of nonparoxysmal atrial fibrillation: a prospective, multicenter randomized clinical trial. Circ Arrhythm Electrophysiol 2017;10:e005405. https://doi.org/10.1161/ circep.117.005405; PMID: 29141843. 74. Abe Y, Fukunami M, Yamada T, et al. Prediction of transition to chronic atrial fibrillation in patients with paroxysmal atrial fibrillation by signal-averaged electrocardiography: a prospective study. Circulation 1997;96:2612–6. https://doi. org/10.1161/01.cir.96.8.2612; PMID: 9355901. 75. Cosio FG, Aliot E, Botto GL, et al. Delayed rhythm control of atrial fibrillation may be a cause of failure to prevent recurrences: reasons for change to active antiarrhythmic treatment at the time of the first detected episode. Europace 2008;10:21–7. https://doi.org/10.1093/europace/eum276; PMID: 18086696. 76. Pathak RK, Middeldorp ME, Meredith M, et al. Long-term effect of goal-directed weight management in an atrial fibrillation cohort: a long-term follow-up study (LEGACY). J Am Coll Cardiol 2015;65:2159–69. https://doi.org/10.1016/j.jacc.2015.03.002; PMID: 25792361. 77. Scaglione M, Gallo C, Battaglia A, et al. Long-term progression from paroxysmal to permanent atrial fibrillation following transcatheter ablation in a large single-center experience. Heart Rhythm 2014;11:777–82. https://doi.org/10.1016/j. hrthm.2014.02.018; PMID: 24561164.

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Electrophysiology and Ablation 78. Nattel S. Molecular and cellular mechanisms of atrial fibrosis in atrial fibrillation. JACC Clin Electrophysiol 2017;3:425–35. https://doi.org/10.1016/j.jacep.2017.03.002; PMID: 29759598. 79. Teh AW, Kistler PM, Lee G, et al. Long-term effects of catheter ablation for lone atrial fibrillation: progressive atrial electroanatomic substrate remodeling despite successful

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ablation. Heart Rhythm 2012;9:473–80. https://doi.org/10.1016/j. hrthm.2011.11.013; PMID: 22079885. 80. Brandes A, Smit MD, Nguyen BO, et al. Risk factor management in atrial fibrillation. Arrhythm Electrophysiol Rev 2018;7:118–27. https://doi.org/10.15420/aer.2018.18.2; PMID: 29967684. 81. Wyse DG, Van Gelder IC, Ellinor PT, et al. Lone atrial fibrillation:

does it exist? J Am Coll Cardiol 2014;63:1715–23. https://doi. org/10.1016/j.jacc.2014.01.023; PMID: 24530673. 82. Middeldorp ME, Pathak RK, Meredith M, et al. Prevention and regressive effect of weight-loss and risk factor modification on atrial fibrillation: the REVERSE-AF study. Europace 2018;20:1929–35. https://doi.org/10.1093/europace/euy117; PMID: 29912366.

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Electrophysiology and Ablation

A New Era in Zero X-ray Ablation Giuseppe Mascia1 and Marzia Giaccardi2 1. Department of Internal Medicine, IRCCS Ospedale Policlinico San Martino, University of Genoa, Genoa, Italy; 2. Department of Internal Medicine, Azienda USL Toscana Centro, Florence, Italy

Abstract In this article, the authors focus on the importance of the zero X-ray ablation approach in electrophysiology. Radiation exposure related to conventional transcatheter ablation carries small but non-negligible stochastic and deterministic effects on health. Non-fluoroscopic mapping systems can significantly reduce, or even completely avoid, radiological exposure. The zero X-ray approach determines potential clinical benefits in terms of reduction of ionising radiation exposure, as well as safe technical advantages. The use of this method can result in similar outcomes when compared to the conventional fluoroscopic technique. These results are achieved without altering the duration, or compromising the effectiveness and safety, of the procedure. The zero X-ray ablation approach is a feasible and safe alternative to fluoroscopy, which is often only used in selected cases for troubleshooting. The non-fluoroscopic approach is considered a milestone for cancer prevention in ablation procedures.

Keywords Arrhythmia, cancer prevention, catheter ablation, radiation risk, zero-fluoroscopy, X-ray ablation approach Disclosure: The authors have no conflicts of interest to declare. Received: 19 January 2020 Accepted: 3 July 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):121–7. DOI: https://doi.org/10.15420/aer.2020.02 Correspondence: Giuseppe Mascia, Department of Internal Medicine, Clinic of Cardiovascular Diseases, IRCCS Ospedale Policlinico San Martino, University of Genoa, Largo Rosanna Benzi 10, 16132, Genoa, Italy. E: giuseppe_mascia@virgilio.it Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

X-rays used in interventional cardiology are proven (class I) carcinogens, and the electrophysiology community should make every effort to give “the right imaging exam, with the right dose, to the right patient”.1 This may be an effective strategy for the primary prevention of cancer for physicians, medical staff and patients (particularly children, young adults and women).2 The impact of X-rays on male and female reproductive health is well known.3 In men, radiation exposure could determine transient sperm count deterioration, resulting in long-lasting or permanent sterility, whereas in women, it can lead to alterations in the hypothalamic–pituitary axis function, affecting fertility and pregnancy outcomes.4 X-rays could lead to potential brain malignancies or long-lasting cognitive impairment, and microRNA dysregulation has been found to be related to certain forms of brain cancer and Alzheimer’s disease.5,6 Moreover, during interventional cardiology procedures, the left side, in particular, is usually exposed to higher radiation doses.7 Radiation exposure related to conventional radiofrequency catheter ablation carries small but non-negligible stochastic and deterministic effects on health.2 These effects are cumulative and potentially more harmful, and are worse in obese patients, who may need a far higher dose of radiation than people of normal weight, increasing their risk of cancer.2,8 Lead aprons can place considerable pressure on the spinal column, and wearing them for hours while standing has potentially detrimental consequences. The long-term use of lead aprons is known to result in orthopaedic disability, and as consequence, early retirement among physicians, technologists and

nurses.9,10 Interventional cardiologists have reported neck and back pain, more time lost from work and a higher incidence of cervical disc herniations, as well as multiple-level disc disease.11 Therefore, several tools have recently been developed to facilitate arrhythmia mapping and ablation, including 3D electroanatomic mapping systems, magnetic navigation and intracardiac echocardiography, which significantly reduce the need for the fluoroscopic visualisation of catheters.12 Comparable long-term ablation outcomes, with clinical benefits for both patients and physicians, have been documented; the non-fluoroscopic approach is considered a feasible and safe alternative to fluoroscopy for arrhythmias ablation.12–15 The zero X-ray ablation approach is a milestone for cancer prevention in electrophysiological procedures.

The History of Zero X-ray Procedures Transcatheter ablation has undergone impetuous advances in the past 25 years. Ablation mechanisms have been largely investigated, with electrophysiologists focusing on the link between anatomical aspects and electrophysiological properties.16–21 In the 2002 Pediatric Radiofrequency Ablation Registry, Kugler et al. compared ‘early’ and ‘recent’ eras, and found that the mean overall fluoroscopic time decreased by 21% in the paediatric population (from 50.9 ± 39.9 minutes in the early era to 40.1 ± 35.1 minutes in the recent era).22 However, X-ray doses were still high, and further improvements were necessary. In a study in the same year, Drago et al. used a 3D navigation system to eliminate fluoroscopic exposure to 21 paediatric patients.23 They demonstrated that ablation of right accessory pathways in children could

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Electrophysiology and Ablation Table 1: Studies on the History of Zero X-ray Procedures Author

Study Type

Arrhythmia Included

Patients (n)

Follow-up (Months)

Drago et al. 200223

Re non-RT

Right AP

15 ± 7

Sporton et al. 200424

Pro RT

AVNRT, right AFL, AP, AT, VT

102

Raju et al. 2016

Re non-RT

Casella et al. 201626

Pro RT

AVNRT, right AP, Left AP, AFL, AT

262

Giaccardi et al. 201612

Re non-RT

AVNRT, right AFL, AP, AT, VT, other

442

Pani et al. 2018

Pro non-RT

AVNRT, right AFL, right AP, left AP, AT

435

Giaccardi et al. 201913

Re non-RT

PVC, AF, right AFL, left AFL, AV node ablation, AVNRT, AP, AT, VT

266

35 ± 19

Santoro et al. 201914

Pro non-RT

AVNRT, AP, AFL, AT, PVC/VT

485

AFL = atrial flutter; AP = accessory pathway; AT = atrial tachycardia; AVNRT = atrioventricular nodal re-entrant tachycardia; NA = not available; pro non-RT = prospective non-randomised; pro RT = prospective randomised trial; PVC = premature ventricular extra beat; re non-RT = retrospective non-randomised; VT = ventricular tachycardia.

be performed without fluoroscopy, using a single catheter with minimal amounts of radiofrequency applications, with a high success rate.23 There was a considerable reduction in the use of fluoroscopy after procedure 8, with a definitive and complete elimination of fluoroscopy from procedure 12 to procedure 21.23 Their study represented the start of the zero X-ray era.23 Two years later, in a study of 102 randomly selected patients referred for catheter ablation, Sporton et al. compared the routine use of electroanatomic imaging with that of a conventional fluoroscopically guided activation map, and documented a similar acute

reduce or eliminate ionising radiation exposure. These reductions were achieved without altering the duration, or compromising the safety and effectiveness, of the procedure. In 2019, our group published the longterm outcomes of 266 patients who had undergone zero X-ray ablation, as no information was available on the long-term benefits.13 Patients were followed up for an average of 2.9 ±1.6 years, and a 100% rate of acute success was observed, with a complication rate of 0.8%; chronic success was achieved in 90.8% of cases, confirming that the complete elimination of fluoroscopy is advantageous and does not compromise

procedural success with both strategies.24

results or patient safety.13

In 2005, the American College of Cardiology recommended that all catheterisation laboratories should adopt the ALARA (as low as reasonably achievable) principle for radiation doses, constituting a pivotal step towards minimising radiation use in invasive cardiology.25 In a multicentre randomised trial, Casella et al. compared a minimally fluoroscopic ablation with conventional fluoroscopic-guided ablation for supraventricular tachycardias in terms of ionising radiation exposure for 262 patients.26 They focused on the radiation exposure during electrophysiological procedures as non-negligible for both patients and medical staff, and found that a minimally fluoroscopic approach dramatically reduced the estimated risk of cancer incidence and mortality (96% reduction). They also found a reduction in estimated years of life lost and years of life affected, while retaining the safety and efficacy of procedures.26 Based on these findings, the electrophysiology community appealed to the industry to reduce costs and educate physicians to facilitate the implementation of this new electrophysiology

In a multicentre prospective study, the Zero Fluoro Study Group evaluated the determinants of zero-fluoroscopic ablation of 430 supraventricular tachycardias in 20 centres.15 The multivariable analysis identified the following predictors of zero-fluoroscopy: operator’s will, experience with >30 procedures, patient’s age and the type of arrhythmia (electrophysiological study and atrioventricular nodal reentry tachycardia ablation having the highest probability of zerofluoroscopy). The Zero Fluoro Study Group confirmed high safety and effectiveness profiles.15 In a recent study, Santoro et al. showed that catheter ablation can be performed without X-ray after an adequate learning curve.14 In 2011, they commenced an X-ray-minimisation programme using the CARTO System (Biosense Webster), with the intention to not aid X-ray unless strictly necessary. From 2011 to 2013, catheter ablations were performed without X-ray in 38.5% of cases, whereas from 2014 to 2017, there were no differences between the two groups in acute success, complications or duration for 525

for left atrial procedures.27 In their study, Raju et al. demonstrated that general anaesthesia, transoesophageal echocardiography and contactforce mapping catheters may all facilitate a minimised fluoroscopic approach among AF ablation patients.28 In this population, complete zero-fluoroscopy was possible in cases with patent foramen ovale (PFO), which was documented in 36% of patients.28

procedures in 96.2% of cases (Table 1).14

In 2016, we published a study of 442 consecutive patients who were referred for radiofrequency catheter ablation during a 5-year period (2009–2013).12 The patients were included in a retrospective observational study, where the first 145 patients (group 1) were treated only under fluoroscopic guidance; the other 297 patients (group 2) were treated with a non-conventional mapping system.12 The acute success rate did not differ between two groups, and there were no differences in either the procedure or complication rate. Moreover, fluoroscopic exposure in group 2 was significantly reduced compared with group 1 (14 ± 6 seconds versus 1,159 ± 833 seconds, p<.0001).12 We demonstrated how a nearzero radiation approach could lead to similar outcomes and significantly

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Additional Advantages of Zero X-ray Ablation In addition to the reduction in X-ray exposure, a non-conventional mapping system could offer several benefits. In the EnSite Precision cardiac mapping system (Abbott), catheter electrodes are detected and displayed based on the impedance measurements from three separate, orthogonal electrical fields, visualising any catheter within the system. The observable region, in particular, is wider, and these catheters can be visualised from the point of access (femoral vein or femoral artery) to the heart.29 The system’s drawbacks include a shift in geometry resulting from impedance changes, as lung volumes or total body fluid volumes change; shift could also occur due to patient perspiration, as well as changes in reference electrode contact.29 However, the benefits outweigh its limitations, such as the addition of magnetic capabilities of newer ablation and mapping catheters.30 The CARTO System functions by measuring magnetic fields, rather than electrical impedances, and is less prone to shift, but requires proprietary

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Zero X-ray Ablation catheters (no catheter visualisation outside the magnetic field) and a longer time to draw a reasonable geometry.29 The Rhythmia mapping system (Boston Scientific) was specifically developed to support high-density/high-resolution mapping, and is a hybrid localisation system.31,32 In particular, magnetic tracking supports navigation-enabled catheters, providing maximum accuracy and efficiency (magnetic localisation ≤1 mm), whereas open architecture supports impedancebased tracking of non-navigation-enabled catheters for flexibility of choice (impedance localisation ≤2 mm).31,32 However, each of these systems functions in a unique manner, and due to rapid improvements, deficiencies are quickly disappearing. Currently, mapping systems are able to locate the correct position of any pole at any time, and allow an accurate reconstruction of the geometry of both heart chambers and vessels, simplifying navigation and speeding up subsequent phases of the procedure.12 It is also helpful to understand the relationship between bipoles and cardiac anatomy, and between different structures and facilitating complex anatomy cases, continuously visualising two projections at the same time.33 Mapping systems allow visualisation of the catheters from the beginning to the end of the procedure.

Figure 1: Ultrasound-guided Central Venous Cannulation

Femoral artery

Femoral vein

In our laboratory, the first catheter inserted is a quadripolar/octopolar steerable catheter through the femoral vein, positioned in the coronary sinus (CS), whereas other diagnostic catheters are inserted and advanced using the previously reconstructed geometry as a guiding path. While moving the catheters, new anatomical points are typically collected in order to better define the boundaries of the areas of interest (both inferior and superior vena cava ostium, CS ostium, right atrial appendage, His bundle region). Integration with the continuous monitoring of intracavitary electrograms is useful during completely different ablation procedures.12 In cases of AP ablation, the location of the AP could be marked and still used to direct radiofrequency pulses in cases of ‘bump’, causing the AP to be no longer visible. In cases of atrioventricular nodal re-entrant tachycardia ablation, the procedure can also be simplified because of an optimal reconstruction of the Koch’s triangle, the anterior area of the CS and the proximity of the His bundle.12,13 In typical atrial flutter (AFL) cases, an activation map during CS stimulation may easily locate any gap along the isthmus ablation line.12,13 However, in atypical AFL, atrial tachycardia and ventricular tachycardia (VT) cases, mapping systems can be used to visualise arrhythmic circuits through activation maps, and to evaluate the electrical substrate through voltage maps.12,13 The high-density multielectrode approach has significantly improved mapping of both complex atrial and VTs, with quicker and more accurate map creation.31,32 The additional advantages of a zero X-ray approach during pulmonary vein isolation should be considered. For example, it might be difficult to insert a standard spiral catheter in both lower pulmonary veins; in this case, it is possible to capture the spiral using a deflectable ablation catheter and to carry it in the lower vessels.

Our Daily Zero X-Ray Approach: Tips and Tricks Ultrasound-guided Central Venous/ Arterial Cannulation Ultrasound probes of 7–10 MHz are suitable for an ultrasound-guided central venous or arterial cannulation. Arteries are pulsatile and are identifiable, as they are difficult to compress. However, veins are nonpulsatile, are easily compressible and may distend when the patient performs Valsalva manoeuvre. A Doppler verification may also be used

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Needle tip

Ultrasound-guided central venous cannulation allows an accurate puncture of the common femoral vein (blue circle), below the inguinal ligament.

to confirm the anatomy. The superficial artery may overlie the femoral vein, and ultrasound imaging allows a differentiation of these structures, as well as an accurate puncture of the common femoral vein below the inguinal ligament during basic electrophysiology (Figure 1).

Zero X-ray Catheter Insertion: From the Groin Area to the Heart After obtaining femoral vein access with short sheaths, the catheter is threaded through the patient’s groin area to the heart. An anterior catheter direction is typically suggested to avoid collateral vessels. This direction may lead to the heart with no intermediate stops, as the anterior face of the inferior vena cava has no collateral vessels (Figure 2). The force that the catheter exerts on the blood vessel depends on the physician’s experience. Utilisation of ‘force-sensing’ ablation catheters may provide a real-time measure of the contact force between the catheter and the vessels, without the use of X-rays. Monitoring electrograms for an atrial signal will inform the operator when the catheter is in the right atrium.

Patent Foramen Ovale and Fossa Ovalis Mapping A PFO may be found after inserting the catheter into the right atrium and generating a 3D map with enough detail to identify both the septum and the fossa ovalis. Around 30% patients may have a PFO, allowing left-side procedures without the need for transseptal puncture (Figure 3).34–36

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Electrophysiology and Ablation Figure 2: Anterior Catheter Direction May Lead from the Groin Area to the Heart with No Intermediate Stops

transoesophageal or intracardiac echocardiography (ICE) utilisation, is critical to reduce or minimise the use of X-rays. In the near-zero X-ray approach, the transseptal sheath may be visualised by inserting the ablation catheter via the long sheath and guiding it up to the superior vena cava (SVC) using the map as a guide. Once in the SVC, the sheath may be advanced slowly to cover the proximal ablation pole (which, for example, can be determined when the pole turns black on the CARTO System, or when a catheter deformation is documented on the Abbott system). The ablation catheter is then removed, and the physician may insert a dilator over a wire. The wire is then withdrawn and a transseptal needle is inserted 2 cm from the tip. At this point, the whole transseptal apparatus is withdrawn while looking at the transoesophageal or ICE images. The sheath could be observed to fall along the fossa ovalis, posteriorly directed towards the left-sided pulmonary veins. It is also possible to highlight the tip of the needle connecting the stylet to the system to confirm the descent of the needle tip until the fossa ovalis. Finally, when the needle reaches the fossa ovalis, it is possible to confirm its presence using transoesophageal or ICE images (Figure 4). Bidirectional guiding sheaths can be visualised on the mapping system and are important for eliminating sole dependence on fluoroscopy to determine their location.38

Contact-force Ablation Catheter Use During the Femoral Artery Approach In the case of left chamber arrhythmic substrates, for which transseptal puncture is not required, the ablation catheter is inserted through the femoral artery from the start, as it is for the venous system. Modern ablation catheters enable monitoring of the contact force to avoid endothelial damage (Figure 5). Therefore, a contactforce catheter may not only be a therapeutic approach to arrhythmias but also a tool for achieving accurate characterisation of contact in the aortic vessel.

Anterior catheter direction may lead from the groin area to the heart with no intermediate stops, as the anterior face of the inferior vena cava has no collateral vessels.

Figure 3: Patent Foramen Ovale Allowing Left-side Procedures Without the Need for Transseptal Puncture

3D Imaging of the Oesophagus Before Pulmonary Vein Isolation Procedures In our daily approach, the integration of an oesophageal tag into the electroanatomic left atrial map is usually performed during pulmonary vein isolations. The insertion of a quadripolar catheter into the oesophagus enables its 3D reconstruction and intraprocedural localisation. This approach can help physicians to correctly evaluate both the localisation of oesophagus and the distance between the posterior part of the left atrium and the anterior part of oesophagus (Figure 6). 3D imaging of the oesophagus may help to avoid an atrialoesophageal fistula,39,40 which is a rare but lethal complication of AF ablation. While imaging modalities have improved, it is important for clinicians to maintain heightened awareness of this complication in post-ablation patients.

Our Perspectives

Transseptal Puncture: The Importance of an Adequate Learning Curve Transseptal puncture could cause potential issues when performing left-side zero X-ray procedures.37 In these cases, an in-depth understanding of cardiac anatomy, as well as high-level

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Innovative solutions have been found for reducing the dose per examination in all fields of medical imaging, including zero-fluoroscopy in electrophysiology, and the cancer- and non-cancer-related effects of medical radiation is currently the focus of the scientific community.2 However, awareness of risks remains the best protection against radiation exposure. More information about the harmful effects of ionising radiation is required in the form of antismoking, anti-alcohol and anti-obesity campaigns, as risk awareness may lead to a risk reduction. Zero X-ray ablation uses expensive technology and equipment. In 2013, Winkle et al. estimated a high cost per case for the use of magnetic navigation ablation.41

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Zero X-ray Ablation Figure 4: Transseptal Puncture Highlighting the Tip of the Needle to Confirm its Descent A

Transseptal puncture highlighting the tip of the needle to confirm its descent until the fossa ovalis (red dot; A) and intracardiac echocardiography utilisation to confirm the ‘tenting’ of fossa ovalis (B).

Figure 5: Contact-force Catheter Inserted Through the Femoral Artery

Figure 6: 3D Imaging of the Oesophagus A

3D imaging of the oesophagus helps the physician to correctly evaluate the localisation, as well as the distance, between the posterior part of the left atrium (A) and the anterior part of the oesophagus (B).

studies, the intervention would be affordable at net cost between €1,151 and €1,918, which is the approximate cost of the mapping system.26,42

Contact-force catheter inserted through the femoral artery to monitor contact (yellow circle) to avoid endothelial damage.

However, in the Near zerO fluoroscopic exPosure during catheter ablAtion of supRavenTricular arrhYthmias (NO-PARTY) multicentre randomised trial, Casella et al. found that a minimally fluoroscopic approach dramatically reduced the estimated risk of cancer incidence and mortality (96% reduction). They also found a reduction in estimated years of life lost and years of life affected, while retaining the safety and efficacy of procedures.26 Considering the impact of cancer on quality of life and the cost-effectiveness of this approach, as discussed in other

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Therefore, in our daily practice, the physicians performing electrophysiological procedures should first ensure that exposure is as low as reasonably achievable without affecting quality of care. The zero X-ray approach is considered a reliable and safe alternative to fluoroscopy for tachyarrhythmia ablation.43 This method may yield potential clinical benefits in terms of reduction of ionising radiation exposure, as well as safe technical advantages. The benefits include no exposure of patients and staff to radiation, more precise definition or localisation of the mechanism of the arrhythmia, spatial display of catheters and arrhythmia activation, shorter procedure times (particularly in patients with complex arrhythmias) and easier access to ablation for certain populations (i.e. pregnant women and those undergoing radiation therapy). The long-term safety benefits of not using fluoroscopy have been documented, and the reduction in the use of X-rays has been achieved without compromising the duration, effectiveness and safety of the procedure.12–14 A planned approach may be necessary to define the optimal learning curve.14 The

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Electrophysiology and Ablation current role and next direction of cardiac magnetic resonance (CMR) in personalising arrhythmia management may be an important future point.44 CMR can determine precise and reproducible assessment of scar and ‘border zone’ volumes, as well as predict the location of re-entrant circuits within the scar to guide ablation.44 Detailed tissue characterisation may create personalised computer models to predict a patient’s risk of arrhythmia. Computational modelling provides a framework for the integration of experimental and clinical findings, and has emerged as essential mechanistic research of arrhythmias.45 Therefore, fluoroscopy may be used only in cases for troubleshooting, including transseptal puncture (considering the several tools we previously described to minimise the use of X-rays), potential peripheral vascular disease, previous lead implantation and epicardial ablation (especially for anterior/posterior pericardial access and for a potential coronarography prior to epicardial ablation). We have reached a new era in minimising X-ray radiation exposure, with new ideas and novel technologies still to be developed in the future.46,47

Conclusion In ablation for arrhythmias, the zero X-ray approach is considered a feasible and safe alternative to fluoroscopy, which is only used in

10. 11.

12.

13.

US Food and Drug Administration. Initiative to reduce unnecessary radiation exposure from medical imaging. Washington, DC: FDA, 2010. http://www.fda.gov/RadiationEmittingProducts/RadiationSafety/RadiationDoseReduction/ ucm199994.htm (accessed 17 August 2020). Picano E, Vañó E, Rehani MM, et al. The appropriate and justified use of medical radiation in cardiovascular imaging: a position document of the ESC Associations of Cardiovascular Imaging, Percutaneous Cardiovascular Interventions and Electrophysiology. Eur Heart J 2014;35:665–72. https://doi. org/10.1093/eurheartj/eht394; PMID: 24401558. Latini G, Dipaola L, Mantovani A, et al. Reproductive effects of low-to-moderate medical radiation exposure. Curr Med Chem 2012;19:6171–7. https://doi.org/10.2174/092986712804485692; PMID: 23033948. Sarkozy A, De Potter T, Heidbuchel H, et al. Occupational radiation exposure in the electrophysiology laboratory with a focus on personnel with reproductive potential and during pregnancy: A European Heart Rhythm Association (EHRA) consensus document endorsed by the Heart Rhythm Society (HRS). Europace 2017;19:1909–22. https://doi.org/10.1093/ europace/eux252; PMID: 29126278. Chambers CE. Health risks of ionizing radiation: Dr Roentgen Today. Circulation 2017;136:2417–9. https://doi.org/10.1161/ CIRCULATIONAHA.117.031673; PMID: 29255122. Borghini A, Vecoli C, Mercuri A, et al. Low-dose exposure to ionizing radiation deregulates the brain-specific microRNA-134 in interventional cardiologists. Circulation 2017;136:2516–8. https://doi.org/10.1161/CIRCULATIONAHA.117.031251; PMID: 29038169. Roguin A. CardioPulse. Radiation in cardiology: can’t live without it!: using appropriate shielding, keeping a distance as safely as possible and reducing radiation time are essential principles for radiation reduction. Eur Heart J 2014;35:599–600. https://doi.org/10.1093/eurheartj/ehu025; PMID: 24609722. Ector J, Dragusin O, Adriaenssens B, et al. Obesity is a major determinant of radiation dose in patients undergoing pulmonary vein isolation for atrial fibrillation. J Am Coll Cardiol 2007;50:234–42. https://doi.org/10.1016/j.jacc.2007.03.040; PMID: 17631216. Orme NM, Rihal CS, Gulati R, et al. Occupational health hazards of working in the interventional laboratory: a multisite case control study of physicians and allied staff. J Am Coll Cardiol 2015;65:820–6. https://doi.org/10.1016/j. jacc.2014.11.056; PMID: 25720626. Pelz DM. Low back pain, lead aprons, and the angiographer. AJNR Am J Neuroradiol 2000;21:1364. PMID: 10954297. Ross AM, Segal J, Borenstein D, et al. Prevalence of spinal disc disease among interventional cardiologists. Am J Cardiol 1997;79:68–70. https://doi.org/10.1016/S0002-9149(96)006789; PMID: 9024739. Giaccardi M, Del Rosso A, Guarnaccia V, et al. Near-zero x-ray in arrhythmia ablation using a 3-dimensional electroanatomic mapping system: a multicenter experience. Heart Rhythm 2016;13:150–6. https://doi.org/10.1016/j.hrthm.2015.09.003; PMID: 26341606. Giaccardi M, Mascia G, Paoletti Perini A, et al. Long-term outcomes after “zero X-ray” arrhythmia ablation. J Interv Card

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14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

selected cases for troubleshooting. The non-fluoroscopic approach is a milestone for cancer prevention in ablation procedures. Awareness of radiation risk is a prerequisite to create a culture of respect for radiation hazard and a commitment to minimise exposure and to maximise protection.

Clinical Perspective • The zero X-ray approach is a reliable and safe alternative to fluoroscopy for tachyarrhythmia ablation. • The electrophysiologist should ensure that X-ray exposure is as low as reasonably achievable without sacrificing quality of care. • A zero X-ray ablation may yield not only potential clinical benefits in terms of reduction of ionising radiation exposure, but also technical safe advantages. • Fluoroscopy may be restricted to troubleshooting selected cases, since X-ray reductions are achieved without compromising the duration, effectiveness and safety of the procedure. • The non-fluoroscopic approach represents a milestone for cancer prevention in ablation procedures.

Electrophysiol 2019;54:43–8. https://doi.org/10.1007/s10840018-0390-7; PMID: 29948584. Santoro A, Di Clemente F, Baiocchi C, et al. From near-zero to zero fluoroscopy catheter ablation procedures. J Cardiovasc Electrophysiol 2019;30:2397–404. https://doi.org/10.1111/ jce.14121; PMID: 31424119. Pani A, Giuseppina B, Bonanno C, et al. Predictors of zero X-ray ablation for supraventricular tachycardias in a nationwide multicenter experience. Circ Arrhythm Electrophysiol 2018;11:e005592. https://doi.org/10.1161/CIRCEP.117.005592; PMID: 29874166. Haïssaguerre M, Jais P, Shah DC, et al. Spontaneous initiation of atrial fibrillation by ectopic beats originating in the pulmonary veins. N Engl J Med 1998;339:659–66. https://doi. org/10.1056/NEJM199809033391003; PMID: 9725923. Haïssaguerre M, Jaïs P, Shah DC, et al. Right and left atrial radiofrequency catheter therapy of paroxysmal atrial fibrillation. J Cardiovasc Electrophysiol 1996;7:1132–44. https://doi.org/10.1111/j.1540-8167.1996.tb00492.x; PMID: 8985802. Swartz JF, Pellersels G, Silvers J. A catheter-based curative approach to atrial fibrillation in humans. Circulation 1993;88(Suppl I):I-335. Gaita F, Riccardi R, Calò L, et al. Atrial mapping and radiofrequency catheter ablation in patients with idiopathic atrial fibrillation: electrophysiological findings and ablation results. Circulation 1998;97:2136–45. https://doi.org/10.1161/01. CIR.97.21.2136; PMID: 9626174. Ernst S, Schlüter M, Ouyang F, et al. Modification of the substrate for maintenance of idiopathic human atrial fibrillation: efficacy of radiofrequency ablation using nonfluoroscopic catheter guidance. Circulation 1999;100:2085–92. https://doi. org/10.1161/01.CIR.100.20.2085; PMID: 10562265. Pappone C, Oreto G, Lamberti F, et al. Catheter ablation of paroxysmal atrial fibrillation using a 3D mapping system. Circulation 1999;100:1203–8. https://doi.org/10.1161/01. CIR.100.11.1203; PMID: 10484541. Kugler JD, Danford DA, Houston KA, et al. Pediatric radiofrequency catheter ablation registry success, fluoroscopy time, and complication rate for supraventricular tachycardia: comparison of early and recent eras. J Cardiovasc Electrophysiol 2002;13:336–41. https://doi.org/10.1046/j.1540-8167. 2002.00336.x; PMID: 12033349. Drago F, Silvetti MS, Di Pino A, et al. Exclusion of fluoroscopy during ablation treatment of right accessory pathway in children. J Cardiovasc Electrophysiol 2002;13:778–82. https://doi. org/10.1046/j.1540-8167.2002.00778.x; PMID: 12212697. Sporton SC, Earley MJ, Nathan AW, et al. Electroanatomic versus fluoroscopic mapping for catheter ablation procedures: a prospective randomized study. J Cardiovasc Electrophysiol 2004;15:310–5. https://doi.org/10.1111/j.1540-8167.2004. 03356.x; PMID: 15030422. Hirshfeld JW Jr, Balter S, Brinker JA, et al. American College of Cardiology Foundation; American Heart Association/; HRS; SCAI; American College of Physicians Task Force on Clinical Competence and Training.ACCF/AHA/HRS/SCAI clinical competence statement on physician knowledge to optimize patient safety and image quality in fluoroscopically guided invasive cardiovascular procedures: a report of the American

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College of Cardiology Foundation/American Heart Association/ American College of Physicians Task Force on Clinical Competence and Training. Circulation 2005;111:511–32. https:// doi.org/10.1161/01.CIR.0000157946.29224.5D; PMID: 15687141. Casella M, Dello Russo A, Pelargonio G, et al. Near zerO fluoroscopic exPosure during catheter ablAtion of supRavenTricular arrhYthmias: the NO-PARTY multicentre randomized trial. Europace 2016;18:1565–72. https://doi. org/10.1093/europace/euv344; PMID: 26559916. Anselmino M, Sillano D, Casolati D, et al. A new electrophysiology era: zero fluoroscopy. J Cardiovasc Med (Hagerstown) 2013;14:221–7. https://doi.org/10.2459/ JCM.0b013e3283536555; PMID: 22526222. Raju H, Whitaker J, Taylor C, et al. Electroanatomic mapping and transoesophageal echocardiography for near zero fluoroscopy during complex left atrial ablation. Heart Lung Circ 2016;25:652–60. https://doi.org/10.1016/j.hlc.2016.01.018; PMID: 26979468. Bigelow AM, Smith G, Clark JM. Catheter ablation without fluoroscopy: current techniques and future direction. J Atr Fibrillation. 2014;6:1066. https://doi.org10.4022/jafib.1066; PMID 27957068. Ptaszek L, Moon B, Sacher F, et al. Novel automated point collection software facilitates rapid, high density electroanatomic mapping with multiple catheter types. J Cardiovasc Electrophysiol 2017;29:186–95. https://doi. org/10.1111/jce.13368; PMID: 29024200. Frontera A, Takigawa M, Martin R, et al. Electrogram signature of specific activation patterns: analysis of atrial tachycardias at high density endocardial mapping. Heart Rhythm 2018;15:28– 37. https://doi.org/10.1016/j.hrthm.2017.08.001; PMID: 28797676. Lackermair K, Kellner S, Kellnar A, et al. Initial single centre experience with the novel Rhythmia© high density mapping system in an all comer collective of 400 electrophysiological patients. Int J Cardiol 2018;272:168–74. https://doi. org/10.1016/j.ijcard.2018.07.141; PMID: 30126655. Giaccardi M, Mascia G, Paoletti Perini A, et al. Ablation of recurrent malignant idiopathic ventricular tachycardia: when proper diagnosis and success is a matter of contact. Clin Case Rep 2018;6:2193–7. https://doi.org/10.1002/ccr3.1777; PMID: 30455919. Hagen PT, Scholz DG, Edwards WD. Incidence and size of patent foramen ovale during the first 10 decades of life: an autopsy study of 965 normal hearts. Mayo Clin Proc 1984;59:17–20. https://doi.org/10.1016/S00256196(12)60336-X; PMID: 6694427. Fisher DC, Fisher EA, Budd JH, et al. The incidence of patent foramen ovale in 1,000 consecutive patients. A contrast transesophageal echocardiography study. Chest 1995;107:1504– 9. https://doi.org/10.1378/chest.107.6.1504; PMID: 7781337. Meissner I, Whisnant JP, Khandheria BK, et al. Prevalence of potential risk factors for stroke assessed by transesophageal echocardiography and carotid ultrasonography: the SPARC study. Stroke prevention: assessment of risk in a community. Mayo Clin Proc 1999;74:862–9. https://doi.org/10.4065/74.9.862; PMID: 10488786. Guarguagli S, Cazzoli I, Kempny A, et al. A new technique for zero fluoroscopy atrial fibrillation ablation without the use of

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Zero X-ray Ablation intracardiac echocardiography. JACC Clin Electrophysiol 2018;4:1647–8. https://doi.org/10.1016/j.jacep.2018.08.021; PMID: 30573134. 38. Shenasa M, Al-Ahmad A. Advances in Cardiac Mapping and Catheter Ablation: Part I, An Issue of Cardiac Electrophysiology Clinics, Volume 11-3. Philadelphia, PA: Elsevier, 2019. 39. Kapur S, Barbhaiya C, Deneke T, et al. Esophageal injury and atrioesophageal fistula caused by ablation for atrial fibrillation. Circulation 2017;136:1247–55. https://doi.org/10.1161/ CIRCULATIONAHA.117.025827; PMID: 28947480. 40. Susi F, Mascia G, Milli M, et al. Esophageal visualization changes atrial fibrillation ablation strategy: from encircling to segmental approach. J Interv Card Electrophysiol 2020. https:// doi.org/10.1007/s10840-020-00774-2; PMID: 32494895; epub ahead of press.

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41. Winkle RA, Mead RH, Engel G, et al. Physician-controlled costs: the choice of equipment used for atrial fibrillation ablation. J Interv Card Electrophysiol 2013;36:157–65. https://doi. org/10.1007/s10840-013-9782-x; PMID: 23483336. 42. Eichler HG, Kong SX, Gerth WC, et al. Use of cost-effectiveness analysis in health-care resource allocation decision-making: how are cost-effectiveness thresholds expected to emerge? Value Health 2004;7:518–28. https://doi.org/10.1111/ j.1524-4733.2004.75003.x; PMID: 15367247. 43. Canpolat U, Faggioni M, Della Rocca DG, et al. State of fluoroless procedures in cardiac electrophysiology practice. J Innov Card Rhythm Manag 2020;11:4018–29. https://doi. org/10.19102/icrm.2020.110305; PMID: 32368376. 44. Nelson T, Garg P, Clayton RH, et al. The role of cardiac MRI in the management of ventricular arrhythmias in ischaemic and

non-ischaemic dilated cardiomyopathy. Arrhythm Electrophysiol Rev 2019;8:191–201. https://doi.org/10.15420/aer.2019.5.1; PMID: 31463057. 45. Aronis KN, Ali RL, Liang JA, et al. Understanding AF mechanisms through computational modelling and simulations. Arrhythm Electrophysiol Rev 2019;8:210–9. https:// doi.org/10.15420/aer.2019.28.2; PMID: 31463059. 46. Romanov A, Dichterman E, Schwartz Y, et al. High-resolution, real-time, and nonfluoroscopic 3-dimensional cardiac imaging and catheter navigation in humans using a novel dielectricbased system. Heart Rhythm 2019;16:1883–9. https://doi. org/10.1016/j.hrthm.2019.06.020; PMID: 31255845. 47. Nicholls M. KODEX-EPD mapping for AF ablation. Eur Heart J 2019;40:3003–5. https://doi.org/10.1093/eurheartj/ehz647; PMID: 31541550.

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Electrophysiology and Ablation

Impact of Micro-, Mini- and Multi-Electrode Mapping on Ventricular Substrate Characterisation Benjamin Berte,1 Katja Zeppenfeld2 and Roderick Tung3 1. Heart Center, Luzerner Kantonsspital, Lucerne, Switzerland; 2. Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands; 3. Center for Arrhythmia Care, Pritzker School of Medicine University of Chicago Medicine, Chicago, IL, US

Abstract Accurate substrate characterisation may improve the evolving understanding and treatment of cardiac arrhythmias. During substrate-based ablation techniques, wide practice variations exist with mapping via dedicated multi-electrode catheter or conventional ablation catheters. Recently, newer ablation catheter technology with embedded mapping electrodes have been introduced. This article focuses on the general misconceptions of voltage mapping and more specific differences in unipolar and bipolar signal morphology, field of view, signal-to-noise ratio, mapping capabilities (density and resolution), catheter-specific voltage thresholds and impact of micro-, mini- and multi-electrodes for substrate mapping. Efficiency and cost-effectiveness of different catheter types are discussed. Increasing sampling density with smaller electrodes allows for higher resolution with a greater likelihood to record near-field electrical information. These advances may help to further improve our mechanistic understanding of the correlation between substrate and ventricular tachycardia, as well as macro-reentry arrhythmia in humans.

Keywords Substrate mapping, electrode design, cardiac arrhythmias, re-entrant tachycardia, ventricular substrate characterisation, ventricular tachycardia Disclosure: BB has received travel grants, research grants and speaker fees from Biosense Webster, Boston Scientific and Abbott. KZ has received research grants from Biosense Webster. RT has received consulting, travel grants and speaker fees from Abbott. Received: 27 May 2020 Accepted: 23 August 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):128–35. DOI: https://doi.org/10.15420/aer.2020.24 Correspondence: Benjamin Berte, Heart Center, Lucerne Cantonal Hospital, Spitalstrasse, 6000 Lucerne 16, Switzerland. E: Benjamin.Berte@luks.ch Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Accurate substrate characterisation is important for depicting scarrelated re-entrant tachycardia to optimise ablation targets and strategies. The underlying substrate can be analysed using electrogram (EGM) characteristics, such as low voltage, local abnormal voltage activity (LAVA), evoked potentials or late potentials, conduction analysis in sinus rhythm or differential pacing, or using imaging modalities, such as delayed enhancement MRI (delayed enhancement) CT, PET, histology or a combination of these techniques.2–11 The aim of high-resolution mapping is to obtain histological-level information of the extent and location of abnormal substrate across the myocardial wall to guide and expedite targeted ablation.

Voltage Mapping: Unipolar, Bipolar or Omnipolar Mapping? Unipolar Recording A dipole field coming towards the electrode creates a positive deflection, and a wavefront going away from the electrode creates a negative deflection. Although unipolar recordings are the purest direct recordings used to derive bipolar recordings, they are less often used due to their large field of view with less sensitivity for near-field, low-amplitude electrogram components, which also makes them more prone to low frequency artefacts. The duration of the unipolar deflection and amplitude are proportional to the electrode size.

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Access at: www.AERjournal.com

Bipolar Recording Bipolar recordings are merely the subtraction of two unipolar recordings. Smaller electrodes average over less space, creating a higher BV (or delta) and shorter duration due to a higher slope (dv/dt), because the dipole field falls off quickly. At normal conduction velocities, the wavefront dipole dimension (+ to –) is around 1–3 mm. This leads to a necessary correlation between adequate electrode size and interelectrode distance. The main advantage of bipolar recordings is far-field rejection, which is further improved with the use of smaller, flatter electrodes with smaller interelectrode distance.12 As a result, higher frequency components are created and visualised, which has become synonymous with near-field recordings. The main disadvantage of bipolar mapping is its wavefront dependency due to the orientation of the relative positioning of the two unipoles to derive the electrogram.13 High-density multi-electrode grid catheters (e.g. HD-32 Grid) allow for simultaneous recordings in multiple orthogonal directions around a small region of tissue, with the ability to select the largest BV. This is possible with equidistant electrode configurations on the HD Grid catheter, which may allow for selection of the bipole pair that aligns most closely to the direction of the activation wavefront.14,15

Omnipolar Technology Due to these findings, new ways to evaluate centrifugal or centripetal activation are suggested, such as omnipolar technology (OT),

Impact of Electrode Design on Substrate Mapping independent of the orientation of the wavefront. OT employs multiple electrodes and mathematical models of wave propagation to determine the direction of a traveling wave along the myocardial plane by interrogating its electric field. OT can survey all possible bipolar electrode orientations and can obtain electrode orientation– independent electrograms along the maximal bipolar direction.16

Figure 1: Impact of Orientation, Size and Spacing on Bipolar Voltage Mapping Bipole orientation PentaRay

Orion

HD Grid

Misconceptions and Difficulties of Substrate Mapping Using Bipolar Voltage Mapping Several factors influence low BV mapping, such as tissue factors (e.g. healthy or fibrotic tissue and epicardial or myocardial fat), the influence of conduction velocity, fibre orientation and curvature, catheter–tissue relationship (angle of incidence, contact force, orientation in relation to wavefront propagation and tissue oedema), different filter settings and catheter characteristics (Figure 1).12 This review focuses on the impact of catheter characteristics, which include electrode size, shape and interelectrode spacing, and electrochemical factors, such as fractal surfacing, coating and welling.

Bipolar spacing

Electrode size

LAVA?

Catheter Types and Configurations Substrate mapping can be performed using conventional ablation catheters with a large tip, or using dedicated linear, basket, multi-spline or grid catheters. Recently, novel ablation catheters have been developed with mini- or micro-electrodes embedded in the distal tip electrode. Catheter and electrode design will influence:

LAVA

• the amplitude and duration of the local EGM, and therefore, the spatial and temporal resolution of the catheter used; • the field of view; • the signal-to-noise ratio; • the catheter-specific voltage values; • the affinity to detect conduction channels and LAVA; and • mapping density, and therefore, the efficiency of the catheter used.

Impact of Catheter Characteristics Electrode Size and Catheter Orientation Smaller electrodes typically result in sharper (high frequency) and shorter EGM duration. The amplitude of a bipolar electrogram depends on the electrode size, the angle of incidence between the catheter and tissue, and the orientation of the bipole relative to the wavefront propagation. Standard 3.5-mm ablation catheters with larger tip electrodes and wide bipolar spacing can appear more similar to unipolar recordings, depending on the angle of incidence and the distance from the ring electrode to the tissue (Figure 1). The design of most multi-electrode catheters with small electrodes allows for a stable bipolar electrode position parallel to the tissue, thereby reducing the influence of the angle of incidence. Ablation catheters with incorporated micro-electrodes have features of both (Table 1).12 Bipolar voltage (BV) recorded with micro-electrodes are three times larger than BV recorded with conventional electrodes at the same site,17 but similar mean BVs were recorded using OctaRay versus PentaRay.17,18 Computing models and animal data suggest possible limited resolution differences <1 mm of electrode sizes for all catheter types.18,19

Interelectrode Distance Increased interelectrode distance results in a larger BV amplitude and a loss of spatial resolution to detect LAVA.12,20,21 Both far-field and nearfield BVs increase with increased spacing, although near-field increases may be less proportional. The near-field to far-field ratio increases due to predominant far-field rejection with closer spacing. Therefore,

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Catheter orientation

Several factors influence low bipolar voltage mapping. Left to right and top to bottom: Bipolar orientation: looking across versus along the PentaRay catheter (Biosense Webster) splines can hide or make appear local abnormal ventricular activity (LAVA) signals. With different spline orientation, a bipole only 2 mm away from each other has significant impact in bipolar voltage, as seen in this example of the Orion catheter (Boston Scientific). Changing the orientation across the HD Grid catheter (Abbott) splines from NorthEast (NE) to SouthEast (SE) had a dramatic impact on the electrogram, revealing a large sharp nearfield (NF) LAVA with NE bipole orientation that was missed completely in the SE direction. Bipolar spacing: larger spacing with the LiveWire catheter (Abbott) detects larger bipolar signals with loss of spatial resolution. Electrode size: due to its smaller electrode size of 1 mm, PentaRay is more sensitive than Navistar (4 mm electrode size) for NF LAVA if 3D tags <3 mm distance are compared to each other. Catheter orientation: ablation catheters mimic unipolar recordings with a large floating ring electrode away from the tissue, and multi-electrode catheters create real bipolar recording due to parallel orientation of similarly sized small electrodes. Micro-embedded ablation catheters have features of both.

smaller spacing, ideally 1–2 mm, results in more optimal resolution. Only very small electrode sizes can be used in tight spacing (<1 mm) to overcome auto-cancellation within a bipole (Table 1).

Bipole Orientation Multi-electrode catheters are highly dependent on the direction of the propagating wavefront relative to the orientation of the bipole pair (Figure 2).12 Depending on the spline orientation or different conduction (sinus rhythm or pacing manoeuvres), different BVs (variation around 30%) are measured, and a significant percentage of around 30% of LAVA are recorded or masked.7,21–23 These variations are most often present in the scar border zone (mixed scar tissue) and with orthogonal bipole activation. This limitation may theoretically be overcome using omnipole mapping or maximal bipolar amplitude mapping (HD wave)

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Electrophysiology and Ablation Table 1: Different Catheter Characteristics of the Most Used Catheters Model

Manufacturer

Electrodes

Tip Electrode Size (mm)

Ring Electrode Size (mm)

Micro- or Minielectrode Area (mm2)

Spacing (Edge to Edge)

Spacing Recorded (Centre to Centre)

QDOT Micro, CF

Biosense Webster

4+ 3ME

3.5

0.086

252

4.25

Intella MiFi

Boston Scientific

4+ 3ME

0.5

2.5 2.5 2.5

4.5

Thermocool ST, CF

Biosense Webster

3.5

162

3.25

Thermocool STSF, CF

Biosense Webster

3.5

252

4.25

Navistar

Biosense Webster

4 or 8

174

3.5

CoolFlex

Abbott

0.5 5 2

2.75

Safire

Abbott

252

FlexAbility

Abbott

141

3.5

Tacticath, CF

Abbott

3.5

252

4.25

Blazer II/OI

Boston Scientific

2.5 2.5 2.5

4.5

MiFi

Boston Scientific

1.5

2.5

Ablation catheters

Multi-electrode mapping OctaRay

Biosense Webster

0.5

1.5

PentaRay

Biosense Webster

2 6 2 or 4 4 4

Decapolar

Biosense Webster

282

Lasso

Biosense Webster

262

HD Grid

Abbott

16 or 32

LiveWire

Abbott

222

IntellaMap Orion

Boston Scientific

0.9 × 0.45

1.6

2.5

Constellation (60 mm)

Boston Scientific

1.5

6.5

Inquiry Optima

Abbott

1 4.5 1

Inquiry AFocus II

Abbott

2.4

CF = contact force; II = closed irrigation; OI = open irrigation; ME = mini- or micro-electrodes. Source: Tung et al. 2016.41 Adapted with permission from Wolters Kluwer Health.

with the HD Grid catheter, or by concomitant use of imaging-derived substrate information.14,24 In theory, an incident wavefront that is exactly 90° to both bipoles would result in cancellation. However, in vivo, activation occurs in 3D, and it is unlikely that this scenario is relevant in clinical cases (isoelectric EGM without an intrinsic amplitude).25 Additionally, repeated sampling in a region of interest also overcomes this limitation, as the catheter orientation varies with each manipulation, increasing the probability of detecting a larger local EGM.

Customising Voltage Mapping Values Relative to the Recording Catheter Conventional scar and low BV thresholds (0.5–1.5 mV) were defined by Marschlinski et al., based on mapping with a conventional large-tip electrode.1 The 1.5 mV threshold has been validated in animal models of transmural myocardial infarcts, but the dense scar level of 0.5 mV has been arbitrarily defined.26 Based on the prior findings and comparison with MRI-derived substrate, several authors have suggested specific BV thresholds for each dedicated mapping catheter: • • • •

PentaRay: 0.2–1 mV or 1.5 mV; Orion: 0.1–1 mV LiveWire: 0.5–1.5 mV; and ablation catheter: 0.5–1.5 mV.20,27,28

As voltage thresholds have only been validated for post-infarct scars, the use of one single threshold is oversimplified. Due to the

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explanations above, it is likely that, for catheters with smaller electrode sizes and spacings, higher voltage thresholds to identify normal myocardium should be applied. For QDOT MICRO, scar thresholds of unipolar <5.44 mV, bipolar <1.27 mV and mini- or micro-electrodes (MEs) <2.84 mV have been suggested validated by histology in an animal infarct model.29 Whole-heart histology in non-ischaemic cardiomyopathy has highlighted that no specific cutoffs can be found, as fibrosis patterns and architecture are different compared with ischaemic cardiomyopathy, and wall thinning is often absent.30

Catheter Design and Configurations Multi-electrode Catheters Different models of dedicated multi-electrode mapping catheters are used: linear versus multi-spline versus grid versus basket catheters with around 0.5–1 mm3 electrode sizes and 2–3 mm interelectrode distances. With all currently available multi-electrode catheters, there is lack of contact force measurement, and the direction of the wavefront influences both electrogram amplitude and duration. Due to their location on the catheter tip (angle between the three bipoles is 60°), ME may at least partly compensate for wavefront influence, as the highest BV is recorded. In recent animal work, the highest recorded ME BV was was able to more adequately detect viable myocardium throughout the ventricular wall in an animal model of reperfused MI, validated by histology, compared to both conventional QDOT MICRO ablation electrodes and PentaRay.31

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Impact of Electrode Design on Substrate Mapping Figure 2: Examples of Micro- and Multi-electrode Catheters Decay S1

Decay S2

QDOT catheter ME c-t-c distance 1.5 mm

Intella MIFI Far field arsing from surviving epicardial layer

Independent signal connector –1 mm diameter Distance from the tip –2 mm

BV QDOT

ME surface area 0.086 mm2

Equally spaced mini-electrodes (2.5 mm centre to centre)

BV Endocardial activation with slight delay

Electrical insulation ME surface area 0.5 mm2

2.0

LiveWire

2.0

64 low-noise electrodes (2.5 mm centre to centre)

2.0 2.0

6.0

2.0 2.0

2.0

PentaRay Paddle design compose of 4 splines (2.5F)

Orion

OctaRay 3-3-3 ring spacing

Irrigation ports 8F shaf

16 electrodes on paddle • 4×4 grid • 1 mm electrode length

HD Grid

2 electrodes Magnetic sensors on distal shaft

Different catheter types and designs. Left to right and top to bottom: QDOT micro has smaller mini-electrodes (called micro-electrodes) more distal on the tip electrode than Intella MiFi. Bipolar signals recorded with micro-electrodes (BVμ) are larger and sharper and have less decay, facilitating near field local abnormal ventricular activity (LAVA) recognition, compared to conventional recording (BVc). It is unknown if there is a large difference in EGM morphology between both, as a direct comparison is missing. LiveWire (Abbott), Orion (Boston Scientific), PentaRay (Biosense Webster), OctaRay (Biosense Webster) and HD Grid (Abbott) are the most commonly used multi-electrode catheters. c-t-c = centre-to-centre; ME = mini- or micro-electrode. Middle upper panel source: Glashan et al. 2020.31 Adapted with permission from Elsevier.

A custom-made 112-electrode (2 mm size, 1 mm spacing) endocardial balloon was used by another group to analyse extremely low amplitude potentials in the range of 50–100 μV. They found that decremental evoked potentials (using extra-stimulus testing) were more specific than LAVA potentials to identify the diastolic isthmus during ventricular tachycardia.32 Multi-spline variants of multi-electrode catheters are often arrhythmogenic during endocardial mapping, especially in small and healthy ventricles, and cannot correct for wavefront dependency of voltage, which can be achieved with a grid design. In theory, more accurate entrainment mapping can be performed using multi-electrode catheters due to less output required to capture from small electrodes and sharper EGM recording allowing for more precise measurements of local activation times. The ideal number, spacing and size of the electrodes of such catheters is still under investigation; for example, OctaRay mapping is faster and denser compared to PentaRay mapping, but has similar substrate resolution in a ventricular mapping study (Figure 2). In the present study we hypothesised a ‘mapping plateau’ with electrode sizes <1 mm, which has been supported by a computational study comparing electrode sizes.18,19 More electrodes can increase mapping speed and density, and smaller sizes and spacing increase spatial resolution and potentially reduce RF time, but their additional impact on ventricular tachycardia non-inducibility or effectiveness is not known.33,34

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Their (cost-)efficiency is questionable; although substrate maps can be acquired faster with higher density and better mapping resolution, a separate ablation catheter is still needed (Table 2).35

Mini- and Micro-electrode Catheters There are currently two ablation catheters with smaller embedded electrodes: IntellaNav MIFI (without contact force, Boston Scientific) and QDOT MICRO (with contact force, Biosense Webster). The three micro-electrodes of the QDOT MICRO are smaller, more distally on the distal electrode located at a 60° angle compared to the three minielectrodes of the IntellaNav MIFI that are slightly larger, and more proximally located on the electrode at a 90° angle (Table 1 and Figure 2). It is not known if the differences between both have a significant clinical impact. The highest ME BV is depicted to compensate, at least in part, for wavefront influence. Due to their design, they record sharper highfrequency EGMs and higher BVs (Figure 2). Therefore, different voltage thresholds for ME voltage maps are needed. These catheters may be more cost-efficient, as the mapping and ablation features are integrated, but mapping time is likely to be longer. These micro-electrodeembedded catheters could be used to directly check LAVA elimination, without the need for remapping with a multi-electrode mapping catheter, saving time and/or the need for an additional catheter. The catheters can be used as standalone, but can also be combined with multi-electrode catheters or imaging-derived scar information (Table 2).36

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Electrophysiology and Ablation Table 2: Pros and Cons of Mini- or Micro-electrode and Multi-electrode Catheters Mini- and Micro-electrodes

Multi-electrodes

Pros

Cons

Pros

Cons

Near field Field of view

‘Real’ near field Small field of view

Noise and artefacts Initial oedema during radiofrequency

Near field Larger field of view

Far field lava mapped?

LAVA endpoint

More sensitive new LAVA endpoint

Confirmation tool needed?

More LAVA, more channels

Mapping resolution

Improved temporal and spatial resolution

Low mapping density: only in area of interest

High-density mapping

Arrhythmogenicity

Contact

Local impedance/contact information

Catheter orientation dependent

Tissue proximity index*

Wavefront dependent No contact info

Other

Lesion formation evaluation Lower pacing threshold

Cost-efficiency

Embedded in ablation catheter

Better entrainment Lower pacing threshold VT activation mapping Extra catheter needed

*Available on CARTO (Biosense Webster). LAVA = local abnormal voltage activity; VT = ventricular tachycardia.

Figure 3: Combined Fields of View from Mini- or Micro-electrode-embedded Catheters

Sharp ABL EGM Sharp ME EGM

Sharb ABL EGM No or blunt ME EGM

No or blunt ABL EGM Sharp ME EGM

ABL dist

ABL d

Micro 1–2

MiFi 1–2

Micro 2–3

Micro 3–1

ABL prox

II aVL v1

MiFi 2–3 MiFi 3–4 ABL p

There are four possibilities of combined field of view with ME-embedded catheters. No signal on both, a sharp signal on both, a sharp signal on Abl but not ME and a sharp signal on ME but not ABL. First EGM shows nice fragmented bridging of the remaining gap on the pulmonary vein isolation circle. The second EGM is a far-field fragmented signal. The last EGM demonstrates an ideal fragmented NF LAVA signal. Abl d= distal ablation electrode; ABL dist= distal ablation electrode; ABL p = proximal ablation electrode; ABL prox = proximal ablation electrode; EGM = electrogram; LAVA = local abnormal voltage activity; ME = mini- or micro-electrode.

Using only ME with a smaller field of view may also present disadvantages with regard to the durability of ablation lesions. In a recent study, radiofrequency applications were immediately terminated just after the rapid (4 seconds) loss of pulmonary vein signals on ME during pulmonary vein isolation. Of importance, reappearance of these micro-EGM signals was observed after 45 minutes’ waiting time, due to reversible oedema. Therefore, microEGM can be used to improve the ablation location accuracy, but should not be used to guide ablation duration.

view (Figure 3). This could lead to more detailed analysis of the subendocardially located tissue in contact using ME combined with a deeper analysis within the myocardial wall using conventional electrodes. In a recently published animal study, the accuracy in correctly identifying the histological substrate increased to 93% using ME in combination with conventional unipolar voltage mapping when using the QDOT MICRO catheter.17

Differences in Fields of View

• The detection of intramural scar covered by layers of viable myocardium may be detected by pacing manoeuvres measuring transseptal conduction time >40 ms and EGM duration >95 ms.37 • Epicardial fat mimicking scar due to attenuation of voltage, but with often shorter EGM duration and less deflections compared to scar.38 • Loss of micro-EGM on ME due to oedema can be interpreted in the same way.

In a computational model, approximately 90% of the BV amplitude reflects the activation of the closest 1-mm myocardium. Accordingly, voltage mapping data for transmural tissue information need to be interpreted with caution.18 Successful ablation and termination of ventricular tachycardia is sometimes performed in locations without any signal on the distal bipolar EGM of the ablation electrode. The new ablation catheters mentioned above combine two different fields of

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Specific problems concerning the field of view include:

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Impact of Electrode Design on Substrate Mapping Figure 4: Problems with Field of View

Epicardial fat

Intramural scar EGM duration (ms)

Estimated Transmural Activation Time (ms)

TS conduction >40 ms Paced EGM >95 ms

140

p<0.0001

120

14 12

10 60

8 6

0 Control

Fat

Septal Scar

ENDO 8.3 mV UV

EPI 1.8 mV BV

Fat

Scar

Normal 3–4 mm rim of endocardium

Thin-layered epicardial scar

Marchlinksi et al. Marchlinkski et al. Zeppenfeld et al.

Scar

EGM characteristics and imaging can define dat Imagine can define fat thickness in mm (efficacy of ablation)

Imaging, TS conduction and LAVA can visualise these scars

ENDO 1.5 mV BV

p<0.0001

18 16

100

EGM deflection 20

EPI 1 mV BV

EPI 7.95 mV UV

EPI 1.5 mV BV

EPI 7.95 mV UNIP

Cano et al.

Zeppenfeld et al.

Manual

Can mimic normal BV

Subendocardial tissue oedema during RF Can mimic low BV on ME

Only imaging and LAVA can visualise these scars Top to bottom, left to right: intramural scar can be missed by voltage mapping. Pacing techniques can help to detect such scars. Epicardial fat can mimic low BV, but has less duration and deflections than fibrotic scar. Subepicardial scar from myocarditis can be missed by conventional UV and BV mapping. Manual reannotation can help to demask these thin layers. Small rims of normal endocardial voltage above the scar can hide the substrate. Tissue oedema during RF can make ME EGM disappear due to their limited field of view. BV = bipolar voltage; EGM = electrogram; LAVA = local abnormal voltage activity; ME = mini- or micro-electrodes; RF = radiofrequency; TS = transseptal; UV = unipolar voltage.

Figure 5: Example of Difference in Field of View

RF distal

RF prox

Uni

ME 1–2 ME 2–3 ME 3–1

ME 1–2 ME 2–3 ME 3–1 Patient with ischaemic cardiomyopathy and ongoing stable ventricular tachycardia (VT). Mapping with Intella MiFi catheter shows sharp, large, fragmented mid-diastolic signal, suggesting a VT isthmus. This signal that was clear on radiofrequency distal was not observed on the mini-electrodes (ME), which are embedded in the tip electrode. Movement of few millimetres to improve contact suddenly showed the same local electrogram on the ME, where VT is terminated successfully. This states the difference in field of view of conventional ablation electrodes and the importance of contact force. Source: P Maury. Reproduced with permission from P Maury.

• Thin-layered epicardial scar obscured by the underlying viable myocardium.39 Contrast-enhanced cardiovascular magnetic resonance can be helpful to identify intramural scars, and multidetector CT can provide detailed information on epicardial fat thickness allowing for better interpretation of the local EGM amplitude (Figure 4).40

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Difference in Signal-to-noise Ratio Flat electrodes are less influenced by far field than cylindric or thicker electrodes, as they collect information further away from the tissue in contact. Fractal surface modification of the electrodes is sometimes used to obtain a small geometric footprint to minimise artefact interaction with multiple wavefronts. However, these fractals have

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Electrophysiology and Ablation high-electrode-tissue impedance, which increases the coupling of electromagnetic noise sources. Therefore, surface enhancements (e.g. Orion catheter with iridium oxide coating) can be used to decrease electrode-tissue impedance by dramatically increasing the active micro-surface area. By design, micro-electrodes have an excellent signal-to-noise ratio, if lab conditions are optimal. Even with these enhancements, inherent noise and artefacts may be seen using micro- and mini-electrode mapping. Operator experience is required to recognise the spectrum of artefacts (artefacts from valves, papillary muscles, catheter movement or poor contact), filter setting dependency, irrigation before and during ablation and electrochemical dirt on the electrodes, and potential solutions to improve signal quality (e.g. high-output pacing through the recording electrodes). Improved tissue contact increases the impedance and improves the signal quality.

Distinguishing Near Field from Far Field While it is important to distinguish near field from far field, a clear uniform definition is not available. In case of poorly coupled electrograms, the two or more components may all arise from nearfield activation (double near field). With higher mapping resolution and limited field of view, greater detection and recording of nearfield activity results. ME often generate sharper, larger signals with both higher spatial and temporal resolution compared with conventional electrodes. This can help to detect thin layers of viable myocardium.7 Examples of differences in field of view are given in Figure 5.

Comparing Catheters Due to all of the abovementioned factors, it is important to understand the influence of the catheter design and the catheter–tissue interaction, and not only focus on single aspects, such as electrode size or interelectrode spacing. Bipole and catheter orientation, different filter

Marchlinski FE, Callans DJ, Gottlieb CD, et al. Linear ablation lesions for control of unmappable ventricular tachycardia in patients with ischemic and nonischemic cardiomyopathy. Circulation 2000;101:1288–96. https://doi.org/10.1161/01. cir.101.11.1288; PMID: 10725289. Jais P, Maury P, Khairy P, et al. Elimination of local abnormal ventricular activities: a new end point for substrate modification in patients with scar-related ventricular tachycardia. Circulation 2012;125:2184–96. https://doi. org/10.1161/CIRCULATIONAHA.111.043216; PMID: 22492578. de Riva M, Naruse Y, Ebert M, et al. Targeting the hidden substrate unmasked by right ventricular extrastimulation improves ventricular tachycardia ablation outcome after myocardial infarction. JACC Clin Electrophysiol 2018;4:316–27. https://doi.org/10.1016/j.jacep.2018.01.013; PMID: 30089556. Porta-Sanchez A, Jackson N, Lukac P, et al. Multicenter study of ischemic ventricular tachycardia ablation with decrementevoked potential (DEEP) mapping with extra stimulus. JACC Clin Electrophysiol 2018;4:307–15. https://doi.org/10.1016/j. jacep.2017.12.005; PMID: 30089555. Vergara P, Trevisi N, Ricco A, et al. Late potentials abolition as an additional technique for reduction of arrhythmia recurrence in scar related ventricular tachycardia ablation. J Cardiovasc Electrophysiol 2012;23:621–7. https://doi. org/10.1111/j.1540-8167.2011.02246.x; PMID: 22486970. Anter E, Kleber AG, Rottmann M, et al. Infarct-related ventricular tachycardia: redefining the electrophysiological substrate of the isthmus during sinus rhythm. JACC Clin Electrophysiol 2018;4:1033–48. https://doi.org/10.1016/j. jacep.2018.04.007; PMID: 30139485. Tung R, Josephson ME, Bradfield JS, et al. Directional Influences of ventricular activation on myocardial scar characterization: voltage mapping with multiple wavefronts during ventricular tachycardia ablation. Circ Arrhythm Electrophysiol 2016;9:e004155. https://doi.org/10.1161/ CIRCEP.116.004155; PMID: 27516464. Jauregui B, Soto-Iglesias D, Penela D, et al. Follow-up after myocardial infarction to explore the stability of

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10.

11.

12.

13.

14.

15.

16.

settings, catheter noise, contact and contact force feedback contribute to EGM recordings. Therefore, operators should be familiar with the specific details of the catheter in use, including number of electrodes, electrode sizes, spacings and noise levels to understand the catheterspecific pitfalls. Table 1 summarises the important variations across diagnostic and ablation catheter configurations that influence the determination of voltage thresholds and the ability to detect near-field electrical recordings.

Conclusion To understand substrate characterisation using specific catheters, knowledge of the impact of catheter design, bipole configurations and recording methods is critical. All electrograms recorded within a given substrate are subject to the size, spacing and orientation of recording electrodes relative to the wavefront. However, a gold standard does not currently exist. Increasing sampling density with smaller electrodes allows for higher resolution with a greater likelihood to record near-field electrical information, which has been demonstrated to be useful during sinus rhythm and ventricular tachycardia. These advances may help to further improve our mechanistic understanding of the correlation between substrate and ventricular tachycardia, as well as the characteristics of human re-entry.

Clinical Perspective • Physicians should be aware of fundamental misconceptions about voltage mapping and the impact of various electrode sizes and configurations on electro-anatomical mapping. • Catheter-specific voltage values should be used for accurate substrate detection and depiction. • The use of conventional ablation catheters without additional imaging techniques or mapping electrode information is often insufficient for substrate recognition.

arrhythmogenic substrate: the Footprint study. JACC Clin Electrophysiol 2020;6:207–18. https://doi.org/10.1016/j. jacep.2019.10.002; PMID: 32081225. Takigawa M, Duchateau J, Sacher F, et al. Are wall thickness channels defined by computed tomography predictive of isthmuses of postinfarction ventricular tachycardia? Heart Rhythm 2019;16:1661–8. https://doi.org/10.1016/j. hrthm.2019.06.012; PMID: 31207315. Esposito A, Palmisano A, Antunes S, et al. Cardiac CT With delayed enhancement in the characterization of ventricular tachycardia structural substrate: relationship between CT-segmented scar and electro-anatomic mapping. JACC Cardiovasc Imaging 2016;9:822–32. https://doi.org/10.1016/j. jcmg.2015.10.024; PMID: 26897692. Duell J, Dilsizian V, Smith M, et al. Nuclear imaging guidance for ablation of ventricular arrhythmias. Curr Cardiol Rep 2016;18:19. https://doi.org/10.1007/s11886-015-0697-2; PMID: 26783000. Josephson ME, Anter E. Substrate mapping for ventricular tachycardia: assumptions and misconceptions. JACC Clin Electrophysiol 2015;1:341–52. https://doi.org/10.1016/j. jacep.2015.09.001; PMID: 29759461. Anter E, Josephson ME. Bipolar voltage amplitude: what does it really mean? Heart Rhythm 2016;13:326–7. https://doi. org/10.1016/j.hrthm.2015.09.033; PMID: 26432582. Jiang R, Beaser AD, Aziz Z, et al. High-density grid catheter for detailed mapping of sinus rhythm and scar-related ventricular tachycardia: comparison with a linear duodecapolar catheter. JACC Clin Electrophysiol 2020;6(3):311– 23. https://doi.org/10.1016/j.jacep.2019.11.007; PMID: 32192682. Takigawa M, Relan J, Martin R, et al. Effect of bipolar electrode orientation on local electrogram properties. Heart Rhythm 2018;15:1853–61. https://doi.org/10.1016/j.hrthm.2018.07.020; PMID: 30026016. Magtibay K, Masse S, Asta J, et al. Physiological assessment of ventricular myocardial voltage using omnipolar electrograms. J Am Heart Assoc 2017;6:e006447. https://doi.org/10.1161/

JAHA.117.006447; PMID: 28862942. 17. Glashan CA, Tofig BJ, Tao Q, et al. Multisize electrodes for substrate identification in ischemic cardiomyopathy: validation by integration of whole heart histology. JACC Clin Electrophysiol 2019;5:1130–40. https://doi.org/10.1016/j.jacep.2019.06.004; PMID: 31648737. 18. Barkagan M, Sroubek J, Shapira-Daniels A, et al. A novel multielectrode catheter for high-density ventricular mapping: electrogram characterization and utility for scar mapping. Europace 2020;22:440–9. https://doi.org/10.1093/europace/ euz364; PMID: 31985784. 19. Stinnett-Donnelly JM, Thompson N, Habel N, et al. Effects of electrode size and spacing on the resolution of intracardiac electrograms. Coron Artery Dis 2012;23:126–32. https://doi.org/10.1097/MCA.0b013e3283507a9b; PMID: 22258280. 20. Tung R, Kim S, Yagishita D, et al. Scar voltage threshold determination using ex vivo magnetic resonance imaging integration in a porcine infarct model: influence of interelectrode distances and three-dimensional spatial effects of scar. Heart Rhythm 2016;13:1993–2002. https://doi. org/10.1016/j.hrthm.2016.07.003; PMID: 27392944. 21. Takigawa M, Relan J, Kitamura T, et al. Impact of Spacing and orientation on the scar threshold with a high-density grid catheter. Circ Arrhythm Electrophysiol 2019;12:e007158. https:// doi.org/10.1161/CIRCEP.119.007158; PMID: 31446771. 22. Berte B, Relan J, Sacher F, et al. Impact of electrode type on mapping of scar-related VT. J Cardiovasc Electrophysiol 2015;26:1213–23. https://doi.org/10.1111/jce.12761; PMID: 26198475. 23. Tschabrunn CM, Roujol S, Dorman NC, et al. High-resolution mapping of ventricular scar: comparison between single and multielectrode catheters. Circ Arrhythm Electrophysiol 2016;9:e003841. https://doi.org/10.1161/CIRCEP.115.003841; PMID: 27307518. 24. Proietti R, Adlan AM, Dowd R, et al. Enhanced ventricular tachycardia substrate resolution with a novel omnipolar highdensity mapping catheter: the omnimapping study. J Interv Card

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36. Soto-Iglesias D, Penela D, Jauregui B, et al. Cardiac magnetic resonance-guided ventricular tachycardia substrate ablation. JACC Clin Electrophysiol 2020;6:436–47. https://doi. org/10.1016/j.jacep.2019.11.004; PMID: 32327078. 37. Betensky BP, Kapa S, Desjardins B, et al. Characterization of trans-septal activation during septal pacing: criteria for identification of intramural ventricular tachycardia substrate in nonischemic cardiomyopathy. Circ Arrhythm Electrophysiol 2013;6:1123–30. https://doi.org/10.1161/CIRCEP.113.000682; PMID: 24106241. 38. Tung R, Nakahara S, Ramirez R, et al. Distinguishing epicardial fat from scar: analysis of electrograms using high-density electroanatomic mapping in a novel porcine infarct model. Heart Rhythm 2010;7:389–95. https://doi.org/10.1016/j. hrthm.2009.11.023; PMID: 20185114. 39. Berte B, Sacher F, Cochet H, et al. Postmyocarditis ventricular tachycardia in patients with epicardial-only scar: a specific entity requiring a specific approach. J Cardiovasc Electrophysiol 2015;26:42–50. https://doi.org/10.1111/jce.12555; PMID: 25257774. 40. Piers SR, van Huls van Taxis CFB, Tao Q, et al. Epicardial substrate mapping for ventricular tachycardia ablation in patients with non-ischaemic cardiomyopathy: a new algorithm to differentiate between scar and viable myocardium developed by simultaneous integration of computed tomography and contrast-enhanced magnetic resonance imaging. Eur Heart J 2013;34:586–96. https://doi.org/10.1093/ eurheartj/ehs382; PMID: 23161702.

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Cardiac Pacing

His–Purkinje Conduction System Pacing: State of the Art in 2020 Ahran D Arnold,1 Zachary I Whinnett1 and Pugazhendhi Vijayaraman2 1. National Heart and Lung Institute, Imperial College London, London, UK; 2. Geisinger Heart Institute, Geisinger Commonwealth School of Medicine, Wilkes-Barre, Pennsylvania, US

Abstract Conduction system pacing involves directly stimulating the specialised His–Purkinje cardiac conduction system with the aim of activating the ventricles physiologically, in contrast to the dyssynchronous activation produced by conventional myocardial pacing. Since the first report of permanent His bundle pacing (HBP) in 2000, the stylet-driven technique of its earliest incarnation has been superseded by a more successful stylet-less approach. Widespread uptake has led to a much greater evidence base. Single-centre observational studies have now been supported by large multicentre, international registries, mechanistic studies and the first randomised controlled trials. New evidence has elucidated mechanisms of HBP and illustrated the nature and magnitude of its potential benefits for preventing pacing-induced cardiomyopathy and correcting bundle branch block. Left bundle branch pacing (LBBP) is a newer technique in which the lead is fixed deep into the left side of the intraventricular septum to allow capture of the left bundle, distal to the His bundle. LBBP holds promise as a method for physiological pacing that overcomes some of the fixation, threshold and sensing challenges of HBP. In this state-of-the-art review of His–Purkinje conduction system pacing, the authors assess recent evidence and current practice and explore emerging and future directions in this rapidly evolving field.

Keywords His bundle pacing, left bundle branch pacing, left bundle area pacing, deep septal pacing, conduction system pacing, cardiac resynchronisation therapy, bundle branch block. Disclosure: ADA has received honoraria from Medtronic. PV has received honoraria from Medtronic, Biotronik, Boston Scientific and Abbott; Research and Fellowship support from Medtronic; and patent pending for His bundle pacing delivery tool. ZIW has received honoraria from Medtronic, Boston Scientific, Micropace and Abbott. Received: 27 April 2020 Accepted: 30 June 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):136–45. DOI: https://doi.org/10.15420/aer.2020.14 Correspondence: Pugazhendhi Vijayaraman, Geisinger Heart Institute, Geisinger Wyoming Valley Medical Center, MC 36-10, 1000 E Mountain Blvd, Wilkes-Barre, PA 18711, US. E: pvijayaraman1@geisinger.edu Support Statement: ADA is supported by the National Institute of Health Research Imperial Biomedical Research Centre and the British Heart Foundation Imperial Centre of Research Excellence (RE/18/4/34215). ZIW receives research funding from the British Heart Foundation, National Institute of Health Research Imperial Biomedical Research Centre and the Coronary Flow Trust. Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Right ventricular apical pacing (RVAP) results in dyssynchronous ventricular activation that can lead to impairment of ventricular function. Alternative myocardial pacing sites such as RV septal pacing (RVSP) and RV outflow tract pacing still rely on myocardial cell-to-cell conduction and have not been shown to prevent pacing-induced cardiomyopathy.1 Biventricular pacing (BVP) certainly improves upon RVAP, but still produces a non-physiological activation pattern.2 Direct pacing of the His–Purkinje conduction system offers the ability to preserve physiological activation of the ventricles in patients with intrinsically normal, narrow QRS complexes. In patients with bundle branch block (BBB), conduction system pacing can deliver cardiac resynchronisation therapy (CRT) by correcting BBB to synchronise ventricular activation.3 The originally favoured site of conduction system stimulation is the His bundle, and there is now large global experience of pacing at this site

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Access at: www.AERjournal.com

with considerable published follow-up data. More recently, new techniques have pulled focus to pacing of the region of the left bundle branch, which has a growing evidence base.4 In this state-of-the-art review of His–Purkinje conduction system pacing, we assess recent evidence and current practice and explore emerging and future directions in this rapidly evolving field.

Terminology His Bundle Pacing Terminology The classification and nomenclature of conduction system pacing has changed since its early period,5 and many definitions are now standardised.6,7 Early discussion of His bundle pacing (HBP) made reference to direct HBP8 as well as to para-Hisian pacing.9 Selective and non-selective HBP (S- and NS-HBP, respectively) are now the two terms used for capture of the His bundle, and their features are outlined in this review. S-HBP results in capture of the His bundle alone without

Conduction System Pacing Figure 1: Conduction System Pacing

Left ventricular septal pacing* Capture of the left side of the IVS, without capture of the conduction system

Selective left bundle branch pacing Capture of the LBB alone, without capture of local myocardium

Non-selective left bundle branch pacing Simultaneous capture of the LBB and local left ventricular septal myocardium

S-LBBP

LVSP

NS-LBBP

S-HBP Selective His bundle pacing Capture of the His bundle alone, without capture of local myocardium Left bundle branch

His

Right bu

ndle bran

NS-HBP Non-selective His bundle pacing Simultaneous capture of both the His bundle and local myocardium

AV node Annular plane

MOP Myocardium-only pacing* Only the local myocardium is captured No capture of conduction system

Anodal capture Ring electrode captures the right side of IVS Simultaneous LBB capture by tip electrode Anodal capture

Right ventricular septal pacing* Left bundle branch block morphology Site of approach for left bundle pacing

RVSP

Mid-septal capture* Morphology observed during traversal of IVS while attempting left bundle pacing Mid-septal capture

Terminology and captured structures during attempted conduction system pacing. Blue represents the conduction system while myocardium and membranous septum are represented in orange. Blue circles represent the functional virtual electrode in different kinds of pacing. In green are capture morphologies seen during attempted His bundle pacing. In red are capture morphologies seen in left bundle branch area pacing. *Direct conduction system capture does not occur (but delayed penetrance into the conduction system may be possible). IVS = interventricular septum; LBB = left bundle branch; LVSP = left ventricular septal pacing ; MOP = myocardium-only pacing; NS-HBP = non-selective His bundle pacing; NS-LBBP = non-selective left bundle branch pacing; RVSP = right ventricular septal pacing S-HBP = selective His bundle pacing; S-LBBP = selective left bundle branch pacing.

myocardial capture. In NS-HBP, in addition to HBP there is capture of surrounding septal myocardium, resulting in septal pre-excitation for most of the duration of His–ventricular (HV) conduction time.

Bundle Branch Block Terminology When HBP is able to narrow the QRS of patients with left or right BBB, varying terms are used to evoke varying explanations of underlying phenomena. ‘His resynchronisation’ or ‘His-CRT’ do not specify a mechanism of QRS shortening.2 ‘Bundle recruitment’ refers to capture of the previously non-functional conduction fibres and the term is used to differentiate this from fusion of myocardial wavefronts, which can produce QRS narrowing when NS-HBP fails to recruit the right bundle in patients with right bundle branch block (RBBB).

Left Septal Pacing Terminology Understandably, given its relatively recent emergence, there is considerably more variation in naming convention in contemporary discussion of pacing the left bundle branch and the surrounding region. Left bundle branch pacing (LBBP) more precisely describes the relevant region of conduction system than ‘left bundle pacing’ given that the longitudinally dissociated and continuous left bundle fibres (both before and after branching) originate in the His bundle. ‘Left bundle branch area’, ‘peri-left-bundle-branch’ and ‘deep septal’ pacing/ capture are also generally used interchangeably to refer to the general trans-interventricular septum (IVS) approach to attempt LBBP but do not specify if conduction system capture is achieved. Selective and non-selective LBB capture are classified similarly as with HBP but, due to the position of the lead ring, anodal capture of the right side of the IVS can also be seen with bipolar deep septal pacing. With emerging

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evidence that endocardial left ventricular (LV) pacing may involve deferred penetrance of activation wavefronts into the conduction system, the term ‘direct’ may return with LBBP to differentiate direct capture of conduction system from this indirect phenomenon.10,11 Figure 1 illustrates the current landscape of terminology, anatomy and conceptual classification of conduction system pacing.

Potential Indications for Conduction System Pacing There are three broad categories of potential indication for conduction system pacing: when a high burden of ventricular pacing is necessary, which includes atrioventricular block (AVB), slowly conducted AF, pacing-induced cardiomyopathy and atrioventricular nodal ablation (AVNA); CRT in patients with heart failure and BBB; and sinus node dysfunction (SND), where AV nodal conduction disease may already coexist or develop during follow-up, and operators can gain experience in conduction system pacing because implant failure is less problematic. Given that HBP has been performed more widely, large registries have collated international experience to provide a picture of contemporary practice, including indications.6,12,13 In the Keene et al. multicentre registry of 529 patients, AVB was the most common indication, seen in half of cases, with slow AF the next most common (27.8%).13 The remainder of the patients had CRT, SND and AVNA in similar proportions (6.6–8.9%). In the Zanon et al. 844 patient multicentre experience, AVB (41.2%) and AF (39.7%) were also the most common indications, but fewer patients underwent His-CRT (1.7%).12 First-degree AVB with narrow QRS, where conduction system pacing can be used to shorten AV delay while preserving physiological ventricular activation, stands apart as a potential indication, and HBP for this indication is

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Cardiac Pacing Table 1: Electrical Responses in Conduction System Pacing for Narrow Intrinsic QRS Parameter

His Bundle Pacing

Left Bundle Branch Area Pacing

QRSd

MOC > NS-HBP >S-HBP = intrinsic

RVSP > LVSP > NS-LBBP <=> S-LBBP > intrinsic

Stim-QRSend or Stim-QRS-LVAT

MOC > NS-HBP = S-HBP = Intrinsic H-QRSend

RVSP > LVSP > NS-LBBP = S-LBBP = Intrinsic LBpo-QRS-LVAT

Stim-V

MOC = NS-HBP < Intrinsic HV = S-HBP

S-LBBP > NS-LBBP = LVSP = RVSP

Conduction system capture confirmation

Multiple thresholds* or Programmed stimulation‡ or H-QRSend = Stim-QRSend

LBpo-QRS-LVAT = Stim-QRS-LVAT or Stim-QRS-LVAT <80 ms or Multiple thresholds† or Programmed stimulation‡

Comparison of ECG parameters with different kinds of capture seen in attempted conduction system pacing in the context of an intrinsically narrow QRS. *During His bundle lead threshold check: initial transition from non-selective His bundle pacing (NS-HBP) to either selective HBP (S-HBP) or myocardium-only capture (MOC) with declining pacing energy output, followed by a second transition from either of these to non-capture with further declining output. Transitions are assessed using QRS duration and morphology, Stim-V and Stim-QRSend time from the table. For example, a transition from NS-HBP to S-HBP will result in shortening of QRS duration, loss of pre-excitation, prolongation of Stim-V and preservation of Stim-QRSend time. †During left bundle branch lead threshold check: initial transition from NS- (or anodal) left bundle branch pacing (LBBP) to either selective LBBP (S-LBBP) or left ventricular septal pacing (LVSP) with declining pacing energy output, followed by a second transition from either of these to non-capture with further declining output. Transitions are assessed using QRS duration and morphology, Stim-V and Stim-QRS-LVAT times from the table. For example, an initial transition from NS-LBBP to S-LBBP will result in prolongation of QRS duration, loss of pre-excitation with appearance of right bundle branch block (RBBB) morphology, prolongation of Stim-V and preservation of Stim-QRS-LVAT time. ‡Programmed stimulation is helpful when multiple thresholds are not seen. A single threshold from broad paced QRS duration (QRSd) to non-capture may be either MOC to non-capture or NS-HBP to non-capture (simultaneous loss of myocardial and His bundle capture). During programmed stimulation (similar to a retrograde curve during electrophysiological study for supraventricular tachycardia) progressively shortened final cycle lengths, following ‘drive trains’ to regulate preceding cycle lengths, can reveal a refractory period difference between His bundle tissue and myocardium. H-QRSend = duration from His potential to QRS offset; HV = interval from His potential to onset of QRS; LBpo-QRS-LVAT = duration from left bundle potential to peak of R wave in lateral leads (where the time of peak of the R wave in lead V5 or V6 is thought to represent lateral LV activation time, LVAT); MOC = myocardium-only capture; NS-HBP = non-selective His bundle pacing; RVSP = right ventricular septal pacing; S-HBP = selective His bundle pacing; Stim-QRSend = duration from pacing stimulus to QRS offset; Stim-QRS-LVAT = duration from pacing stimulus to peak of R wave in lateral leads; Stim-V = interval from pacing stimulus to onset of QRS.

being tested in the His Optimized Pacing Evaluated for Heart Failure (HOPE‐HF) blinded randomised cross-over trial.14 The early experience of LBBP indicates a similar range of indications but with small numbers of patients in published series, the relative proportions are difficult to ascertain. In principle, there is no reason for indications to differ between HBP and LBBP, with the exception of CRT for RBBB where LBBP needs to be carefully studied.

Conduction System Pacing Techniques History of the HBP Technique Stimulation in the region of the cardiac conduction system to achieve physiological ventricular activation and normalised QRS appearance through direct capture of the His bundle or bundle branches was first reported in humans in 1970.15 Temporary para-Hisian pacing has been a standard manoeuvre in electrophysiological (EP) studies for decades,16 but the implantation of an actively fixed His bundle lead was first described in 2000.8 The initial technique involved mapping the region of the His bundle using a steerable catheter inserted via the femoral vein prior to a carefully shaped stylet being used to guide a lead to the mapped His bundle.17 This cumbersome method was refined to the modern stylet-less technique, where a lumenless lead is steered towards the His bundle, a right atrial structure found at the inferior interatrial septum immediately superior to the tricuspid valve, using a pre-shaped sheath or a deflectable sheath.16 Although in its infancy this technique was supported by EP catheter mapping of the region, the ability to map signals from the conduction system and adjacent myocardium and using the lead within the sheath was subsequently described by the Geisinger HBP group.18

Modern HBP Technique The His signal and appropriately balanced atrial and ventricular components (typically a ventricular signal at least twice the amplitude

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of the atrial signal) are identified on the lead electrogram (EGM). EGM and ECG characteristics (Table 1) during pacing can confirm the suitability of the location for fixation. The lead is slowly manually rotated through fewer than 10 complete revolutions (typically five). The modern technique utilises the property of the SelectSecure 3830 lead (Medtronic), where the exposed helix is a constituent part of the tip electrode, rather than only the lead tip itself, proximal to the screw, so that when the screw penetrates the fibrous capsule of the His bundle, the conduction system fibres within the His bundle can be captured at relatively low thresholds. Several registries have demonstrated that the stylet-less technique using a SelectSecure 3830 lead is effective in achieving HBP.6,12,13 In the vast majority of cases, the C315 fixed curve workhorse sheath (Medtronic) is sufficient to reach the His bundle, but in a sizeable minority the deflectable C304 deflectable delivery sheath (Medtronic) is used, with a yet smaller minority requiring modifications to coronary sinus sheaths.19 The C315 has a primary curve to direct leads anteriorly towards the tricuspid annulus and a secondary curve to reach the septum.

Left Bundle Branch Pacing Technique The technique for directly pacing the left bundle branch was first reported by Huang et al. in 2017.20 The 3830 lead was deployed deep in the IVS, 15 mm distal to the His bundle site in a patient whose LBBB was not corrected by HBP. Pacing at this site successfully narrowed the QRS duration with a response consistent with conduction system capture. The technique for this trans-IVS approach to LBBP is now more firmly established.21 The HBP technique is used to first identify the distal His bundle, before moving the sheath tip 1–2 cm more distally along the RV septal surface toward the RV apex (Figure 2). Fixating a lead into the His bundle as an anatomical landmark is useful

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Conduction System Pacing in challenging cases. Pacing at the distal site will produce an LBBBtype pattern including a negative QRS with W-shaped notching in lead V1. Rather than the small number of slow turns recommended for HBP, LBBP requires several bursts of multiple rapid rotations of the SelectSecure 3830 to progress the lead 6–8 mm through the IVS. This may result in a total number of revolutions several times higher than performed in HBP. Periodic checking of the paced QRS characteristics (Table 1) and of lead impedance should be performed after each burst of rotations to confirm if LBB capture has been achieved and to ensure that the lead does not perforate through to the LV cavity, respectively. Contrast injection through the sheath, measuring the point of the lead fulcrum (at the cavity–septum interface) and echocardiography (transoesophageal, intracardiac and, sometimes, transthoracic) can help to identify the depth of lead penetration through the IVS. The paced QRS will change in morphology as the lead progresses through the mid-septum to the left side of the IVS. In lead V1, the emergence of an RBBB type pattern with a notch/R’ wave, thought to represent RV activation, moves later in the QRS complex, the deeper into the septum the lead progresses. The time of peak of the R wave in lead V5 or V6 is thought to represent lateral LV activation time (referred to here as QRS-LVAT to distinguish this measure from LVAT measured using other techniques). The time from the stimulation artefact to QRS-LVAT (Stim-QRS-LVAT) gradually shortens the deeper into the septum the lead is progressed until a step change occurs and Stim-QRS-LVAT substantially shortens to less than 80 ms as left bundle capture is achieved (Figure 3). A left bundle potential may now be seen on lead EGM during intrinsic conduction. In general, the transition from pacing at the RV septum, through the mid-septum to the left septum, where the left bundle can be captured, can be thought of as an LBBB-type paced QRS morphology changing into an RBBB type. There are related techniques that produce deep septal pacing, but do not necessitate conduction system capture, however, it is hypothesised that such techniques, along with trans-interatrial septum endocardial LV pacing, may involve a degree of direct or delayed conduction system capture.10,11,22

Pacing Characteristics in Conduction System Pacing Capture Characteristics in His Bundle Pacing Selective HBP occurs when the His bundle is captured without capture of surrounding local myocardium. In patients with a narrow intrinsic QRS complex, this manifests on 12-lead ECG as an iso-electric interval between the pacing stimulus and the QRS onset (Stim-V interval) that is usually approximately equal to the unpaced, intrinsic interval from the His signal on the lead EGM to the onset of QRS (HV interval). The paced QRS duration (QRSd) is equal to intrinsic QRSd, because the LV and RV are activated entirely via the His–Purkinje conduction system, and therefore the time from the pacing stimulus to the end of the QRS complex (Stim-QRSend) is equal to the time from the His signal to the end of the QRS complex (H-QRSend). The local EGM will be discrete from the pacing artefact, suggesting lack of local myocardial capture (Figure 3). Non-selective HBP occurs when the local septal myocardium is captured alongside capture of the His bundle. During the time where the signal is travelling through the insulated His bundle, local myocardial activation is occurring due to myocardial capture by the pacing stimulus. Therefore, the QRS complex onset occurs very soon, often immediately, after the pacing stimulus, via slow cell-to-cell

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Figure 2: Fluoroscopy of Conduction System Pacing Lead positions LAO

RAO

HBP

LBBP HBP

LBBP

An example of a His bundle pacing (HBP) lead and left bundle branch pacing (LBBP) lead in the same patient in the right anterior oblique (RAO) and left anterior oblique (LAO) projections. RV = right ventricular.

myocardial conduction through a small region. The remainder of the ventricles are activated rapidly by the His–Purkinje system, therefore ventricular activation (and thus the QRS complex) is completed at an identical duration from the pacing stimulus as in S-HBP, but QRSd is longer in NS-HBP due to early ventricular activation. The slow slurred QRS pre-excitation in NS-HBP is akin to a delta wave in patients with manifest accessory pathways and is referred to as the pseudo-deltawave. The local EGM is incorporated into the pacing artefact due to local capture (Figure 4). When the His bundle is not captured but the pacing stimulus nevertheless produces ventricular activation, myocardium-only capture (MOC) occurs. This results in slow cell-to-cell activation of the entirety of both the RV and LV. The measurements that distinguish S-HBP, NSHBP and MOC are set out in Table 1, showing that H-QRSend is the key reference measurement to distinguish individual NS-HBP complexes from MOC. During non-selective His bundle capture the H-QRSend will be equal to Stim-QRSend. This requires co-visualisation of the lead EGM with the 12-lead QRS, which is easily done on EP laboratory systems. Without the reference H-QRSend interval, a sudden prolongation of QRSd, and transition in morphology, from NS-HBP to S-HBP or MOC with declining pacing output during a threshold check can be seen. This diagnoses NS-HBP and MOC. When such a transition is not seen (and a reference H-QRSend measurement is unavailable), there may be either NS-HBP or MOC at all capturing outputs but the distinction cannot easily be made. Recent applications of differences in refractory periods between conduction tissue and myocardium have led to the technique pioneered by Jastrze˛bski et al. to allow HBP-MOC distinction in these cases.23 Programmed stimulation with a fixed S1 drive train and shortening S2 coupling interval can reveal MOC at shortest capturing coupling intervals with NS-HBP at longer coupling intervals. As criteria and manoeuvres for capture confirmation become increasingly complex, the use of artificial intelligence may become important, with proof of concept recently demonstrated.24 Assessing and defining conduction system capture in patients with underlying conduction disease is more complex, and a summary of this is provided in Table 2.

Selective Versus Non-selective His Bundle Pacing The superiority of NS-HBP over MOC has a clear physiological basis, with only NS-HBP, of the two, involving conduction system capture.

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Cardiac Pacing Figure 3: Selective His Bundle Pacing QRS morphology identical to intrinsic A

Isoelectric Stim-V similar to HV interval

B I II III aVR aVL aVF V1 V2 V3 V4 V5 V6

HIS d

Stim-QRSend similar to H-QRSend

EGM distinct from pacing artifact

A: Twelve-lead ECG and electrograms (EGMs) from His bundle pacing (HBP) leads. B: During pacing from the HBP lead, selective capture with QRS morphology identical to baseline is seen. Note the discrete local EGM in the HBP lead suggesting absence of direct myocardial capture. H = His potential; H-QRSend = time from the His signal to the end of the QRS complex; HV = His–ventricular; Stim-QRSend = time from the pacing stimulus to the end of the QRS complex; Stim-V = interval between pacing stimulus and QRS onset.

Although the QRS appearance of MOC may, in some cases, be only subtly different from NS-HBP, in MOC slow cell-to-cell propagation is responsible for LV activation (rather than rapid and physiological conduction system activation).25 However, the relative merits of S-HBP and NS-HBP are a key ongoing controversy in HBP, with important recent evidence illuminating the issue. The 12-lead ECG appearance of S-HBP suggests that both ventricles are activated physiologically, whereas in NS-HBP there is non-physiological activation of some septal myocardium. The extent to which local myocardial capture is physiologically relevant is of importance, because NS-HBP has some potential advantages compared with selective His capture. First, local myocardial capture allows the potential for continued ventricular pacing in the event of the development of infra-Hisian block. Second, the evoked potential of myocardial capture in NS-HBP can be detected using auto-threshold algorithms, but this does not occur with S-HBP, which limits the value of automatic capture detection algorithms.26 Electrical mapping suggests that local myocardial capture mainly affects the basal-to-mid RV, and mechanical synchrony indices suggest that LV activation is dyssynchronous only when conduction system capture is not present (as occurs in MOC), and that LV dyssynchrony is not induced by NS-HBP.14,27 Measurements using ultra-high-frequency ECG, which can spatially segregate signals within the QRS to measure LV electrical synchrony, corroborate electrocardiographic imaging (ECGI) data that LV synchrony is largely unaffected by NS-HBP in comparison with S-HBP or intrinsic activation.28 Beer et al. compared long-term outcomes of heart failure hospitalisation or mortality between S- and NS-HBP and found no significant difference.29 The region of activation from local myocardial capture is small and similar

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to accessory pathway pre-excitation, which only rarely causes dyssynchrony-induced cardiomyopathy.30 The current consensus is that in the vast majority of cases, dyssynchrony induced by NS-HBP is minimal, unless intrinsic HV is very long, and mostly isolated to the RV. In relatively rare cases, presumably in those with a genetic susceptibility to dilated cardiomyopathy and/or NS-HBP with considerable myocardial pre-excitation, NS-HBP dyssynchrony may be problematic. This may explain the slight, statistically nonsignificant, divergence in outcomes between S-HBP and NS-HBP seen in the Beer et al. observational analysis (but this may be due to intrinsic differences in the populations).29

Capture Characteristics in Left Bundle Branch Pacing LBBP also demonstrates selective and non-selective conduction system capture, and LV septal pacing without direct conduction system capture is the equivalent of MOC. Jastrze˛bski et al. showed that programmed stimulation can also be helpful in LBBP.31 However, capture characteristics of LBBP are more complex than HBP. LBBP will result in an RBBB-type morphology. The second component of the QRS (R’) represents RV activation; thus, QRS offset does not demarcate the end of conduction-system activated myocardium. LBBP QRS durations may therefore be longer than intrinsic QRSd. Therefore Stim-QRS-LVAT measurements, using the peak of the R wave in lateral leads, are preferred. This provides a method for assessing the time to lateral LV activation, which is expected to occur via left conduction system capture. The current convention is to assume that left conduction capture has occurred when Stim-QRS-LVAT is shortened to <80 ms. Left bundle potentials are seen with varying frequency (in contrast to

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Conduction System Pacing Figure 4: Non-selective His Bundle Pacing versus Myocardial Capture Short/non-existent Stim-V interval

QRS appears pre-excited B: Non-selective

A: Intrinsic rhythm I

C: Myocardial capture Broad LBBB morphology QRS

II III aVR aVL aVF V1

Stim-QRSend longer than H-QRSend

V2 V3 V4 V5 V6 HRAd

HIS d

Stim-QRSend similar to H-QRSend

EGM not distinct from pacing artefact

A: Twelve-lead ECG and electrograms (EGMs) from right atrial (HRA) and His bundle pacing (HBP) leads. B: During pacing from the HBP lead at 1.0 V, non-selective capture with pre-excited QRS morphology is seen. C: Pacing at 0.8 V demonstrates myocardial-only capture (MOC) with wider QRS morphology and longer stimulus to QRS offset time compared with during His capture in B. Note that there is no discrete local EGM in the HBP lead, suggesting direct myocardial capture has occurred in both B and C. Short or non-existent Stim-V times are a shared feature between non-selective HBP and MOC. H = His potential; H-QRSend = time from the His signal to the end of the QRS complex; HV = His–ventricular; LBBB = left bundle branch block; Stim-QRSend = time from the pacing stimulus to the end of the QRS complex; Stim-V = interval between pacing stimulus and QRS onset.

the near ubiquity of His potentials in HBP), and the interval from potential to QRS onset is typically 15–35 ms. NS-LBBP can be differentiated from LVSP (without LBB capture) using Stim-QRS-LVAT, but recent evidence from Salden et al. suggests that the importance of this distinction is not as clear cut as the NS-HBP/MOC distinction.32 LVSP without direct/immediate LB capture has similar electromechanical characteristics to BVP and HBP. This may be due to delayed/indirect penetrance of left-sided conduction system, or due to the balanced position of the LV septum with regard to intra-LV and inter-ventricular synchrony.

Thresholds in Conduction System Pacing

In general, during LBBP, lead V1 demonstrates RBBB morphology. To confirm LBB capture, in addition to an RBBB paced pattern one or more of the following criteria should be present: presence of LBB potential; evidence for transition from non-selective LBBP to either selective LBBP or LVSP during threshold testing; short and constant Stim-QRSLVAT <80 ms at high and low outputs; and direct LBB capture demonstrated by short retrograde His or anterograde distal conduction system potentials or programmed stimulation to demonstrate LBB capture (Figure 5).

LBBP thresholds have been noted to be very low (usually <1 V at 0.5 ms) since its inception and low thresholds are reported in every series.10,33–35 Post-implant threshold rises are observed in around 7% of cases in HBP and may be due to micro-displacement or fibrosis. They occur frequently enough to encourage some operators to implant back-up RV leads (although this practice is declining).14 They can occur early (prior to initial follow-up) but very late rises have also been seen >6 months or even 1 year after follow up despite stable, low intervening thresholds.12 Such threshold rises have not been seen yet with LBBP, which is promising, but this is in the context of a much smaller published experience and short-term follow-up.

Sensing From Conduction System Leads R wave amplitudes sensed from His leads are generally lower than 5 mV and atrial EGMs of varying amplitudes may also be present.3 Therefore, there is the potential for ventricular under-sensing and possible atrial over-sensing. LBBP leads that are surrounded by abundant myocardium have larger R waves, providing one very clear advantage over HBP.10

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The HBP thresholds are typically higher than for RV myocardial capture, but large contemporary registries suggest that improvements in technique have considerably reduced this issue, with mean His capture thresholds of 1.4 ± 0.9 V at 0.8 ± 0.3 ms, and 1.6 ± 1.0 V at 0.8 ± 0.4 ms observed in the two recent large registries.8,12,14 The Keene et al. registry showed that there is a learning curve with HBP and that after 30–50 cases the implant threshold is reduced, as is fluoroscopy time.14 Recent insights into the importance of His injury currents to determine conduction system lead fixation have also improved thresholds.13

Outcomes in Conduction System Pacing Success Rates and Safety Profile of Conduction System Pacing Reports of HBP implant success rates range from 72 to 92%, but success definitions have not always been standardised and lower rates

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Cardiac Pacing Table 2: Electrical Responses in His Bundle Pacing for Broad Intrinsic QRS Intrinsic QRS

Degree of BBB correction

His Bundle Pacing

LBBB

Full correction

S-HBP Normal QRS appearance (no BBB morphology) Stim-QRSend < H-QRSend paced QRSd < 120 ms < intrinsic QRSd

NS-HBP Pre-excited normal QRS appearance (no BBB morphology) Stim-QRSend usually < H-QRSend paced QRSd >120 ms paced QRSd usually < intrinsic QRSd

Partial correction

S-HBP LBBB morphology Stim-QRSend < H-QRSend paced QRSd < intrinsic QRSd

NS-HBP LBBB QRS morphology Stim-QRSend </= H-QRSend paced QRSd >120 ms paced QRSd usually < intrinsic QRSd

No correction

Stim-QRSend = H-QRSend S-HBP LBBB morphology paced QRSd = intrinsic QRSd

RBBB*

IVCD

NS-HBP LBBB morphology paced QRSd > intrinsic QRSd

Myocardium-only capture

LBBB morphology Stim-QRSend usually > H-QRSend paced QRSd > intrinsic QRSd

Bundle recruitment

S-HBP Normal QRS appearance (No BBB morphology) Stim-QRSend < H-QRSend paced QRSd < 120 ms < intrinsic QRSd

Resynchronisation

NS-HBP without right bundle recruitment Pre-excited normal QRS appearance (No BBB morphology) Stim-QRSend < H-QRSend paced QRSd < intrinsic QRSd

No bundle recruitment or resynchronisation

S-HBP without right bundle recruitment RBBB morphology Stim-QRSend = H-QRSend paced QRSd = intrinsic QRSd

Myocardium-only capture

LBBB morphology Stim-QRSend > H-QRSend paced QRSd > intrinsic QRSd

Partial correction

Variable response†

No correction

S-HBP Stim-QRSend = H-QRSend paced QRSd = intrinsic QRSd

Myocardium-only capture

LBBB morphology Stim-QRSend </=/> H-QRSend paced QRSd </=/> intrinsic QRSd

NS-HBP Pre-excited normal QRS appearance (No BBB morphology) Stim-QRSend < H-QRSend paced QRSd </=/> intrinsic QRSd

NS-HBP Stim-QRSend < H-QRSend paced QRSd </=/> intrinsic QRSd

Comparison of 12-lead ECG responses to different kinds of conduction system capture in His bundle pacing (HBP) for broad intrinsic QRS complex. *Right bundle branch block (RBBB) can be resynchronised in two ways: bundle recruitment with or without myocardial capture; and non-selective (NS)-HBP without bundle recruitment, which will resynchronise the right ventricle due to the presence of at least two wavefronts in the right ventricle (one from myocardial capture and at least one breakout from the left ventricle). †ECG response of intraventricular conduction delay (IVCD) to conduction system pacing depends on degree of correctable left- or right-sided conduction system delay present. BBB = bundle branch block; H-QRSend = duration from His potential to QRS offset; LBBB = left bundle branch block; QRSd = QRS duration; S-HBP = selective His bundle pacing; Stim-QRSend = duration from pacing stimulus to QRS offset.

are seen with His-CRT.3,13,36,37 Transient AVB and RBBB can be seen during implant. Macro-displacements are rare but rising thresholds are not uncommon. Combining macro-displacement and high threshold as indications for redo procedures, the re-intervention rate is between 6% and 8% in larger long-term studies.12,13,37,38 The early indications are that LBBP has a high success rate (>80%) with low re-intervention rates, and that lead perforation of the deeply fixated LBB lead into the LV cavity is very rare.39 There may, however, be patient populations for whom LBBP is more challenging, such as patients with extensive septal fibrosis or scarring. Longer term follow-up data from large registries are also awaited.

Clinical Outcomes in Conduction System Pacing Despite more than 20 years of progressively increasing experience of permanent HBP, several years of widespread global interest and uptake and a sizeable social media presence,40 there have been no long-term, large-scale, clinical outcome driven, randomised controlled trials (RCT) of conduction system pacing. The HOPE-HF trial is due to report in 2020

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and is the only large-scale RCT imminent.14 In the first decade of BVP, more than 6,000 patients were randomised to BVP versus standard-ofcare trials,but if current trends continue it is unlikely even a tenth of that population will be randomised in conduction system pacing RCTs.39 Indeed the established presence of BVP is a key factor that makes trial design for conduction system pacing difficult, alongside disruption by the novel LBBP technique.39 Therefore, we must rely on observational data to make any inferences about long-term clinical outcomes in conduction system pacing. Improvements in quality of life, 6-minute walk test, LV ejection fraction (LVEF), LV size, heart failure hospitalisations and mortality have been seen with HBP in comparison with RVP. Some of the most compelling evidence comes from a comparison of a hospital performing HBP with a nearby hospital with operators who did not perform HBP, but with otherwise similar populations and standards of care.41 HBP was associated with a statistically significant 29% reduction in the primary outcome of death, heart failure or upgrade to BVP at 2-year follow-up in that 756 patient study, and the effect was most pronounced in the subgroup with >20% ventricular pacing

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Conduction System Pacing Figure 5: Left Ventricular Septal Pacing versus Left Bundle Branch Pacing Left bundle branch pacing LVS captured alone 3V

NS-LBBP

LVS + LBB both captured 8V

LVS + LBB both captured 0.6V

LBB captured alone 0.5V

I II III aVR aVL aVF V1 V2 V3 V4 105

Short LVAT preserved

LBBP LB

H His

H A Unpaced

H B LVSP

C NS-LBBP Position 1

D Unpaced

E NS-LBBP

F S-LBBP

Position 2

Twelve-lead ECG and electrograms from His bundle pacing and left bundle branch pacing (LBBP) leads are shown. A: Initial left ventricular septal (LVS) site shows small left bundle branch (LBB) potential prior to pacing. B: Pacing at 3 V shows long Stim-QRS-LVAT of 105 ms without a right bundle branch block (RBBB) pattern, indicating the LVS myocardium is captured alone. C: Pacing at 8 V shows shorter Stim-QRS-LVAT of 80 ms with an RBBB pattern demonstrating simultaneous capture of the LVS and the LBB. D: At final site, the LBBP lead shows a large LBB potential with injury current prior to pacing. E: Pacing at 0.6 V demonstrates non-selective (NS-) LBB capture with short Stim-QRS-LVAT of 80 ms. F: Pacing at 0.5 V shows selective (S-) LBB capture with short Stim-QRS-LVAT of 80 ms. Unlike the transition between left ventricular septal pacing (LVSP) and LBBP, the transition between NS-LBBP and S-LBBP preserves a short Stim-QRS-LVAT. Both E and F demonstrate retrograde His (H) potentials with short stim-H intervals. Stim-QRS-LVAT is the time from stimulus to peak of R wave in lateral 12-lead ECG leads (where the time of peak of the R wave in lead V5 or V6 is thought to represent lateral LV activation time, LVAT). LBB = left bundle branch; LBBP = left bundle branch pacing; LVAT = left ventricular activation time; LVS = left ventricular septal; LVSP = left ventricular septal pacing; NS-LBBP = non-selective left bundle branch pacing; S-LBBP = selective left bundle branch pacing.

burden, with the 25% event rate for the primary outcome demonstrating that the difference was clinically meaningful in absolute terms.41 Smallscale observational studies of LBBP suggest similar clinical and echocardiographic outcomes, but larger, long-term studies and headto-head comparisons with RVP, BVP and HBP will be required to fully assess LBBP outcomes.11

Conduction System CRT The role of conduction system pacing to resynchronise BBB in patients with heart failure is a particular indication for which recent insights have greatly altered our understanding. El-Sherif et al. observed in the 1970s that pacing the distal portion of the His bundle could correct LBBB to create a narrow QRS complex.42 Lustgarten et al. demonstrated that this could be achieved with permanent HBP in 2010.43 Subsequent observational studies show that HBP can shorten QRS duration and improve cardiac function and symptoms in patients with heart failure and LBBB.44–46 Given these data, His-CRT has gained prominence as a bail-out in cases of failed BVP, but the burning question in this field was whether the physiological nature of resynchronisation by His-CRT produced better outcomes than BVP. In 2019, a pilot head-to-head comparison between the two modalities was published – His Bundle Pacing versus Coronary

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Sinus Pacing for CRT (HIS-SYNC).47 His-CRT produced greater QRSd reduction than BVP but a statistically significant difference in LVEF improvement was not found. Unfortunately, the study suffered from a very high rate of cross-over from the HBP arm to the BVP arm, and the reasons for this illustrate the current challenges facing His-CRT. Half of crossovers were attributed to ECGs showing intraventricular conduction delay rather than LBBB. Thirty per cent crossed over due to inability to correct LBBB.47 Arnold et al. have demonstrated, in a withinpatient comparison, that when HBP successfully corrects LBBB, the haemodynamic and electrical improvements are greater than with BVP.2 HIS-SYNC showed that successful His-CRT requires selection of patients with conduction system disease amenable to correction by HBP and that improved implantation tools are required to facilitate correction in these patients.47 Upadhyay et al. have shown the physiological basis for patient selection.48 They found, by studying the left-sided conduction system, that patients with 12-lead ECG appearances of LBBB have variation in the nature of conduction disease. The majority had conduction block within the bundle of His, clearly amenable to correction by HBP. A smaller proportion had proximal conduction block within the proximal conduction system but distal to the His bundle: the block was located in the left bundle branch.48 Such patients may be amenable to HBP

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Cardiac Pacing correction, but LBBP offers a more plausible corrective method. Importantly, in a sizeable minority of their population of patients attending for ventricular tachycardia ablation (36%), the left-sided conduction system appeared to be intact; QRS widening in these patients was presumed to be due to intramyocardial conduction delay. The 12-lead ECG features of typical LBBB do not seem to reliably discriminate between these groups. Practical methods to distinguish these LBBB phenotypes are required alongside tools dedicated to maximising resynchronisation achieved by conduction system pacing. It should be noted that even though conduction system pacing will not correct it, LV septal pacing may have a role in patients with intraventricular conduction delay with intact conduction system. This group includes, for example, a combination of LV hypertrophy and left axis deviation, which can appear on 12-lead ECG as LBBB. LV septal pacing can produce improvements in AV delay in such patients, while activation pattern may be improved compared to the intrinsic pattern.49 LBBP is also able to resynchronise LBBB but the literature is sparse. Published series and case reports include few patients with LBBB.35,49,51 LBBP is promising for CRT due to its presumed ability to correct block within the His bundle and the proximal left bundle. Furthermore, even if the conduction system is not captured, pacing in the LV septum appears to produce similar electromechanical improvements to BVP.32 This potentially makes patient selection less of a problem: even intraventricular conduction delay with intact conduction system (including e.g. LV hypertrophy ECG appearances) might be potentially resynchronised to some degree, and furthermore there is scope for AV delay improvement.50 Conversely, given that LBBP produces an RBBB pattern, HBP is likely to have an advantage over LBBP for resynchronising RBBB. HBP can resynchronise RBBB in two ways: direct recruitment of the right bundle; and NS-HBP results in a wavefront from the basal RV (local myocardial capture) meeting another wavefront originating more apically (from left bundle mediated activation of the RV).52 The HOPE-HF study is recruiting patients with long PR intervals and both narrow QRS and RBBB, and will provide evidence in this group.14

Recent Advances and Future Directions in Conduction System Pacing New, dedicated HBP sheaths from different manufacturers are on the horizon and it is likely that dedicated equipment for LBBP will follow. Recently some operators have returned to stylet-driven HBP.53,54 This permits variation in lead model as well as an alternate approach in challenging cases. 3D electro-anatomical mapping for pacing the His bundle and left bundle is another area of interest, offering the ability to eliminate or minimise fluoroscopy for the benefit of operators and

Ng AC, Allman C, Vidaic J, et al. Long-term impact of right ventricular septal versus apical pacing on left ventricular synchrony and function in patients with second-or thirddegree heart block. Am J Cardiol 2009;103:1096–101. https:// doi.org/10.1016/j.amjcard.2008.12.02; PMID: 19361596. Arnold AD, Shun-Shin MJ, Keene D, et al. His resynchronization versus biventricular pacing in patients with heart failure and left bundle branch block. J Am Coll Cardiol 2018;72:3112–22. https://doi.org/10.1016/j.jacc.2018.09.073; PMID: 30545450. Ali N, Keene D, Arnold A, et al. His bundle pacing: a new frontier in the treatment of heart failure. Arrhythm Electrophysiol Rev 2018;7:103–10. https://doi.org/10.15420/aer.2018.6.2; PMID: 29967682. Verma N, Knight BP. Update in cardiac pacing. Arrhythm Electrophysiol Rev 2019;8:228–33. https://doi.org/10.15420/ aer.2019.15.3; PMID: 31463061. Dandamudi G, Vijayaraman P. History of His bundle pacing. J Electrocardiol 2017;50:156–60. https://doi.org/10.1016/j.

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patients, but restricting practice to operators familiar with mapping and in some cases prolonging overall procedure time.55,56 Alternately, an EGM-only guided approach to successful HBP with minimal fluoroscopy was recently reported by Zanon et al. to be compatible with use of the SelectSecure 3830 lead.57 Automated analysis of HBP ECGs is in development and this has the potential to facilitate even more rapid uptake of the technique.24 Meanwhile, new evidence is gathering regarding the relative efficacy of LBBP compared with HBP, and its ECG characteristics are being more rigorously codified.

Conclusion Conduction system pacing previously referred only to HBP but is now seen as a collection of techniques: pacing the His bundle, the proximal left conduction system, and the region surrounding it. Initial studies of HBP were mainly confined to single-centre observational series, but widespread interest and uptake of HBP have led to large multicentre, international registries, longer-term follow-up studies and the first RCTs. With more evidence we have gained new insights into the mechanisms of HBP and the nature and magnitude of its benefits, including its ability to prevent pacing-induced cardiomyopathy and to physiologically resynchronise LBBB. Greater scrutiny has also elucidated the limitations of HBP, such as high thresholds, small R waves, long fluoroscopy times and higher failure rates, but larger datasets have also shown that these limitations can be considerably mitigated by operator experience. LBBP has emerged more recently with an impressive rate of accumulation of early evidence. Although it has the potential to address many of the challenges of HBP, its growing evidence base is still sparse and the technique is evolving. Development of newer leads and delivery systems specifically geared towards conduction system pacing addressing the current limitations is necessary to democratise its use. As permanent conduction system pacing enters its third decade, global enthusiasm continues to accelerate and the coming years will hopefully see physiological pacing realise its full potential.

Clinical Perspective • His bundle pacing has rapidly evolved and has been shown to restore physiologic activation of the ventricles and maintain ventricular synchrony. • More stable and distal conduction system pacing in the left bundle branch region is a newcomer to the field of physiologic pacing and early evidence suggests it shows promise. • Randomised controlled clinical trials of the new forms of pacing for bradycardia and resynchronisation therapy are lacking and are essential to gain additional evidence related to the risks and benefit of this approach.

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characteristics and pacing parameters between left bundle branch pacing and right ventricular pacing in patients receiving pacemaker therapy. Europace 2019;21:673–80. https://doi.org/10.1093/europace/euy252; PMID: 30462207. Hou X, Qian Z, Wang Y, et al. Feasibility and cardiac synchrony of permanent left bundle branch pacing through the interventricular septum. Europace 2019;21:1694–702. https:// doi.org/10.1093/europace/euz188; PMID: 31322651. Zanon F, Abdelrahman M, Marcantoni L, et al. Long term performance and safety of His bundle pacing: a multicenter experience. J Cardiovasc Electrophysiol 2019;30:1594–601. https://doi.org/10.1111/jce.14063; PMID: 31310410. Keene D, Arnold AD, Jastrze˛bski M, et al. His bundle pacing, learning curve, procedure characteristics, safety, and feasibility: insights from a large international observational study. J Cardiovasc Electrophysiol 2019;30:1984–93. https://doi. org/10.1111/jce.14064; PMID: 31310403. Keene D, Arnold A, Shun‐Shin MJ, et al. Rationale and design of

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29. Beer D, Sharma PS, Subzposh FA, et al. Clinical outcomes of selective versus nonselective His bundle pacing. JACC Clin Electrophysiol 2019;5:766–74. https://doi.org/10.1016/j. jacep.2019.04.008; PMID: 31320004. 30. Emmel M, Balaji S, Sreeram N. Ventricular preexcitation associated with dilated cardiomyopathy: a causal relationship? Cardiol Young 2004;14:594–9. https://doi.org/10.1017/ S1047951104006031; PMID: 15679994. 31. Jastrze˛bski M, Moskal P, Bednarek A, et al. Programmed deep septal stimulation: a novel maneuver for the diagnosis of left bundle branch capture during permanent pacing. J Cardiovasc Electrophysiol 2020;31:485–93. https://doi.org/10.1101/786665; PMID: 31930753. 32. Salden FC, Luermans JG, Westra SW, et al. Short-term hemodynamic and electrophysiological effects of cardiac resynchronization by left ventricular septal pacing. J Am Coll Cardiol 2020;75:347–59. https://doi.org/10.1016/j. jacc.2019.11.040; PMID: 32000945. 33. Chen X, Wu S, Su L, et al. The characteristics of the electrocardiogram and the intracardiac electrogram in left bundle branch pacing. J Cardiovasc Electrophysiol 2019;30:1096–101. https://doi.org/10.1111/jce.13956; PMID: 31094058. 34. Jastrze˛bski M, Moskal P, Bednarek A, et al. First Polish experience with permanent direct pacing of the left bundle branch. Kardiol Pol 2019;77:580–1. https://doi.org/10.33963/ KP.14850; PMID: 31125031. 35. Li Y, Chen K, Dai Y, et al. Left bundle branch pacing for symptomatic bradycardia: implant success rate, safety, and pacing characteristics. Heart Rhythm 2019;16:1758–65. https:// doi.org/10.1016/j.hrthm.2019.05.014; PMID: 31125667. 36. Vijayaraman P, Dandamudi G, Lustgarten D, et al. Permanent His bundle pacing: electrophysiological and echocardiographic observations from long‐term follow‐up. Pacing Clin Electrophysiol 2017;40:883–91. https://doi.org/10.1111/ pace.13130; PMID: 28569391. 37. Zanon F, Ellenbogen KA, Dandamudi G, et al. Permanent Hisbundle pacing: a systematic literature review and metaanalysis. Europace 2018;20:1819–26. https://doi.org/10.1093/ europace/euy058; PMID: 29701822. 38. Vijayaraman P, Naperkowski A, Subzposh FA, et al. Permanent His-bundle pacing: long-term lead performance and clinical outcomes. Heart Rhythm 2018;15:696–702. https://doi. org/10.1016/j.hrthm.2017.12.022; PMID: 29274474. 39. Arnold AD, Vijayaraman P. Editorial commentary: His bundle pacing: the road ahead. Trends Cardiovasc Med 2019;29:333–4. https://doi.org/10.1016/j.tcm.2018.10.004; PMID: 31234967. 40. Beer D, Dandamudi G, Mandrola JM, et al. His-bundle pacing: impact of social media. Europace 2019;21:1445–50. https://doi. org/10.1093/europace/euz169; PMID: 31230085. 41. Abdelrahman M, Subzposh FA, Beer D, et al. Clinical outcomes of His bundle pacing compared to right ventricular pacing. J Am Coll Cardiol 2018;71:2319–30. https://doi.org/10.1016/j. jacc.2018.02.048; PMID: 29535066. 42. El-Sherif N, Amay-Y-Leon F, Schonfield C, et al. Normalization of bundle branch block patterns by distal His bundle pacing. Clinical and experimental evidence of longitudinal dissociation in the pathologic his bundle. Circulation 1978;57:473–83. https://doi.org/10.1161/01.CIR.57.3.473; PMID: 624157. 43. Lustgarten DL, Calame S, Crespo EM, et al. Electrical resynchronization induced by direct His-bundle pacing. Heart Rhythm 2010;7:15–21. https://doi.org/10.1016/j. hrthm.2009.09.066; PMID: 19914142.

44. Ajijola OA, Upadhyay GA, Macias C, et al. Permanent Hisbundle pacing for cardiac resynchronization therapy: initial feasibility study in lieu of left ventricular lead. Heart Rhythm 2017;14:1353–61. https://doi.org/10.1016/j.hrthm.2017.04.003; PMID: 28400315. 45. Huang W, Su L, Wu S, et al. Long-term outcomes of His bundle pacing in patients with heart failure with left bundle branch block. Heart 2019;105:137–43. https://doi.org/10.1136/ heartjnl-2018-313415; PMID: 30093543. 46. Teng AE, Massoud L, Ajijola OA. Physiological mechanisms of QRS narrowing in bundle branch block patients undergoing permanent His bundle pacing. J Electrocardiol 2016;49:644–8. https://doi.org/10.1016/j.jelectrocard.2016.07.013; PMID: 27485351. 47. Upadhyay GA, Vijayaraman P, Nayak HM, et al. His corrective pacing or biventricular pacing for cardiac resynchronization in heart failure. J Am Coll Cardiol 2019;74:157–9. https://doi. org/10.1016/j.jacc.2019.04.026; PMID: 31078637. 48. Upadhyay GA, Cherian T, Shatz DY, et al. Intracardiac delineation of septal conduction in left bundle branch block patterns: mechanistic evidence of left intra-Hisian block circumvented by His pacing. Circulation 2019;139:1876–88. https://doi.org/10.1161/CIRCULATIONAHA.118.038648; PMID: 30704273. 49. Lin J, Dai Y, Wang H, et al. A comparison of left bundle branch pacing with His bundle pacing in a patient with heart failure and left bundle branch block. HeartRhythm Case Rep 2019;6:293–6. https://doi.org/10.1016/j.hrcr.2019.10.007; PMID: 32577379. 50. Sohaib SA, Wright I, Lim E, et al. Atrioventricular optimized direct His bundle pacing improves acute hemodynamic function in patients with heart failure and PR interval prolongation without left bundle branch block. JACC Clin Electrophysiol 2015;1:582–91. https://doi.org/10.1016/j. jacep.2015.08.008; PMID: 29759412. 51. Chan JYS, Huang WJ, Yan B. Non-invasive electrocardiographic imaging of His-bundle and peri-left bundle pacing in left bundle branch block. Europace 2019;21:837. https://doi. org/10.1093/europace/euy293; PMID: 30590453. 52. Sharma PS, Naperkowski A, Bauch TD, et al. Permanent His bundle pacing for cardiac resynchronization therapy in patients with heart failure and right bundle branch block. Circ Arrhythm Electrophysiol 2018;11:e006613. https://doi. org/10.1161/CIRCEP.118.006613; PMID: 30354292. 53. Kneller J. His bundle pacing: new approach using styletsupported pacing leads. EP Lab Digest 2018;18:10–2. 54. Orlov MV, Casavant D, Koulouridis I, et al. Permanent Hisbundle pacing using stylet-directed, active-fixation leads placed via coronary sinus sheaths compared to conventional lumen-less system. Heart Rhythm 2019;16:1825–31. https://doi. org/10.1016/j.hrthm.2019.08.017; PMID: 31425775. 55. Sharma PS, Huang HD, Trohman RG, et al. Low fluoroscopy permanent His bundle pacing using electroanatomic mapping: a feasibility study. Circ Arrhythm Electrophysiol 2019;12:e006967. https://doi.org/10.1161/CIRCEP.118.006967; PMID: 30704289. 56. Vijayaraman P, Panikkath R, Mascarenhas V, et al. Left bundle branch pacing utilizing three dimensional mapping. J Cardiovasc Electrophysiol 2019;30:3050–6. https://doi. org/10.1111/jce.14242; PMID: 31626377. 57. Zanon F, Marcantoni L, Zuin M, et al. Electrogram‐only guided approach to His bundle pacing with minimal fluoroscopy: a single‐center experience. J Cardiovasc Electrophysiol 2020;31:805–12. https://doi.org/10.1111/jce.14366; PMID: 31976602.

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Big Data and Artificial Intelligence: Opportunities and Threats in Electrophysiology Rutger R van de Leur,1 Machteld J Boonstra,1 Ayoub Bagheri,1,2 Rob W Roudijk,1,3 Arjan Sammani,1 Karim Taha,1,3 Pieter AFM Doevendans,1,3,5 Pim van der Harst,1 Peter M van Dam,1 Rutger J Hassink,1 René van Es1 and Folkert W Asselbergs1,4,6 1. Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; 2. Department of Methodology and Statistics, Utrecht University, Utrecht, the Netherlands; 3. Netherlands Heart Institute, Utrecht, the Netherlands; 4. Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK; 5. Central Military Hospital Utrecht, Ministerie van Defensie, Utrecht, the Netherlands; 6. Health Data Research UK and Institute of Health Informatics, University College London, London, UK

Abstract The combination of big data and artificial intelligence (AI) is having an increasing impact on the field of electrophysiology. Algorithms are created to improve the automated diagnosis of clinical ECGs or ambulatory rhythm devices. Furthermore, the use of AI during invasive electrophysiological studies or combining several diagnostic modalities into AI algorithms to aid diagnostics are being investigated. However, the clinical performance and applicability of created algorithms are yet unknown. In this narrative review, opportunities and threats of AI in the field of electrophysiology are described, mainly focusing on ECGs. Current opportunities are discussed with their potential clinical benefits as well as the challenges. Challenges in data acquisition, model performance, (external) validity, clinical implementation, algorithm interpretation as well as the ethical aspects of AI research are discussed. This article aims to guide clinicians in the evaluation of new AI applications for electrophysiology before their clinical implementation.

Keywords Artificial intelligence, deep learning, neural networks, cardiology, electrophysiology, ECG, big data Disclosure: The authors have no conflicts of interest to declare. Funding: This study was partly supported by The Netherlands Organisation for Health Research and Development (ZonMw, grant number 104021004) and partly supported by the Netherlands Cardiovascular Research Initiative, an initiative with support of the Dutch Heart Foundation (grant numbers CVON2015-12 eDETECT and QRS-VISION 2018B007). FWA is supported by UCL Hospitals NIHR Biomedical Research Center. AS is supported by the UMC Utrecht Alexandre Suerman MD/PhD programme. Received: 8 June 2020 Accepted: 3 August 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):146–54. DOI: https://doi.org/10.15420/aer.2020.26 Correspondence: FW Asselbergs, Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, the Netherlands. E: f.w.asselbergs@umcutrecht.nl Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Clinical research that uses artificial intelligence (AI) and big data may aid the prediction and/or detection of subclinical cardiovascular diseases by providing additional knowledge about disease onset, progression or outcome. Clinical decision-making, disease diagnostics, risk prediction or individualised therapy may be informed by insights obtained from AI algorithms. As health records have become electronic, data from large populations are becoming increasingly accessible.1 The use of AI algorithms in electrophysiology may be of particular interest as large data sets of ECGs are often readily available. Moreover, data are continuously generated by implantable devices, such as pacemakers, ICDs or loop recorders, or smartphone and smartwatch apps.2–6 Interpretation of ECGs relies on expert opinion and requires training and clinical expertise which is subjected to considerable inter- and intra-clinician variability.7–12 Algorithms for the computerised interpretation of ECGs have been developed to facilitate clinical decision-making. However, these algorithms lack accuracy and may provide inaccurate diagnoses which may result in misdiagnosis when not reviewed carefully.13–18

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Substantial progress in the development of AI in electrophysiology has been made, mainly concerning ECG-based deep neural networks (DNNs). DNNs have been tested to identify arrhythmias, to classify supraventricular tachycardias, to predict left ventricular ejection fraction, to identify disease development in serial ECG measurements, to predict left ventricular hypertrophy and to perform comprehensive triage of ECGs.6,19–23 DNNs are likely to aid non-specialists with improved ECG diagnostics and may provide the opportunity to expose yet undiscovered ECG characteristics that indicate disease. With this progress, the challenges and threats of using AI techniques in clinical practice become apparent. In this narrative review, recent progress of AI in the field of electrophysiology is discussed together with its opportunities and threats.

A Brief Introduction to Artificial Intelligence AI refers to mimicking human intelligence in computers to perform tasks that are not explicitly programmed. Machine learning (ML) is a branch of AI concerned with algorithms to train a model to perform a task. Two types of ML algorithms are supervised learning and

AI in Electrophysiology: Opportunities and Threats unsupervised learning. Supervised learning refers to ML algorithms where input data are labelled with the outcome and the algorithm is trained to approximate the relation between input data and outcome. In unsupervised learning, input data are not labelled and the algorithm may discover data clusters in the input data. In ML, an algorithm is trained to classify a data set based on several statistical and probability analyses. In the training phase, model parameters are iteratively tuned by penalising or rewarding the algorithm based on a true or false prediction. Deep learning is a subcategory of ML that uses DNNs as architecture to represent and learn from data. The main difference between deep learning and other ML algorithms is that DNNs can learn from raw data, such as ECG waveforms, in an end-to-end manner with extraction and classification united in the algorithm (Figure 1a). For example, in ECG-based DNNs, a matrix containing the time-stamped raw voltage values of each lead are used as input data. In other ML algorithms, features like heart rate or QRS duration are manually extracted from the ECG and used as input data for the classification algorithm.

Figure 1: Traditional Machine Learning and Deep Learning with a Schematic Representation of Fitting a Model to a Data Set A

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To influence the speed and quality of the training phase, the setting of hyperparameters, such as the settings of the model architecture and training, is important. Furthermore, overfitting or underfitting the model to the available data set must be prevented. Overfitting can occur when a complex model is trained using a small data set. The model will precisely describe the training data set but fail to predict outcomes using other data (Figure 1b). On the other hand, when constraining the model too much, underfitting occurs (Figure 1b), also resulting in poor algorithm performance. To assess overfitting, a data set is usually divided into a training data set, a validation data set and a test data set, or resampling methods are used, such as crossvalidation or bootstrapping.24 To train and test ML algorithms, particularly DNNs, it is preferable to use a large data set, known as big data. Performance of highly dimensional algorithms – e.g. algorithms with many model parameters such as DNNs – depends on the size of the data set. For deep learning, more data is often required as DNNs have many non-linear parameters and non-linearity increases the flexibility of an algorithm. The size of a training data set has to reasonably approximate the relation between input data and outcome and the amount of testing data has to reasonably approximate the performance measures of the DNN. Determining the exact size of a training and testing data set is difficult.25,26 It depends on the complexity of algorithm (e.g. the number of variables), the type of the algorithm, the number of outcome classes and the difficulty of distinguishing between outcome classes as inter-class differences might be subtle. Therefore, size of the data set should be carefully reviewed for each algorithm. A rule of thumb for the adequate size of a validation data set is 50–100 patients per outcome class to determine overfitting. Recent studies published in the field of ECG-based DNNs used between 50,000 and 1.2 million patients.6,19,21,27

data quality of ECGs, as these data are easily acquired and large data sets are readily available.

Technical Specifications of ECGs ECGs are obtained via electrodes on the body surface using an ECG device. The device samples the continuous body surface potentials and the recorded signals are filtered to obtain a clinically interpretable ECG.28 As the diagnostic information of the ECG is contained below 100 Hz, a sampling rate of at least 200 Hz is required according to the Nyquist theorem.29–33 Furthermore, an adequate resolution of at least 10 µV is recommended to also obtain small amplitude fluctuations of the ECG signal. In the recorded signal, muscle activity, baseline wander, motion artefacts and powerline artefacts are also present, distorting the measured ECG. To remove noise and obtain an easily interpretable ECG, a combination of a high-pass filter of 0.67 Hz and a low-pass filter of 150–250 Hz is recommended, often combined with a notch filter of 50 Hz or 60 Hz. The inadequate setting of these filters might result in a loss of information such as QRS fragmentation or notching, slurring or distortion of the ST segment. Furthermore, a loss of QRS amplitude of the recorded signal might be the result of the inappropriate combination of a high frequency cut-off and sampling frequency.28,34 ECGs used as input for DNNs are often already filtered, thus potentially relevant information might already be lost. As DNNs process and interpret the input data differently, filtering might be unnecessary and potentially relevant information may be preserved. Furthermore, as filtering strategies differ between manufacturers and even different versions of ECG devices, the performance of DNNs might be affected when ECGs from different ECG devices are used as input data.

Prerequisites for AI in Electrophysiology Preferably, data used to create AI algorithms is objective, as subjectivity may introduce bias in the algorithm. To ensure clinical applicability of created algorithms, ease of access to input data, difference in data quality in different clinical settings as well as the intended use of the algorithm should be considered. In this section, we mainly focus on the

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Apart from applied software settings, such as sampling frequency or filter settings, the hardware of ECG devices also differs between manufacturers. Differences in analogue to digital converters, type of electrodes used, or amplifiers also affect recorded ECGs. The effect of input data recorded using different ECG devices on the performance of

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Clinical Arrhythmias Figure 2: The Effect of Shifting Precordial Electrodes Upward or Downward

of all unique measurements. However, conventional 12-lead ECG is widely accepted for most clinical applications. An adjustment of a lead position is only considered when a posterior or right ventricle MI or Brugada syndrome is suspected.27,47–50 The interpretation of ECGs by computers and humans is fundamentally different and factors like electrode positioning or lead misplacement might influence algorithms. However, the effect of electrode misplacement or reversal, disease-specific electrode positions or knowledge of lead positioning on the performance on DNNs remains to be identified. A recent study was able to identify misplaced chest electrodes, implying that the effect of electrode misplacement might be able to be identified and acknowledged by algorithms.51 Studies have suggested that DNNs can achieve similar performance when fewer leads are used.50

ECG Input Data Format ECGs can be obtained from the electronic database in three formats – visualised signals (as used in standard clinical practice), raw ECG signals or median beats. Raw signals are preferable for input for DNNs as visualised signals require digitisation, which results in a loss of signal resolution. Furthermore, raw ECG signals often consist of a continuous 10-second measurement of all recorded leads, whereas visualised signals may consist of 2.5 seconds per lead with only three

50 mm/s 10 mm/mV The effect of shifting precordial electrodes 4 m upward (blue) or downward (red) from standard 12-lead electrode positioning (black). Displayed signals were simultaneously recorded using a 64-electrode measurement set-up.

AI algorithms is yet unknown. However, as acquisition methods may differ significantly between manufacturers, the performance of algorithms are likely to depend on the type or even version of the device.35 Testing the performance of algorithms using ECGs recorded by different devices would illustrate the effect of these technical specifications on performance and generalisability.

ECG Electrodes The recorded ECG is affected by electrode position with respect to the anatomical position of the heart and displacement of electrodes may result in misdiagnosis in a clinical setting.36,37 For example, placement of limb electrodes on the trunk significantly affects the signal waveforms and lead reversal may mimic pathological conditions.38–41 Furthermore, deviations in precordial electrode positions affect QRS and T wave morphology (Figure 2). Besides the effect of cardiac electrophysiological characteristics like anisotropy, His-Purkinje anatomy, myocardial disease and cardiac anatomy on measured ECGs, cardiac position and cardiac movement also affect the ECG.42–45 Conventional clinical ECGs mostly consist of the measurement of eight independent signals; two limb leads and six precordial leads (Figure 3b). The remaining four limb leads are derived from the measured limb leads. However, body surface mapping studies identified the number of signals containing unique information up to 12 for ventricular depolarisation and up to 10 for ventricular repolarisation.46 Theoretically, to measure all information about cardiac activity from the body surface, the number of electrodes should be at least the number

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simultaneously recorded signals per 2.5 seconds (Figure 3). A median beat per lead can also be used, computed from measured raw ECG signals or digitised visualised signals. Using the median beat might reduce noise, as noise is expected to cancel out by averaging all beats. Therefore, subtle changes in cardiac activation, invisible due to noise might become distinguishable for the algorithm. The use of the median beat may allow for precise analysis of waveform shapes or serial changes between individuals but rhythm information will be lost.

Opportunities for Artificial Intelligence in Electrophysiology Enhanced Automated ECG Diagnosis An important opportunity of AI in electrophysiology is the enhanced automated diagnosis of clinical 12-lead ECGs.8,11,12,20,52–54 Adequate computerised algorithms are especially important when expert knowledge is not readily available, such as in pre-hospital care, nonspecialist departments, or facilities that have minimal resources. If high-risk patients can be identified correctly, time-to-treatment can be reduced. However, currently available computerised ECG diagnosis algorithms lack accuracy.11 Progress has been made in using DNNs to automate diagnosis or triage ECGs to improve time-to-treatment and reduce workload.19,55 Using very large data sets, DNNs can achieve high diagnostic performance and outperform cardiology residents and noncardiologists.6,19 Moreover, progress has been made in using ECG data for predictive modelling for AF in sinus rhythm ECGs or for the screening of hypertrophic cardiomyopathy.56–58

Combining Other Diagnostic Modalities with ECG-based DNN Some studies have suggested the possibility of using ECG-based DNNs with other diagnostic modalities to screen for disorders that are currently not associated with the ECG. In these applications, DNNs are thought to be able to detect subtle ECG changes. For example, when combined with large laboratory data sets, patients with hyperkalaemia could be identified, or when combined with echocardiographic results, reduced ejection fraction or aortic stenosis could be identified. The created DNNs

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AI in Electrophysiology: Opportunities and Threats identified these three disorders from the ECG with high accuracy.21,50,59 As a next step, supplementing ECG-based DNNs with body surface mapping data with a high spatial resolution (e.g. more than 12 measurement electrodes), inverse electrocardiography data or invasive electrophysiological mapping data, may result in the identification of subtle changes in the 12-lead ECG as a result of pathology.

Figure 3: Standardised Clinical Visualised Signals A

Artificial Intelligence for Invasive Electrophysiological Studies The application of AI before and during complex invasive electrophysiological procedures, such as electroanatomical mapping, is another major opportunity. By combining information from several diagnostic tools such as MRI, fluoroscopy or previous electroanatomical mapping procedures, invasive catheter ablation procedure time might be reduced through the accelerated identification of arrhythmogenic substrates. Also, new techniques such as ripple mapping may be of benefit during electroanatomical mapping studies.60 Recent studies suggest that integration of fluoroscopy and electroanatomical mapping with MRI is feasible using conventional statistical techniques or ML, whereas others suggest the use of novel anatomical mapping systems to circumvent fluoroscopy.61â&#x20AC;&#x201C;64 Furthermore, several ML algorithms have been able to identify myocardial tissue properties using electrograms in vitro.65

Ambulatory Device-based Screening for Cardiovascular Diseases One of the major current challenges in electrophysiology is the applicability of ambulatory rhythm devices in clinical practice. Several tools, such as implantable devices or smartwatch and smartphonebased devices, are becoming more widely used and continuously generate large amounts of data which would be impossible to evaluate manually.66 Arrhythmia detection algorithms based on DNNs trained on large cohorts of ambulatory patients with a single-lead plethysmography or ECG device have shown similar diagnostic performance as cardiologists or implantable loop recorders.2,3,6 Another interesting application of DNN algorithms are data from intracardiac electrograms before and during the activation of the defibrillator. Analysis of the signals before the adverse event might provide insight into the mechanism of the ventricular arrhythmia, providing the clinician with valuable insights. Continuous monitoring also provides the possibility of identifying asymptomatic cardiac arrhythmias or detecting post-surgery complications. Early detection might overcome serious adverse events and significantly improve timely personalised healthcare.6,19 A promising benefit of smartphone applications for the early detection of cardiovascular disease is in early detection of AF. As AF is a risk factor for stroke, early detection may be important to prompt adequate anticoagulant treatment.67â&#x20AC;&#x201C;69 An irregular rhythm can be accurately detected using smartphone or smartwatch-acquired ECGs. Even predicting whether a patient will develop AF in the future using smartphone-acquired ECGs recorded during sinus rhythm has been recently reported.69,70 Also, camera-based photoplethysmography recordings can be used to differentiate between irregular and regular cardiac rhythm.71,72 However, under-detection of asymptomatic AF is expected as the use of applications requires active use and people are likely to only use applications when they have a health complaint. Therefore, a non-contact method with facial photoplethysmography recordings during regular smartphone use may be an interesting option to explore.70,73,74

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10-second measurement

Median beat

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Time (s) Time (s) A: Three simultaneously recorded 2.5 second measurements and raw signals. B: A 10-second measurement and median beats of all recorded leads. Displayed signals are acquired using a General Electric Healthcare MAC 5500 ECG device.

Apart from the detection of asymptomatic AF, the prediction or early detection of ventricular arrhythmias using smartphone-based techniques are potentially clinically relevant. For example, smartphonebased monitoring of people with a known pathogenetic mutation might aid the early detection of disease onset. In some pathogenetic mutations, this may be especially relevant as sudden cardiac death can be the first manifestation of the disease. In these patients, close monitoring to prevent these adverse events by starting early treatment when subclinical signs are detected may provide clinical benefit.

Threats of Artificial Intelligence in Electrophysiology Data-driven Versus Hypothesis-driven Research Data from electronic health records are almost always retrospectively collected, leading to data-driven research, instead of hypothesis-driven research. Research questions are often formulated based on readily available data, which increases the possibility of incidental findings and spurious correlations. While correlation might be sufficient for some predictive algorithms, causal relationships remain of the utmost important to define pathophysiological relationships and ultimately for the clinical implementation of AI algorithms. Therefore, big data research is argued to be in most cases solely used to generate hypotheses and controlled clinical trials remain necessary to validate these hypotheses. When AI is used to identify novel pathophysiological phenotypes, e.g. with specific ECG features, sequential prospective studies and clinical trials are crucial.75

Input Data Adequate labelling of input data is important for supervised learning.18,76,77 Inadequate labelling of ECGs or the presence of

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Clinical Arrhythmias pacemaker artefacts, comorbidities affecting the ECG or medication affecting the rhythm or conduction, might influence the performance of DNNs.13–18 Instead of true disease characteristics, ECG changes due to clinical interventions are used by the DNN to classify ECGs. For example, a DNN using chest X-rays provided insight into long-term mortality, but the presence of a thoracic drain and inadequately labelled input data resulted in an algorithm that was unsuitable for clinical decision-making.77–80 Therefore, the critical review of computerised labels and the identification of important features used by the DNN are essential. Data extracted from ambulatory devices consist of real-time continuous monitoring data outside the hospital. As the signal acquisition is performed outside a standardised environment, signals are prone to errors. ECGs are more often exposed to noise due to motion artefacts, muscle activity artefacts, loosened or moved electrodes and alternating powerline artefacts. To accurately assess ambulatory data without the interference of artefacts, signals should be denoised or a quality control mechanism should be implemented. For both methods, noise should be accurately identified and adaptive filtering or noise qualification implemented.81–83 However, as filtering might remove information, rapid real-time quality reporting of the presence of noise in the acquired signal is thought to be beneficial. With concise instructions, users can make adjustments to reduce artefacts and the quality of the recording will improve. Different analysis requires different levels of data quality and through classification recorded data quality, the threshold for user notification can be adjusted per analysis.84,85

Generalisability and Clinical Implementation With the increasing number of studies on ML algorithms, generalisability and implementation is one of the most important challenges to overcome. Diagnostic or prognostic prediction model research, from simple logistic regression to highly sophisticated DNNs, is characterised by three phases: • Development and internal validation. • External validation and updating for other patients. • Assessment of the implementation of the model in clinical practice and its impact on patient outcomes.86,87 During internal validation, the predictive performance of the model is assessed using the development data set through train-test splitting, cross-validation or bootstrapping. Internal validation is however insufficient to test generalisability of the model in ‘similar but different’ individuals. Therefore, external validation of established models is important before clinical implementation. A model can be externally validated through temporal (same institution, later period), geographical (a different institution with a similar patient group) or domain (different patient group) validation. Finally, implementation studies, such as cluster randomised trials, before and after studies or decision-analytic modelling studies, are required to assess the effect of implementing the model in clinical care.86,87 Most studies in automated ECG prediction and diagnosis performed some type of external validation. However, no study using external validation in a different patient group or implementation study has been published so far. A study has shown similar accuracy to predict low ejection fraction from the ECG using a DNN through temporal validation as in the development study.88 A promising finding was a

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similar performance of the algorithm for different ethnic subgroups, even if the algorithm was trained on one subgroup.89 As a final step to validate this algorithm, a cluster randomised trial is currently being performed. This might provide valuable insight into the clinical usefulness of ECG-based DNNs.90 Implementation studies for algorithms using ambulatory plethysmography and ECG data are ongoing. For example, the Apple Heart Study assessed the implementation of smartphone-based AF detection.5 More than 400,000 patients who used a mobile application were included, but only 450 patients were analysed. Implementation was proven feasible as the number of false alarms was low, but the study lacks insight into the effect of smartphone-based AF detection on patient outcome. Currently, the Heart Health Study Using Digital Technology to Investigate if Early AF Diagnosis Reduces the Risk of Thromboembolic Events Like Stroke IN the Real-world Environment (HEARTLINE; NCT04276441) is randomising patients to use the smartwatch monitoring device. The need for treatment with anticoagulation of patients with device-detected subclinical AF is also being investigated.4 A final step for the successful clinical implementation of AI is to inform its users about adequate use of the algorithm. Standardised leaflets have been proposed to instruct clinicians when, and more importantly when not, to use an algorithm.91 This is particularly important if an algorithm is trained on a cohort using a specific subgroup of patients. Then, applying the model to a different population may potentially result in misdiagnosis. Therefore, describing the predictive performance in different subgroups, such as different age, sex, ethnicity and disease stage, is of utmost importance as AI algorithms are able to identify these by themselves.89,92–94 However, as most ML algorithms are still considered to be ‘black boxes’, algorithm bias might remain difficult to detect.

Interpretability Many sophisticated ML methods are considered black boxes as they have many model parameters and abstractions. This is in contrast with the more conventional statistical methods used in medical research, such as logistic regression and decision trees, where the influence of a predictor on the outcome is clear. The trade of complexity of models and interpretability for improved accuracy is important to acknowledge; with increased complexity of the network, interpretation becomes more complicated. But interpretability remains important to investigate false positives and negatives, to detect biased or overfitted models, to improve trust in new models or to use the algorithms as a feature detector.95 Within electrophysiology, few studies have investigated how the AI algorithms came to a certain result. For DNNs, three recent studies visualised individual examples using Guided Grad-CAM, a technique to show what the networks focus on. They showed that the DNN used the same segment of the ECG that a physician would use (Figure 4).19,27,96–98 Visualisation techniques may provide the ECG locations which the algorithms find important, but do not identify the specific feature. Therefore, the opportunity to identify additional ECG features remains dependent on expert opinion and analysis of the data by a clinician is still required. Visualisation techniques and their results are promising and help to increase trust in DNNs for ECG analysis, but additional work is needed to further improve the interpretability of AI algorithms in clinical practice.99,100

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AI in Electrophysiology: Opportunities and Threats

In contrast to physicians or conventional statistical methods, DNNs struggle to inform their users when they do not know and to give uncertainty measures about their predictions. Current models always output a diagnosis or prediction, even if they have not seen the input before. In a real-world setting, clinicians acknowledge uncertainty and consult colleagues or literature but a DNN always makes a prediction. Therefore, methods that incorporate uncertainty are essential before implementation of such algorithms is possible.101

Figure 4: Important Regions for the Deep Neural Network to Predict Whether an ECG is Normal, Abnormal or Acute II

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Another concerning privacy aspect is the continuous data acquisition through smartphone-based applications. In these commercial applications, data ownership and security are vulnerable. Security between smartphones and applications is heterogeneous and data may be stored on commercial and poorly secured servers. Clear regulations and policies should be in place before these applications can enter the clinical arena. Data sets contain information about medical history and treatment but may also encompass demographics, religious status or socioeconomic status. Apart from medical information, sensitive personal data might be taken into account by developed algorithms, possibly resulting in discrimination in areas such as ethnicity, gender or religion.54,108–110 As described, DNNs are black boxes wherein input data is classified. An estimate of the competency of an algorithm can be made through

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Several other ethical and legal challenges within the field of AI in healthcare are yet to be identified, such as patient privacy, poor quality algorithms, algorithm transparency and liability concerns. Data are subjected to privacy protections, confidentiality and data ownership, therefore requiring specific individual consent for use and reuse of data. However, by increasing the size of the data set, anonymisation techniques used nowadays might be inadequate and eventually result in the identification of patients.105,106 As large data sets are required for DNNs, collaboration between institutions becomes inevitable. To facilitate data exchange, platforms have been established to allow for safe and consistent data-sharing between institutions.107 However, these databases may still contain sensitive personal data.54,108 Therefore, federated learning architectures are proposed that provide data-sharing while simultaneously obviating the need to share sensitive personal data. An example of this is the anDREea Consortium (andrea-consortium.org).

C 2

reviewed by an expert.104

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Ideally, the algorithm provides results only when it reaches a high threshold of certainty, while the uncertain cases will still be reviewed by a clinician.101 For DNNs, several new techniques are available to obtain uncertainty measures, such as Bayesian deep learning, Monte Carlo dropout and ensemble learning, but these have never been applied in electrophysiological research.102 They have been applied to detect diabetic retinopathy in fundus images using DNNs, where one study showed that overall accuracy could be improved when uncertain cases were referred to a physician.103 Another study suggested that uncertainty measures were able to detect when a different type of scanner was used that the algorithm had not seen before.35 Combining uncertainty with active or online learning allows the network to learn from previously uncertain cases, which are now

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ECG leads II and V1 with a superimposed guided Grad-CAM visualisation showing regions important for the deep neural network to predict whether an ECG is normal, abnormal or acute. A and B: Normal ECGs with focus on the P wave, QRS-complex, and T wave, while correctly ignoring a premature ventricular complex. C: Abnormal ECG with a long QT interval and a focus on the beginning and end of the QT-segment. D and E: Acute ECGs with an inferior ST-segment elevation MI (D) and a focus on the ST-segment and with a junctional escape rhythm (E) and a focus on the pre-QRS-segment, where the P wave is missing. Source: van de Leur et al. 2020.19 Reproduced from the American Heart Association, Inc., by Wiley Blackwell under a Creative Commons (CC BY-NC-ND 4.0) licence.

the interpretation of DNNs and the incorporation of uncertainty measures. Traditionally, clinical practice mainly depends on the competency of a clinician. Decisions about diagnoses and treatments are based on widely accepted clinical standards and the level of competency is protected by continuous intensive medical training. In the case of adverse events, clinicians are held responsible if they deviated from standard clinical care. However, the medical liability of the DNN remains questionable. Incorrect computerised medical diagnoses or treatments result in adverse outcomes, thereby raising the question: who is accountable for a misdiagnosis based on an AI algorithm.

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Clinical Arrhythmias Table 1: Systematic Overview of Relevant Threats of AI Algorithms in Electrophysiology Domain

Key Points

Questions

Algorithm input

Subjects

Is an appropriate data source used with clear inclusion and exclusion criteria?

Data

Is the ECG data of sufficient quality? Is the quality of ambulatory data continuously assessed?

Robustness

How does the model perform? Were there a reasonable number of subjects? Were ECGs equally sampled per subject?

Overfitting and optimism

Was overfitting assessed using internal validation with train-test splitting, cross-validation or bootstrapping? Was the validation data set of sufficient size (>100 participants with the outcome)?

External validation

Are there studies that provide temporal, geographical or domain validation?

Subgroups

Is subgroup analysis provided to minimise the risk of poor performance in subgroups? Is there a bias based on ethnicity, gender or other demographic factors?

Subjects

Is the population that will use the algorithm similar to the external validation population? Is the disease prevalence similar?

Data

Is the algorithm evaluated on the used diagnostic device of a specific manufacturer? Was data standardised according to general agreements?

Implementation studies

Have implementation studies, such as RCTs or before and after studies, been performed? Does implementation of the model positively influence patient outcomes?

Interpretation and uncertainty

Are there possibilities to check the predictions of the model in clinical practice (using visualisations)? Does the model provide uncertainty measures? How does the model deal with ECG noise or electrode misplacements? Is there a clear flowchart that allows uncertain cases to be referred to a physician?

Ethical and legal

Are the ethical and legal aspects sufficiently addressed?

Algorithm performance

Algorithm implementation

RCT = randomised controlled trial.

To guide the evaluation of ML algorithms, in particular DNNs, and accompanying literature in electrophysiology, a systematic overview of all relevant threats discussed in this review is presented in Table 1.

Conclusion Many exciting opportunities arise when AI is applied to medical data, especially in cardiology and electrophysiology. New ECG features, accurate automatic ECG diagnostics and new clinical insights can be

rapidly obtained using AI technology. In the near future, AI is likely to become one of the most valuable assets in clinical practice. However, as with every technique, AI has its limitations. To ensure the correct use of AI in a clinical setting, every clinician working with AI should be able to recognise the threats, limitations and challenges of the technique. Furthermore, clinicians and data scientists should closely collaborate to ensure the creation of clinically applicable and useful AI algorithms.

Clinical Perspective • Artificial intelligence (AI) may support diagnostics and prognostics in electrophysiology by automating common clinical tasks or aiding complex tasks through the identification of subtle or new ECG features. • Within electrophysiology, automated ECG diagnostics using deep neural networks is superior to currently implemented computerised algorithms. • Before the implementation of AI algorithms in clinical practice, trust in the algorithms must be established. This trust can be achieved through improved interpretability, measurement of uncertainty and by performing external validation and feasibility studies to determine added value beyond current clinical care. • Combining data obtained from several diagnostic modalities using AI might elucidate pathophysiological mechanisms of new, rare or idiopathic cardiac diseases, aid the early detection or targeted treatment of cardiovascular diseases or allow for screening of disorders currently not associated with the ECG.

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ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Clinical Arrhythmias

Differential Diagnosis of Wide QRS Tachycardias Demosthenes G Katritsis1 and Josep Brugada2 1. Department of Cardiology, Hygeia Hospital, Athens, Greece; 2. Cardiovascular Institute, University of Barcelona, Spain

Abstract In this article, the authors discuss the differential diagnostic methods used in clinical practice to identify types of wide QRS tachycardias (QRS duration >120 ms). A correct diagnosis is critical to management, as misdiagnosis and the administration of drugs usually utilised for supraventricular tachycardia can be harmful for patients with ventricular tachycardia.

Keywords Tachycardias, supraventricular tachycardia, ventricular tachycardia Disclosure: The authors have no conflicts of interest to declare. Received: 28 April 2020 Accepted: 27 May 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):155–60. DOI: https://doi.org/10.15420/aer.2020.20 Correspondence: Demosthenes Katritsis, Hygeia Hospital, 4 Erythrou Stavrou St, Athens 15123, Greece; E: dkatrits@dgkatritsis.gr Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

The term narrow QRS tachycardia indicates individuals with a QRS duration ≤120 ms, while wide QRS tachycardia refers to tachycardia with a QRS duration >120 ms. 1 Narrow QRS complexes are due to rapid activation of the ventricles via the His–Purkinje system, suggesting that the origin of the arrhythmia is above or within the His bundle. However, early activation of the His bundle can also occur in high septal ventricular tachycardia (VT), resulting in relatively narrow QRS complexes of 110–140 ms. 2 Wide QRS tachycardias can be VT, supraventricular tachycardia (SVT) conducting with bundle branch block (BBB) aberration, or over an accessory pathway, and account for 80%, 15% and 5% of cases, respectively.3 The correct diagnosis of VT is critical to management, as misdiagnosis and the administration of drugs usually utilised for SVT can be harmful for patients in VT.4 In this article, we discuss the differential diagnostic methods encountered in clinical practice. The text is mainly based on the recently published ESC guidelines on SVT.1

Regular Tachycardias As a rule, the default diagnosis of a wide QRS tachycardia should be VT until proven otherwise. VT is defined as a tachycardia (rate >100 BPM) with three or more consecutive beats that originate in the ventricles.5,6 Differential diagnoses include (Table 1):7 • SVT with BBB. This may arise due to pre-existing BBB or the development of aberrancy during tachycardia, known as phase 3 block, which more commonly has a right bundle branch block (RBBB) pattern due to the longer refractory period of the right bundle branch. • SVT with antegrade conduction over an AP that participates in the circuit (antidromic atrioventricular re-entrant tachycardia) or is a bystander during AF, focal atrial tachycardia/flutter or atrioventricular nodal re-entrant tachycardia.

• SVT with widening of the QRS interval induced by drugs or electrolyte disturbances. Class IC and IA drugs cause usedependent slowing of conduction and class III drugs prolong refractoriness to a greater extent at the His–Purkinje tissue than in the ventricular myocardium. Both can result in atypical BBB morphologies during SVT that mimic VT. • Apical ventricular pacing, pacemaker-related endless loop tachycardia and artefacts can also mimic VT.

Electrocardiographic Differential Diagnosis If the QRS morphology is identical during sinus rhythm and tachycardia, then VT is unlikely. However, bundle branch re-entrant VTs and high septal VTs exiting close to the conduction system can have similar morphologies to sinus rhythm. The presence of a contralateral BBB pattern in sinus rhythm is more indicative of VT.

Atrioventricular Dissociation The presence of either atrioventricular dissociation or capture/ fusion beats in the 12-lead ECG during tachycardia are key diagnostic features of VT (Table 2). Atrioventricular dissociation may be difficult to recognise because P waves are often hidden by wide QRS and T waves during a wide QRS tachycardia. P waves are usually more prominent in inferior leads and modified chest lead placement (Lewis lead). 3 The relation between atrial and ventricular events is 1:1 or greater, i.e. more atrial than ventricular beats, in most VTs. Atrioventricular nodal re-entrant tachycardia can be associated with 2:1 conduction, but this is rare.8 Although VA conduction an be found in up to 50% of patients with VT and a 1:1 relation is possible, most VTs have a relation of <1:1, i.e. more QRS complexes than P waves.

QRS Duration A QRS duration >140 ms with RBBB or >160 ms with left bundle branch block (LBBB) pattern suggests VT. These criteria are not

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Clinical Arrhythmias Table 1: Differential Diagnosis of Wide QRS Tachycardias Wide QRS (>120 ms) Tachycardias Regular: • Ventricular tachycardia/flutter • Ventricular paced rhythm • Antidromic AV re-entrant tachycardia • Supraventricular tachycardias with aberration/bundle branch block (pre-existing or rate-dependent during tachycardia) • Atrial or junctional tachycardia with pre-excitation/bystander accessory pathway • Supraventricular tachycardia with QRS widening due to electrolyte disturbance or antiarrhythmic drugs Irregular: • AF or atrial flutter or focal atrial tachycardia with varying block conducted with aberration • Antidromic AV re-entrant tachycardia due to a nodo-ventricular/fascicular accessory pathway with variable VA conduction • Pre-excited AF • Polymorphic VT • Torsades de pointes • VF Occasionally, AF with very fast ventricular response may apparently resemble a regular narrow-QRS tachycardia. AV = atrioventricular; VA = ventriculoarterial; VT = ventricular tachycardia. Source: Brugada et al. 2019.1 Reproduced with permission from Oxford University Press.

Table 2: ECG Criteria in the 2019 European Society of Cardiology Guidelines Suggest Ventricular Rather Than Supraventricular Tachycardia in Wide Complex Tachycardia Atrioventricular dissociation

Ventricular rate > atrial rate

Fusion/capture beats

Different QRS morphology from that of tachycardia

Chest lead negative concordance

All precordial chest leads negative

RS in precordial leads

• Absence of RS in precordial leads • RS >100 ms in any lead*

QRS complex in aVR

• Initial R wave • Initial R or Q wave >40 ms • Presence of a notch of predominantly negative complex

QRS axis −90° to ± 180°

Both in the presence of right and left bundle branch block morphology

R wave peak time in lead II

R wave peak time ≥50 ms

Right bundle branch block morphology

Lead V1: Monophasic R, rsR’, biphasic qR complex, broad R (>40 ms), and a double-peaked R wave with the left peak taller than the right (the so-called rabbit ear sign) Lead V6: R:S ratio <1 (rS, QS patterns)

Left bundle branch block morphology

Lead V1: Broad R wave, slurred or notched down stroke of the S wave and delayed nadir of S wave Lead V6: Q or QS wave

*RS = beginning of R to deepest part of S. Source: Brugada et al. 2019.1 Reproduced with permission from Oxford University Press.

helpful for differentiating VT from SVT in specific settings, such as pre-excited SVT or when class IC or class IA antiarrhythmic drugs are administered.9

QRS Axis Since VT circuits, especially post MI or in cardiomyopathies, frequently lie outside the normal His–Purkinje network, significant axis shifts are likely to occur that enable diagnosis. In SVT patients with aberrancy, the QRS axis is confined between −60° and +120°. Extreme axis deviation (from −90° to ±180°) is strongly indicative of VT in the presence of RBBB and LBBB.7

Chest Lead Concordance The presence of negative chest lead concordance (i.e. when all QRS complexes in leads V1–V6 are negative) is almost diagnostic of VT, with a specificity of >90%, but is only present in 20% of VTs (Figure 1). Positive concordance can be indicative of VT or an antidromic tachycardia utilising a left posterior or left lateral accessory pathway.10

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Right Bundle Branch Block Morphology In the V1 lead, typical RBBB aberrancy has a small initial r’, since in RBBB the high septum is activated primarily from the left septal bundle. This means that rSR’, rSr’ or rR’ patterns are evident in lead V1. However, in VT the activation wavefront progresses from the LV to the right precordial V1 lead in such a way that a prominent R wave (monophasic R, Rsr’, biphasic qR complex or broad R >40 ms) will more commonly be seen.11 Additionally, a double-peaked R wave (M pattern) in lead V1 favours VT if the left peak is taller than the right peak – the so-called ‘rabbit ear’ sign. A taller right rabbit ear characterises RBBB aberrancy but does not exclude VT. In the V6 lead, a small amount of normal right ventricular voltage is directed away from V6. Since this is a small vector in RBBB aberrancy, the R:S ratio is >1. In VT, all of the right and some of the left ventricular voltage is directed away from V6, leading to an R:S ratio <1 (rS and QS patterns). An RBBB morphology with an R:S ratio <1 in V6 is seen rarely in SVT with aberrancy, mainly when the patient has a left axis deviation during sinus rhythm.

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Differential Diagnosis of Wide QRS Tachycardias Figure 1: Measurement of the R-wave Peak Time in Lead II

Figure 3: Differential Diagnosis of Wide QRS Tachycardia using the Vereckei et al. Algorithm

Lead II aVR lead

80 ms

R-wave peak time ≥50 ms

Initial R wave? No

Yes

Supraventricular tachycardia

Yes Initial R or Q wave >40 ms?

Ventricular tachycardia

R-wave peak time measured from the isoelectric line to the point of first change in polarity, was >50 ms (80 ms, see arrows on ECG). Source: Katritsis et al. 2017.28 Reproduced with permission from Oxford University Press.

Notch on the descending limb of a negative onset and predominantly negative QRS?

Figure 2: Differential Diagnosis of Wide QRS Tachycardia using the Brugada et al. Algorithm

Yes

vi/vt≤1 Yes

RS interval (beginning of the R wave to the deepest part of the S wave) >100ms in any precordial lead? No

Yes

Absence of RS in all precordial leads? No

Yes

Ventricular tachycardia

Supraventricular tachycardia

aVR

Yes

aVR

Atrioventricular dissociation? vi = 0.15

Yes No

Apply the following conventional criteria

I II LBBB morphology

RBBB morphology

III R

V1 Monophasic R RSr

V1 or V6 Triphasic QRS

V1 or V2 R>30 ms or >60 ms to nadir S, or notched S

SVT

L F

aVL

vi = 0.4

vt = 0.2 vi/vt > 1

SVT

aVL

V1 V2

vt = 0.6 vi/vt < 1

aVF

V4 aVF

V3 V4 V5

The RS interval (A), enlarged in (B), measures 160 ms in lead V4 and 70 ms in lead V6. Thus, the longest RS interval is >100 ms and diagnostic of ventricular tachycardia. LBBB = left bundle branch block; RBBB = right bundle branch block; SVT = supraventricular tachycardia; VT = ventricular tachycardia. Source: Katritsis et al. 2017.28 Reproduced with permission from Oxford University Press.

Differentiating fascicular VT from SVT with bifascicular block (RBBB and left anterior hemiblock) is very challenging. Features that indicate SVT in this context include QRS >140 ms, r’ in V1, overall negative QRS in aVR and R/S ratio >1 in V6.

ECGs: The vertical lines on the aVR lead show the onset and end of the QRS complex. Crosses indicate the first and last 40 ms of the chosen QRS complex. The ventricular activation velocity ratio (vi /vt) is calculated by measuring the vertical excursion in mV recorded on the ECG during the initial (vi ) and terminal (vt ) 40 ms of the QRS complex. Left: During the initial 40 ms of the QRS, the impulse travelled 0.15 mV vertically; therefore, vi=0.15. During the terminal 40 ms, the impulse travelled 0.6 mV vertically; therefore, vt=0.6. Thus, vi /vt <1 yields a diagnosis of ventricular tachycardia. Right: vi=0.4 and vt=0.2; thus, vi /vt >1 suggests a diagnosis of supraventricular tachycardia. Source: Katritsis et al. 2017.28 Reproduced with permission from Oxford University Press.

In the V6 lead, no Q wave is present in the lateral precordial leads in true LBBB. The presence of any Q or QS wave in lead V6 favours VT, indicating that the activation wavefront is moving away from the left ventricular apical site. A number of algorithms have been developed to differentiate VT from SVT.12–14 The most established are the Brugada algorithm and the Vereckei algorithm, which utilises a single aVR lead.12,13,15

Left Bundle Branch Block Morphology In the V1 lead, the presence of broad R wave, slurred or notched downstroke of the S wave and delayed nadir of the S wave are strong predictors of VT for the same reasons as stated for RBBB.11

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RS Interval in the Precordial Leads The absence of RS complex in the precordial leads, i.e. only R and S complexes are seen on ECG, is only found in VTs (Figure 2). An RS

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Clinical Arrhythmias Figure 4: Twelve-lead Electrocardiogram Morphology of Different Sites of Idiopathic Ventricular Tachycardia Origin

Epicardial VT I II III Outflow tract VT

aVR

aVL

aVF

III

aVR

aVL

aVF

GCV

AIV

V4 V5 V6 RVOT

RCC

LCC

R-L Com

AMC

Fasicular VT Perivalvular VT I I

III

aVR

Intracavity VT

aVR

aVL

aVF

III

aVR

aVL

aVF

V2 TV

aVF V1 V2 V3 V4 V5 V6 LPF

LAF

V4 V5 V6 Moderator Band

APM

PPM

AIV = anterior inter-ventricular vein; AMC = aortomitral continuity; APM = anterior PAP; GCV = greater cardiac vein; LAF = left anterior fascicle; LCC = left coronary cusp; LPF = left posterior fascicle; MV = mitral annulus; PAP = papillary muscle; PPM = posterior PAP; RCC = right coronary cusp; R–L com = right–left coronary cusp commissure; RVOT = right ventricular outflow tract; TV = tricuspid annulus. Source: Tanawuttiwat et al. 2016.24 Reproduced with permission from Oxford University Press.

complex is found in all SVTs and in 74% of VTs. No SVT with aberrant conduction has an interval >100 ms between the onset of the R wave and the deepest part of the S wave at its longest duration, irrespective of the morphology of the tachycardia.15 About half of VTs have an RS interval ≤100 ms and the other half have an RS interval >100 ms. The Brugada et al. algorithm has a sensitivity and specificity of 98.7% and 96.5%, respectively.12

QRS Complex in the aVR Lead During sinus rhythm and SVT, the wavefront of depolarisation moves away from the aVR lead, yielding a negative QRS complex in the aVR lead with few exceptions, e.g. inferior myocardial infarction. In contrast, the presence of an initial R wave (Rs complex) in the aVR lead suggests VT (Figure 3). The Vereckei et al. algorithm has a 91.5% overall accuracy in the diagnosis of VT.13

R-wave Peak Time at Lead II ≥50 ms This criterion has the potential advantage that lead II is easy to obtain and is almost always present on ECG rhythm strips recorded in different settings, e.g. ECG monitoring in emergency rooms and intensive care units. In lead II an R-wave peak time ≥50 ms, independent of whether the complex is positive or negative, has been reported to have a sensitivity of 93% and specificity of 99% for identifying VT (Figure 1), but these results were not verified in the first large external application of this criterion.10,16

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All criteria have limitations. Several conditions, such as bundle branch re-entrant tachycardia, fascicular VT, VT with exit site close to the His– Purkinje system and wide-QRS tachycardia occurring during antiarrhythmic drug treatment, are difficult to diagnose using the morphological criteria mentioned. This is most pronounced in VT originating from septal sites, particularly Purkinje sites and the septal outflow tract regions.17 Left posterior fascicular VT, the most common form of idiopathic left ventricular VT, is frequently misdiagnosed as SVT with RBBB and left anterior hemiblock aberration.2 Differentiation between VT and antidromic atrioventricular re-entrant tachycardia is extremely difficult because the QRS morphology in antidromic atrioventricular re-entrant tachycardia is similar to that of a VT originating at the insertion of the accessory pathway in the ventricular myocardium. An algorithm has been derived for differential diagnosis based on the analysis of 267 wide-QRS tachycardias, consisting of VT and antidromic atrioventricular re-entrant tachycardia. The criteria derived from this analysis were found to have a sensitivity of 75% and specificity of 100% and the algorithm was validated in another study but experience is still limited.18,19 Several independent studies have found that various ECG-based methods have specificities of 40–80% and accuracies of ~75%.2,10,19–22 A similar diagnostic accuracy of ~75% would be achieved effortlessly by considering every wide QRS tachycardia to be a VT because only

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Differential Diagnosis of Wide QRS Tachycardias Figure 5: Localisation of the Origin of Scar-related Ventricular Tachycardia A

I aVF− II 1. Short axis location Maximal QRS amplitude limb leads

2. Longitudinal axis location V3–V4 polarity

III

aVR+

aVF− II−

III−

aVR+

2 8

I− 3 aVL−

V4+

I+

16 15 10

V3+

V4+

4 III+

Mid

V3−

aVL−

aVR−

Apical

V4−

II+

I+

16 15 10

4 III+

aVR− II+

aVF+

V3 Steps: V4

aVF+

6 12

13 14

V2 V3−

7 8

I−

AVF

aVL+

1 2

AVL

V3+

Basal

13 14

AVR aVL+

III−

II−

1. Highest voltage magnitude: −III 2. Adjacent lead with higher magnitude: −aVF 3. Polarity V3 and V4: +/+

V5 V6 10 mm/mV 25 mm

Left panel: QRS axis–based algorithm showing the 17-segment model from the American Heart Association superimposed on a representation of the QRS axis and all the limb leads. Steps to identify the segment of origin of a ventricular arrhythmia are as follows. A: Identify the limb lead with the highest voltage (positive or negative). If in lead I, II or III, analyse the adjacent leads. The adjacent limb lead with higher voltage will determine the group of segments likely to be the site of origin. B: Identify the positivity or negativity of precordial leads V3 and V4; concordance indicates a basal or apical origin, respectively. Other combinations indicate a medial origin. Right panel: Example of the application of the QRS axis–based algorithm. C: An ECG of ventricular tachycardia. D: The application of the QRS axis-based graphical algorithm. In the ECG, the lead with the highest voltage is III2. Applying step 1, the segment the ventricular tachycardia originates from is one of the sections in the red circle. Analysing voltage in the adjacent leads reveals that aVF2 has a higher voltage than aVL1 and the origin is therefore in a segment within the blue circle. Application of step 2 indicates the ventricular tachycardia has a basal origin, as leads V3 and V4 are both more positive than negative. The final segment selected by the algorithm is 4 (green circle). Source: Andreu et al. 2018.25 Reproduced with permission from Elsevier.

25–30% are SVTs. Emerging approaches to integrate these algorithms to provide more accurate scoring systems are being evaluated.23 Figure 4 presents the ECG morphology of idiopathic ventricular tachycardia with different sites of origin24 and Figure 5 demonstrates localisation of the origin of scar-related VT.25

Electrophysiology Study On certain occasions, such as tachycardias with borderline QRS duration and/or in the absence of atrioventricular dissociation, an electrophysiology study is necessary for diagnosis.26

Irregular Tachycardias An irregular ventricular rhythm most commonly indicates AF, multifocal atrial tachycardia or focal atrial tachycardia/atrial flutter with variable atrioventricular conduction, and may occur in the context of both narrow and broad QRS complexes. When AF is associated with rapid

Brugada J, Katritsis D, Arbelo E, et al. 2019 ESC guidelines for the management of supraventricular tachycardias. The Task Force for the management of patients with supraventricular tachycardia of the European Society of Cardiology (ECS). Eur Heart J 2019;41:655–720. https://doi.org/10.1093/eurheartj/ ehz467; PMID: 31504425. Michowitz Y, Tovia-Brodie O, Heusler I, et al. Differentiating the QRS morphology of posterior fascicular ventricular tachycardia from right bundle branch block and left anterior hemiblock aberrancy. Circ Arrhythm Electrophysiol 2017;10:e005074. https://doi.org/10.1161/CIRCEP.117.005074; PMID: 28899954. Alzand BSN and Crijns HJGM. Diagnostic criteria of broad QRS complex tachycardia: Decades of evolution. Europace 2011;13:465–72. https://doi.org/10.1093/europace/euq430; PMID: 21131372.

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ventricular rates, the irregularity of this ventricular response is less easily detected and can be misdiagnosed as a regular SVT.16 If the atrial rate exceeds the ventricular rate, then atrial flutter or atrial tachycardia (focal or multifocal) is usually present. Polymorphic VT and, rarely, monomorphic VT may also be irregular. Occasionally, a junctional, nonre-entrant tachycardia may have a variable rate. The differential diagnosis of an irregular wide QRS tachycardia is either pre-excited AF or polymorphic VT or atrial arrhythmia with variable block in the context of aberrancy. Pre-excited AF manifests as irregularity, varying QRS morphology and rapid ventricular rate owing to the short RP of the accessory pathway. The changing QRS morphology results from varying degrees of fusion due to activation over both the accessory pathway and the atrioventricular node (or over two accessory pathways) which also results in variation in the width of the delta wave. The ventricular rate tends to be higher than in those with non-pre-excited AF.28

Stewart RB, Bardy GH, Greene H. Wide complex tachycardia: misdiagnosis and outcome after emergent therapy. Ann Inten Med 1986;104:766–71. https://doi.org/10.7326/0003-4819-1046-766; PMID: 3706928. Priori SG, Blomstrom-Lundqvist C, Mazzanti A, et al. 2015 ESC guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: the Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC). Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC). Eur Heart J 2015;36:2793–867. https://doi.org/10.1093/ eurheartj/ehv316; PMID: 26320108. Al-Khatib SM, Stevenson WG, Ackerman MJ, et al. 2017 AHA/ ACC/HRS guideline for management of patients with ventricular arrhythmias and the prevention of sudden

cardiac death: a report of the American College of Cardiology/ American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. Heart Rhythm 2017;15:e190–252. https://doi.org/10.1016/j. hrthm.2017.10.035; PMID: 29097320. Wellens HJJ. Ventricular tachycardia: diagnosis of broad QRS complex tachycardia. Heart 2001;86:579–85. https://doi. org/10.1136/heart.86.5.579; PMID: 11602560. Willems S, Shenasa M, Borggrefe M, et al. Atrioventricular nodal reentry tachycardia: electrophysiologic comparisons in patients with and without 2:1 infra-His block. Clin Cardiol 1993;16:883–8. https://doi.org/10.1002/clc.4960161209; PMID: 8168273. Ranger S, Talajic M, Lemery R, et al. Kinetics of use-dependent ventricular conduction slowing by antiarrhythmic drugs in humans. Circulation 1991;83:1987–94. https://doi.

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Clinical Arrhythmias org/10.1161/01.CIR.83.6.1987; PMID: 2040051. 10. Jastrzebski M, Kukla P, Czarnecka D, et al. Comparison of five electrocardiographic methods for differentiation of wide QRScomplex tachycardias. Europace 2012;14:1165–71. https://doi. org/10.1093/europace/eus015; PMID: 22333239. 11. Kindwall KE, Brown J, Josephson ME. Electrocardiographic criteria for ventricular tachycardia in wide complex left bundle branch block morphology tachycardias. Am J Cardiol 1988;61:1279–83. https://doi.org/10.1016/00029149(88)91169-1; PMID: 3376886. 12. Brugada P, Brugada J, Mont L, et al. A new approach to the differential diagnosis of a regular tachycardia with a wide QRS complex. Circulation 1991;83:1649–59. https://doi. org/10.1161/01.CIR.83.5.1649; PMID: 2022022. 13. Vereckei A, Duray G, Szénási G, et al. New algorithm using only lead aVR for differential diagnosis of wide QRS complex tachycardia. Heart Rhythm 2008;5:89–98. https://doi. org/10.1016/j.hrthm.2007.09.020; PMID: 18180024. 14. Pava LF, Perafán P, Badiel M, et al. R-wave peak time at DII: a new criterion for differentiating between wide complex QRS tachycardias. Heart Rhythm 2010;7:922–6. https://doi. org/10.1016/j.hrthm.2010.03.001; PMID: 20215043. 15. Katritsis DG, Boriani G, Cosio FG, et al. European Heart Rhythm Association (EHRA) consensus document on the management of supraventricular arrhythmias, endorsed by Heart Rhythm Society (HRS), Asia-Pacific Heart Rhythm Society (APHRS), and Sociedad Latinoamericana de Estimulación Cardiaca y Electrofisiologia (SOLAECE). Eur Heart J 2018;39:1442–5. https:// doi.org/10.1093/eurheartj/ehw455; PMID: 28756499. 16. Knight BP, Zivin A, Souza J, et al. Use of adenosine in patients

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ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Clinical Arrhythmias

Rhythm Control in Heart Failure Patients with Atrial Fibrillation William Eysenck and Magdi Saba St George’s, University of London, London, UK

Abstract AF and heart failure (HF) commonly coexist. Left atrial ablation is an effective treatment to maintain sinus rhythm (SR) in patients with AF. Recent evidence suggests that the use of ablation for AF in patients with HF is associated with an improved left ventricular ejection fraction and lower death and HF hospitalisation rates. We performed a systematic search of world literature to analyse the association in more detail and to assess the utility of AF ablation as a non-pharmacological tool in the treatment of patients with concomitant HF.

Keywords AF, heart failure, rhythm control, rate control, cardiac ablation Disclosure: The authors have no conflicts of interest to declare. Received: 22 May 2020 Accepted: 24 August 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):161–6. DOI: https://doi.org/10.15420/aer.2020.23 Correspondence: William Eysenck, St George’s University Hospitals NHS Foundation Trust, Blackshaw Rd, Tooting, London SW17 0QT, UK. E: william.eysenck@nhs.net Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Sir James Mackenzie, famous for describing the first mechanistic insights into AF in 1902 using his polygraph, also reported that AF was present in 80–90% of patients who had congestive heart failure (HF) in 1920.1 Today, the conditions are the two ‘epidemics’ of cardiovascular disease.2 They are dominating cardiovascular care and, with increasing longevity, they will become more prevalent and place an even greater burden upon healthcare resources over the coming decades.3, 4 The conditions are inextricably linked in a vicious cycle, with HF promoting the development of AF and vice versa. In addition, each increases the morbidity and mortality associated with the other.5 Despite good progress in the management of AF-related symptoms, there are limited data to compare the benefits of different treatments and international guidelines advocate multiple therapeutic options.6 Traditionally, AF rhythm control involves a combination of antiarrhythmic medical therapy and direct current cardioversion (DCCV). Partly because of the inefficacy of these therapies the ‘rate versus rhythm’ debate has been intense in the aftermath of trials showing that, compared to a rate control strategy, a rhythm control strategy does not reduce mortality or morbidity and is more costly and inconvenient.7, 8 More recently, multiple studies have reported improvements in ‘soft’ end points with catheter ablation while two trials – Catheter Ablation vs Anti-arrhythmic Drug Therapy for Atrial Fibrillation Trial (CABANA; NCT00911508) and Catheter Ablation vs Standard Conventional Treatment in Patients With LV Dysfunction and AF (CASTLE-AF) – have reignited the debate as to whether modern rhythm control therapy can improve prognosis in patients with AF. This paper is a state-of-the-art review analysing world literature accessed via detailed literature searches utilising PubMed, Web of

Science and Scopus to establish the connection between AF and HF in detail and to determine the impact of AF rhythm control on patients with coexisting HF.

Direct Current Cardioversion for AF and Left Ventricular Performance In 1962, Lown described electrical cardioversion of AF.9 He later won the Nobel Prize for his nuclear weapon non-proliferation work.10 Electrical cardioversion is indicated for patients with AF associated with significant symptoms or as part of a long-term rhythm control strategy. The efficacy and immediacy of DCCV in restoring SR provides valuable insight into the potential benefit of rhythm control on cardiac performance. Kieny et al. demonstrated that, after successful cardioversion in persistent AF patients with dilated cardiomyopathy, left ventricular ejection fraction (LVEF) improved from 32.1% ±€5.3% to 52.9 ±€9.7%; p<0.001.11 Wall et al. demonstrated an improvement in LVEF of 14.2% in patients with impaired LV function following successful cardioversion (n=108; 95% CI [11.0%–17.4%]; p<0.0001). Furthermore, the benefit was more significant the lower the LVEF. The subgroup analysis of moderately reduced ejection fraction (HFmrEF) showed a mean improvement of 4.24% (n=50; 95% CI [0.3–8.2%]; p=0.03) and the subgroup analysis of reduced ejection fraction (HFrEF) showed a mean improvement of 23.0% (n=58; 95% CI [19.4–26.6%]; p<0.0001). DCCV successfully restores SR in the majority of patients who undergo the procedure with quoted success rates at the time of the procedure of the order of 85%.12 However, it is widely accepted that DCCV has limited long-term success rate with only 30–40% of patients remaining in SR at the end of 1 year.13 Restoration of SR with

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Clinical Arrhythmias DCCV can improve AF-related symptoms, LVEF, exercise capacity and HF symptoms.14,15 Given the greater efficacy of AF ablation and antiarrhythmic drug (AAD) therapy in maintaining SR, it is logical to hypothesise a more substantial role for these interventions in patients with coexisting HF and AF. Despite this, the only indication in international guidelines for catheter and surgical AF ablation (including concomitant open and closed procedures and standalone) remains symptom relief.16

Antiarrhythmic Medication for AF in Heart Failure Two landmark studies, each with >1,000 patients, have assessed the efficacy of pharmacological rhythm control in patients with concomitant AF and HF (AF-CHF) with HFrEF.17 In the Danish Investigators of Arrhythmia and Mortality on Dofetilide in Congestive Heart Failure (DIAMOND-CHF) trial, 1,518 patients were randomised to receive either dofetilide (n=762) or placebo (n=758). At the conclusion of the trial (12 months follow-up), 65% of patients in the dofetilide arm were in SR versus 30% of patients in the placebo arm. There was no difference in mortality between the two groups, but the dofetilide arm had lower rates of HF hospitalisation than the placebo group.18 In the AF-CHF trial, there was no difference in cardiovascular death when comparing a rate versus rhythm-control strategy with antiarrhythmic medications in 1,376 patients with AF and HFrEF and New York Heart Association (NYHA) classes II–IV (HR 1.06; 95% CI [0.86–1.30]; p=0.59), with similar findings for all-cause mortality and worsening HF.19 A possible explanation for these neutral outcomes is the difficulty in achieving and maintaining SR in patients with HF. In the rhythm control arm of AF-CHF, although 82% or participants were taking amiodarone, 58% had at least one episode of AF during the trial.19 In addition, the potential benefit of SR maintenance with respect to mortality may have been neutralised by harmful effects of AADs.17

Benefits of Rate Control for AF in Heart Failure A poor rate control resulting in fast ventricular response has been suspected as one of the major determinants of HF in AF patients. Impaired cardiac function can be reversed after restoration of SR and good ventricular rate control achieved as well by using either antiarrhythmic drugs or by atrioventricular (AV) node ablation and pacemaker implantation.2 While the benefit of cardiac resynchronisation therapy (CRT) is established in symptomatic HF patients in SR with LVEF ≤35% and QRS duration of ≥120 ms, its role in patients with coexistent HF and AF is less well defined.20,21 CRT with AV node ablation provides robust rate control and improved ventricular synchrony in AF and requires attention. Three studies have evaluated the impact of AV node ablation on LVEF in 346 CRT-AF patients.22–24 The mean increase in LVEF was 10.3% (95% CI [6.4%–14.2%]) in patients receiving a CRT device combined with AV node ablation. These data suggest an important role for rate control of AF in improving outcomes in HF patients.

Catheter Ablation for AF in Heart Failure The first data on the impact of curative catheter ablation for AF in HF patients was reported by Hsu et al. in 2004.25 The authors demonstrated that LVEF significantly increased after AF ablation with the greatest

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improvement within the first 3 months after the procedure. Interestingly, LVEF increased in most of the patients irrespective of whether ventricular rates were poor or well-controlled before ablation, indicating the existence of other factors than a fast ventricular rate for the development of AF-CHF. In the Comparison of Pulmonary Vein Isolation Versus AV Nodal Ablation With Biventricular Pacing for Patients With Atrial Fibrillation With Congestive Heart Failure (PABA CHF; NCT00599976) study, 41 patients with drug-resistant AF were randomly assigned to pulmonary vein isolation (PVI) and 40 patients to undergo AV node ablation combined with biventricular pacing.26 At 6 months, patients who had undergone PVI had a higher LVEF than those who had received AV node ablation and biventricular pacing (35% versus 28%; p<0.011). Patients undergoing the rhythm control procedure also had better 6-minute walk distance (340 m versus 297 m; p<0.001) than those in the ‘ablate and pace’ strategy. In patients undergoing PVI, 71% remained in SR at 6 months. AV node ablation with biventricular pacing is a robust form of the rate-control strategy and of rate regularisation. PABA CHF showed that PVI, compared to the best possible rate-control and rate-regularisation strategy, provides superior morphological and functional improvements. Potential explanations for LVEF improvement might be the improvement of atrial contractility, maintenance of atrioventricular synchrony, as well as the prevention of high ventricular rates.27

Importance of Sinus Rhythm A number of recent trials have suggested that SR following AF ablation is associated with improved outcomes in patients with AF.28 Substantial data demonstrate that restoration of SR leads to an improvement in LVEF in AF patients (Table 1).29 Regardless of aetiology, LV systolic dysfunction and HF are associated with a higher risk of death.30 The majority of AF ablation trials use freedom from AF and restoration of SR as their primary endpoints, with procedural success rates of 50–60% after a single procedure and 80–85% after repeat procedures.31 Therefore, it is logical to postulate that, in restoring SR, a successful AF ablation may not only improve LVEF but also reduce the excess mortality associated with concomitant HF. In studies of catheter ablation of AF, restoration of SR is associated with significant improvements in LVEF, with an 11% increase on average.32 In addition, patients with AF and HF who spend a higher proportion of time in SR experience less severe functional impairment (NYHA class III symptoms in 27 versus 35%; p<0.0001).33

Myocardial Fibrosis in AF and Heart Failure Atrial fibrosis leads to structural and functional impairment of the left atrium and persistence of AF, and is associated with the development of AF-HF.34,35 Mild pre-ablation left atrial structural remodelling by delayed enhancement MRI (DEMRI) predicts favourable structural and functional reverse remodelling and long-term success after catheter ablation of AF, irrespective of the paroxysmal or persistent nature of AF.34 Despite extensive research addressing the interplay between changes in the atria and AF, relatively few studies provide histological evaluation of the ventricle in patients with AF.36 However, it appears to have a crucial role in the AF-CHF interaction. Ventricular fibrosis may occur secondary to AF as a consequence of rapid ventricular rates, the

ARRHYTHMIA & ELECTROPHYSIOLOGY REVIEW

Rhythm Control in AF-CHF Table 1: Summary of Randomised Trials of Catheter Ablation of Atrial Fibrillation in Patients with Heart Failure Sample size Age NICM Comparator LVEF Follow-up SingleMultiLVEF Other comments (number of (years) (%) arm (%) (months) procedure procedure improvement patients in success (%) success (%) (%) ablation arm) Khan et al. 200827

81 (41)

AV nodal ablation and BIV pacing

Improved 6MHW and Minnesota score

MacDonald 41 (22) et al. 201169

Medical rate control

No difference versus rate control, high complication rate

Jones 52 (26) et al. 201370

Medical rate control

Minnesota score, BNP and peak oxygen consumption improved

Hunter 366 (67) et al. 201471

Medical rate control

Minnesota score and peak oxygen consumption improved

Di Biase 203 (102) et al. 201672

Amiodarone

–

1.4 procedures per patient, 6MHW, Minnesota score and hospitalisation and death rates improved by ablation

6MHW: 6-minute hall walk; AV: atrioventricular; BIV: biventricular; BNP: brain natriuretic peptide; LVEF: left ventricular ejection fraction; NICM: nonischaemic cardiomyopathy. Source: Verma et al. 2017.2 Reproduced with permission from Wolters Kluwer Health.

irregularity of ventricular contraction or activation of the renin– angiotensin–aldosterone system.35,37,38 Myocardial interstitial fibrosis contributes to left ventricular dysfunction leading to the development of HF.39 Successful catheter ablation has been shown to result in reverse remodelling and a regression of diffuse fibrosis in AF-mediated cardiomyopathy providing the pathophysiological explanation for the benefit of ablation in AF-CHF patients.40 Cardiac MRI offers noninvasive assessment of atrial injury and recovery of active atrial function following AF ablation because of its ability to visualise all segments of the atrial wall during the cardiac cycle.41 Catheter ablation can be associated with sustained atrial dysfunction owing to to ablation-related scarring. Previous studies have demonstrated that the difference between electroanatomic mapping (EAM) ablated area and LGE-MRI scar area was associated with higher AF recurrence after ablation.42 Despite the aforementioned benefits of catheter ablation in AF-CHF, repeat ablation could be associated with more ablation-related scarring and worse outcomes.43,44 This suggests timely treatment of arrhythmia-mediated cardiomyopathy may minimise irreversible ventricular remodelling if SR is restored and multiple AF ablation procedures should be avoided.

Cardiopulmonary Exercise Testing in AF and Sinus Rhythm Cardiopulmonary exercise testing (CPET) is an important tool to evaluate exercise capacity and predict outcomes in patients with HF.45 It provides an assessment of the integrative exercise responses involving the pulmonary, cardiovascular and skeletal muscle systems, which are not adequately reflected through the measurement of individual organ system function.45 Peak oxygen uptake (VO2 peak) is an important, reproducible facet of exercise performance and has been shown to have high prognostic value in cardiac patients and healthy individuals. VO2 peak is determined by cellular oxygen demand and equates to the maximal rate of oxygen transport. Significant increases in VO2 peak in SR have been demonstrated on

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CPET in patients who have undergone AF ablation.46 These findings imply that an improvement in haemodynamics in SR improves the rate of oxygen transport and, ultimately, this has the potential to improve prognosis. In addition, VO2 peak is a strong prognostic indicator in chronic HF and is a criterion variable for consideration of cardiac transplantation in such patients.47,48 Among patients with chronic systolic HF, even a modest increase in peak VO2 peak over 3 months has been associated with more favourable outcomes, highlighting the importance of CPET as an investigative tool; it also provides an insight into the favourable haemodynamic effects of restoring SR with an ablation procedure.49

Sleep Studies and Rhythm Control Another condition strongly associated with AF is sleep-disordered breathing (SDB). Perhaps the most straightforward explanation for the association is that patients with AF and SDB share a number of risk factors and comorbidities, including age, male sex, hypertension, HF and coronary artery disease. More evidence is emerging of a true physiological connection.50,51 Patients with obstructive sleep apnoea (OSA) have >30% greater risk of AF recurrence after catheter ablation than those without.52–54 However, the efficacy of catheter ablation for AF is similar in patients without obstructive sleep apnoea and those with this condition who are on continuous positive airway pressure treatment.55,56 In an animal model, obesity and acute obstructive apnoea have been shown to interact to promote AF.57 OSA is associated with repetitive forced inspiration against a closed airway which can result in negative intrathoracic pressure leading to an increase in cardiac afterload, larger atrial size and higher wall stress, resulting in atrial remodelling, which predisposes patients to arrhythmia.58 Further recent studies have demonstrated a reduction in nocturnal respiratory events (apnoeas and hypopnoeas) and a reversal of sleep-

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Clinical Arrhythmias disordered breathing with restoration of SR using both DCCV and AF ablation procedures at short-term follow-up.55,56 Improving haemodynamic status and cardiac function with restoration of SR could reduce fluid displacement from the lower limbs to the neck region of the body, a key mechanism in the pathogenesis of OSA.59–61 The hazard of mortality in sleep apnoea increases with apnoea severity, highlighting the potential importance of these findings and providing a further, different angle to hypotheses supporting a mortality benefit of SR in patients with AF.62

likely that these factors are the drivers for the reduced mortality observed with AF ablation in the recent CASTLE-AF study.

AF Ablation and Mortality in Heart Failure

Finally, given the importance of restoration and maintenance of SR following ablation, we propose that AF ablation trials should use stringent heart rhythm monitoring, ideally with implanted devices, allowing monitoring of every heartbeat to document the true impact of ablation on heart rhythm. Long-term monitoring with an implanted device allows for determination of AF pattern, number of discrete episodes and AF burden, providing a wealth of information regarding a patient’s AF.

A number of studies postulate that AF ablation can reduce mortality. CASTLE-AF is the only randomised clinical trial to date comparing catheter ablation and pharmacological therapy for patients with coexisting HF and AF that measures the ‘hard’ primary endpoints of death and hospitalisation for heart failure.63 Patients had symptomatic paroxysmal or persistent AF, LVEF ≤35%, NYHA class ≥2, with an ICD or CRT with defibrillator implanted. AF ablation was associated with a significantly lower rate of a composite of death and hospitalisation for HF than medical therapy.63 There was also a benefit in all-cause mortality alone, driven by a significantly lower rate of cardiovascular death in the ablation group. Furthermore, catheter ablation reduced the AF burden, increased the distance walked in 6 minutes and improved the LVEF. On the basis of the data extracted from the memory of the implanted devices, 63.1% of the patients in the ablation group and 21.7% in the medical-therapy group (p<0.001) were in SR at the 60-month follow-up visit and had not had AF recur since the previous follow-up visit (typically at 48 months).63

Heart Rhythm Monitoring Following AF Ablation Given the benefits of maintenance of SR following AF ablation described, accurate and complete heart rhythm monitoring is imperative. The HRS Expert Consensus Statement set guidelines for catheter ablation trials stating that, after the blanking period, success is defined as ‘freedom from AF, atrial flutter or tachycardia’ and discontinuation of antiarrhythmic medication, that patients should be followed for at least 12 months and, at minimum, should have a 24hour Holter monitor at 3, 6, 12 and 24 months.16,64 The gold standard of heart rhythm monitoring is beat-to-beat monitoring with implanted devices.65 AF ablation studies employing beat-to-beat monitoring with implanted devices have determined ‘cure’ rates of only 29% for persistent AF, significantly lower than trials that used less stringent monitoring criteria.31, 66 Beat-to-beat monitoring will detect significantly more AF episodes because of the continuous monitoring capabilities of implanted devices. In the absence of large, prospective, randomised studies using beat-to-beat follow up, ablation success remains open to speculation. Beat-to-beat monitoring is particularly important if it is the restoration of SR that is associated with improvement in LV function and provides an argument for all catheter ablation studies to have significantly tighter cardiac monitoring, ideally with implanted devices allowing every heartbeat to be monitored.

Discussion The main findings of our systematic review are that the pathophysiological benefits from AF ablation stem from successful restoration of SR and this is most likely to be achieved by early intervention. These benefits extend to reversed remodelling of the left cardiac chambers, an improvement in LVEF, an improvement in key, prognostic facets of exercise performance and a reduction in SDB. It is

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In addition, a large percentage of patients in the general population progress from a paroxysmal form of AF to a persistent or permanent form, limiting the likelihood of successful ablation, suggesting timely treatment of arrhythmia-mediated cardiomyopathy with ablation may minimise irreversible remodelling when SR is restored.

Recent evidence has suggested the importance of AF burden to cardiovascular and neurological outcomes, and the effect of lifestyle and risk factor modification on AF burden. AF burden is best defined as the proportion of time an individual is in AF during a monitoring period, expressed as a percentage, and continuous monitoring, ideally with an implanted device, is required to meet this definition. A number of studies have reported improvement in ‘soft’ end points with catheter ablation of AF. However, they are not powered to demonstrate that mortality can be reduced by ablation. The CASTLE-AF trial substantiates these earlier reports that AF ablation is beneficial in patients with AF and HF. The study demonstrated that the use of ablation for AF in patients with HF is associated with a significantly lower composite of death and HF hospitalisation than medical therapy. The results from CASTLE-AF are of significant interest and support a role for AF ablation in such patients. However, these results do not support offering AF ablation to all patients with AF and HF. The inclusion criteria for the trial were strict, resulting in more than 3,000 patients being screened to identify 363 patients to take part in the trial. The quality of the rate control in the pharmacological group has not been published and, in the current review, we have demonstrated the importance of effective rate control in improving LV performance. The mortality benefits of ablation only appeared after 3 years into the trial, by which stage only 191 of the original trial patients were still being followed up. Finally, some subgroups did not benefit from ablation, such as those with an LVEF<25%.67 However, despite these issues, there is sufficient evidence to support early AF ablation in patients with symptomatic AF and HF, in addition to device therapy.

The Future A significant limitation of all AF ablation studies is the lack of blinding with regard to randomisation and treatment. Randomised, doubleblind, placebo-controlled studies are considered the gold standard of studies involving a medical intervention. Randomised clinical trials with inadequate blinding report enhanced placebo effects for intervention groups and nocebo effects for placebo groups.68 It is difficult to perform a truly blinded trial with a sham AF ablation procedure, but the lack of blinding could result in bias as to whether, for example, to admit a patient for worsening HF, how the patients are medically managed, how the patients report symptoms and so on. To date, no studies have included a satisfactory, ethically justifiable sham limb to compare with AF ablation. The advent of such a study design could advance our understanding to another level.

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Rhythm Control in AF-CHF

Clinical Perspective • The pathophysiological benefits from AF ablation stem from successful restoration and maintenance of sinus rhythm and this is most likely to be achieved by early intervention. • These benefits extend to reversed remodelling of the left cardiac chambers, an improvement in left ventricular ejection fraction, an improvement in key, prognostic facets of exercise performance and a reduction in sleep-disordered breathing. • Timely treatment of arrhythmia-mediated cardiomyopathy with ablation may minimise irreversible remodelling when sinus rhythm is restored. • Given the importance of restoration and maintenance of sinus rhythm following ablation, we propose that AF ablation trials should use stringent heart rhythm monitoring, ideally with implanted devices, allowing monitoring of every heartbeat to document the true impact of ablation on heart rhythm.

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34. Kuppahally SS, Akoum N, Badger TJ, et al. Echocardiographic left atrial reverse remodeling after catheter ablation of atrial fibrillation is predicted by preablation delayed enhancement of left atrium by magnetic resonance imaging. Am Heart J 2010;160:877–84. https://doi.org/10.1016/j.ahj.2010.07.003; PMID: 21095275. 35. Avitall B, Bi J, Mykytsey A, Chicos A. Atrial and ventricular fibrosis induced by atrial fibrillation: evidence to support early rhythm control. Heart Rhythm 2008;5:839–45. https://doi. org/10.1016/j.hrthm.2008.02.042; PMID: 18534368. 36. Wijesurendra RS, Casadei B. Atrial fibrillation: effects beyond the atrium? Cardiovasc Res 2015;105:238–47. https://doi. org/10.1093/cvr/cvv001; PMID: 25587048. 37. Nattel S, Burstein B, Dobrev D. Atrial remodeling and atrial fibrillation: mechanisms and implications. Circ Arrhythm Electrophysiol 2008;1:62–73. https://doi.org/10.1161/ CIRCEP.107.754564; PMID: 19808395. 38. Hanna N, Cardin S, Leung TK, et al. Differences in atrial versus ventricular remodeling in dogs with ventricular tachypacinginduced congestive heart failure. Cardiovasc Res 2004;63:236– 44. https://doi.org/10.1016/j.cardiores.2004.03.026; PMID: 15249181. 39. González A, Schelbert EB, Díez J, et al. Myocardial interstitial fibrosis in heart failure: biological and translational perspectives. J Am Coll Cardiol 2018;71:1696–706. https://doi. org/10.1016/j.jacc.2018.02.021; PMID: 29650126. 40. Prabhu S, Costello BT, Taylor AJ, et al. Regression of diffuse ventricular fibrosis following restoration of sinus rhythm with catheter ablation in patients with atrial fibrillation and systolic dysfunction: a substudy of the CAMERA MRI trial. JACC Clin Electrophysiol 2018;4:999–1007. https://doi.org/10.1016/j. jacep.2018.04.013; PMID: 30139501. 41. Inoue YY, Alissa A, Khurram IM, et al. Quantitative tissuetracking cardiac magnetic resonance (CMR) of left atrial deformation and the risk of stroke in patients with atrial fibrillation. J Am Heart Assoc 2015;4:e001844. https://doi. org/10.1161/JAHA.115.001844; PMID: 25917441. 42. Parmar BR, Jarrett TR, Kholmovski EG, et al. Poor scar formation after ablation is associated with atrial fibrillation recurrence. J Interv Card Electrophysiol 2015;44:247–56. https:// doi.org/10.1007/s10840-015-0060-y; PMID: 26455362. 43. Nori D, Raff G, Gupta V, et al. Cardiac magnetic resonance imaging assessment of regional and global left atrial function before and after catheter ablation for atrial fibrillation. J Interv Card Electrophysiol 2009;26:109–17. https://doi.org/10.1007/ s10840-009-9409-4; PMID: 19629666. 44. Muellerleile K, Groth M, Steven D, et al. Cardiovascular magnetic resonance demonstrates reversible atrial dysfunction after catheter ablation of persistent atrial fibrillation. J Cardiovasc Electrophysiol 2013;24:762–7. https://doi.org/10.1111/jce.12125; PMID: 23551416. 45. Albouaini K, Egred M, Alahmar A, et al. Cardiopulmonary exercise testing and its application. Postgrad Med J 2007;83:675–82. https://doi.org/10.1136/hrt.2007.121558; PMID: 17989266. 46. Fiala M, Wichterle D, Bulková V, et al. A prospective evaluation of haemodynamics, functional status, and quality of life after radiofrequency catheter ablation of long-standing persistent atrial fibrillation. Europace 2014;16:15–25. https://doi. org/10.1093/europace/eut161; PMID: 23851514. 47. Jessup M, Abraham WT, Casey DE, et al. 2009 focused update: ACCF/AHA guidelines for the diagnosis and management of heart failure in adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines: developed in collaboration with the International Society for Heart and Lung Transplantation. Circulation. 2009;119:1977–2016. https:// doi.org/10.1161/CIRCULATIONAHA.109.192064; PMID: 19324967. 48. Mancini DM, Eisen H, Kussmaul W, et al. Value of peak exercise oxygen consumption for optimal timing of cardiac transplantation in ambulatory patients with heart failure. Circulation 1991;83:778–86. https://doi.org/10.1161/01. CIR.83.3.778; PMID: 1999029. 49. Swank AM, Horton J, Fleg JL, et al. Modest increase in peak

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VO2 is related to better clinical outcomes in chronic heart failure patients: results from heart failure and a controlled trial to investigate outcomes of exercise training. Circ Heart Fail 2012;5:579–85. https://doi.org/10.1161/CIRCHEARTFAILURE. 111.965186; PMID: 22773109. Kwon Y, Misialek JR, Duprez D, et al. Association between sleep disordered breathing and electrocardiographic markers of atrial abnormalities: the MESA study. Europace 2017;19:1759–66. https://doi.org/10.1093/europace/euw328; PMID: 28017934. Morrell MJ, McMillan A. Does age matter? The relationship between sleep-disordered breathing and incident atrial fibrillation in older men. Am J Respir Crit Care Med 2016;193:712–4. https://doi.org/10.1164/rccm.201511-2298ED; PMID: 27035781. Fox H, Bitter T, Horstkotte D, et al. Cardioversion of atrial fibrillation or atrial flutter into sinus rhythm reduces nocturnal central respiratory events and unmasks obstructive sleep apnoea. Clin Res Cardiol 2016;105:451–9. https:// doi.org/10.1007/s00392-015-0940-2; PMID: 26552903. Sanders P, Elliott AD, Linz D. Upstream targets to treat atrial fibrillation. J Am Coll Cardiol 2017;70:2906–8. https://doi. org/10.1016/j.jacc.2017.10.043; PMID: 29216986. Pathak RK, Evans M, Middeldorp ME, et al. Cost-effectiveness and clinical effectiveness of the risk factor management clinic in atrial fibrillation: the CENT study. JACC Clin Electrophysiol 2017;3:436–47. https://doi.org/10.1016/j.jacep.2016.12.015; PMID: 29759599. Naruse Y, Tada H, Satoh M, et al. Radiofrequency catheter ablation of persistent atrial fibrillation decreases a sleepdisordered breathing parameter during a short follow-up period. Circ J 2012;76:2096–103. https://doi.org/10.1253/circj. CJ-12-0014; PMID: 22664722. O’Brien LM, Bullough AS, Shelgikar AV, et al. Validation of Watch-PAT-200 against polysomnography during pregnancy. J Clin Sleep Med 2012;8:287–94. https://doi.org/10.5664/ jcsm.1916; PMID: 22701386.

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57. Iwasaki YK, Shi Y, Benito B, et al. Determinants of atrial fibrillation in an animal model of obesity and acute obstructive sleep apnea. Heart Rhythm 2012;9:1409–16.e1. https://doi. org/10.1016/j.hrthm.2012.03.024; PMID: 22440155. 58. Marulanda-Londoño E, Chaturvedi S. The interplay between obstructive sleep apnea and atrial fibrillation. Front Neurol 2017;8:668. https://doi.org/10.3389/fneur.2017.00668; PMID: 29312113. 59. Redolfi S, Yumino D, Ruttanaumpawan P, et al. Relationship between overnight rostral fluid shift and obstructive sleep apnea in nonobese men. Am J Respir Crit Care Med 2009;179:241–6. https://doi.org/10.1164/rccm.200807-1076OC; PMID: 19011149. 60. Bucca CB, Brussino L, Battisti A, et al. Diuretics in obstructive sleep apnea with diastolic heart failure. Chest 2007;132:440–6. https://doi.org/10.1378/chest.07-0311; PMID: 17699130. 61. Tang SC, Lam B, Lai AS, et al. Improvement in sleep apnea during nocturnal peritoneal dialysis is associated with reduced airway congestion and better uremic clearance. Clin J Am Soc Nephrol 2009;4:410–8. https://doi.org/10.2215/CJN.03520708; PMID: 19118118. 62. Lavie P, Lavie L, Herer P. All-cause mortality in males with sleep apnoea syndrome: declining mortality rates with age. Eur Respir J 2005;25:514–20. https://doi.org/10.1183/09031936.05.0 0051504; PMID: 15738297. 63. Marrouche NF, Kheirkhahan M, Brachmann J. Catheter ablation for atrial fibrillation with heart failure. N Engl J Med 2018;379:492. https://doi.org/10.1056/NEJMc1806519; PMID: 30067924. 64. Terricabras M, Verma A, Morillo CA. Measuring success in ablation of atrial fibrillation: time for a paradigm shift? Circ Arrhythm Electrophysiol 2018;11:e006582. https://doi. org/10.1161/CIRCEP.118.006582; PMID: 30002067. 65. Podd SJ, Sugihara C, Furniss SS, et al. Are implantable cardiac monitors the ‘gold standard’ for atrial fibrillation detection? A prospective randomized trial comparing atrial fibrillation monitoring using implantable cardiac monitors and DDDRP permanent pacemakers in post atrial fibrillation ablation

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COVID-19

Electrophysiology in the Era of Coronavirus Disease 2019 Vijayabharathy Kanthasamy1 and Richard J Schilling1,2 1. St Bartholomew’s Hospital, Barts Health NHS Trust, London, UK; 2. NHS Nightingale Hospital, London, UK

Disclosure: RJS has received research grants and speaker fees from Abbott, Medtronic, Boston Scientific and Johnson & Johnson, and is a shareholder of AI Rhythm. VK has no conflicts of interest to declare. Received: 20 July 2020 Accepted: 22 July 2020 Citation: Arrhythmia & Electrophysiology Review 2020;9(3):167–70. DOI: https://doi.org/10.15420/aer.2020.32 Correspondence: Richard J Schilling, St Bartholomew’s Hospital, Department of Cardiac Electrophysiology, West Smithfield, London EC1A 7BE, UK. E: richard.schilling@nhs.net Open Access: This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for noncommercial purposes, provided the original work is cited correctly.

Coronavirus disease 2019 (COVID-19) is caused by the novel betacoronavirus officially named by the WHO as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has spread rapidly globally since the first case reported in Wuhan, China in

cardiogenic shock. This would also explain the trend of raised cardiac troponin T seen in these patients who are severely affected, and the correlation with disease severity and mortality.9,10 In several studies a significant proportion (22–33%) of patients with severe COVID-19 were

December 2019 and has now affected more than 12 million people worldwide, with varying fatality rates across different countries.1 The clinical presentation of COVID-19 is heterogeneous and varies from asymptomatic to severe pneumonia/acute respiratory distress syndrome (ARDS) requiring invasive mechanical ventilation. In addition, a hyperinflammatory state secondary to cytokine release syndrome leads to hypercoagulation, multiorgan failure and increased mortality.

found to have acute myocardial injury, as evidenced by raised cardiac troponin (above upper limits of normal) or new electrocardiographic/ echocardiographic abnormalities.11–14

COVID-19 has had a huge and unprecedented global impact on public health and healthcare delivery across several countries. Most electrophysiology (EP) activities have been significantly reduced or deferred in order to accommodate the healthcare demands of the pandemic. Irrespective of challenges faced during the pandemic, electrophysiologists still play a vital role in managing cardiovascular complications related to COVID-19 and in maintaining services for urgent and emergency EP procedures.

COVID-19 and the Cardiovascular System The pathogenesis of COVID-19 is characterised by an initial phase of viral response followed by a host inflammatory response.2 During the early viral infection phase, the virus infiltrates the lung parenchyma and replicates. Collateral tissue injury and the inflammatory process that follows cause vasodilatation, endothelial permeability, and leucocyte recruitment leading to further pulmonary damage, hypoxaemia and cardiovascular stress.3,4 Several recent studies have demonstrated a deleterious impact on the cardiovascular system including acute myocardial injury, acute myocarditis, cardiomyopathies, arrhythmias, sudden cardiac death and cardiac arrest.5,6 Angiotensin-converting enzyme 2 (ACE2) acts as a host receptor, facilitating entry of the SARS-CoV-2 infection into human cells, and is expressed in lung alveolar epithelial, heart, vascular and gastrointestinal tract cells.7,8 Even though it is not certain at this time, ACE2 host receptor involvement may account for the clinical presentations with cardiovascular complications, such as myocarditis, arrhythmia and

Arrhythmias Arrhythmias are common in viral infections/sepsis and can occur during both the viral and inflammatory phases in COVID-19. There are several factors that may contribute to arrhythmias in the context of COVID-19 (Figure 1) including fever, sepsis, hypoxia, MI, myocarditis, stress-induced cardiomyopathy, electrolyte imbalance and multiorgan failure. A recent report from Wuhan noted arrhythmias in 16.7% of hospitalised patients with COVID-19, and in 44.4% of patients in the intensive care unit.14 However, the nature of the common arrhythmias has been poorly described in the literature so far. Apart from achieving rate/rhythm control for AF/atrial flutter, anticoagulation for stroke prevention remains a challenging management strategy with regard to this disease entity. Uncontrolled activation of coagulation cascade following lung injury contributes to pulmonary inflammation in ARDS. As a result, extremely raised D-dimer levels are found in patients affected with COVID-19, with a substantial proportion affected with venous and arterial thromboembolism.13,15 There is no clear evidence as to whether all patients with the combination of severe COVID-19, new-onset AF and very high D-dimer would benefit from therapeutic anticoagulation irrespective of CHA2DS2VASc score due to the additional risk of thromboembolism associated with COVID-19. Being mindful of the bleeding risk in sepsis, particularly in the intensive care setting with the need for multiple central and arterial lines, careful consideration should be taken with an individualised management plan, balancing the possible therapeutic benefit against the risk of bleeding. Off-label antiviral therapy, such as lopinavir/ritonavir, has the potential for drug interaction with CYP3Amediated direct oral anticoagulation drugs (DOAC; rivaroxaban and apixaban), thereby increasing the plasma DOAC levels. Hence either dose reduction or monitoring of plasma levels is essential to minimise the risk of bleeding.16–18

Access at: www.AERjournal.com

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COVID-19 Figure 1: Potential Triggers of Arrhythmia in Coronavirus Disease 2019 SARS-CoV-2-induced myocardial injury

Electrolyte imbalance

Due to upregulation of ACE2 receptor during viral invasion in heart and coronary vessels

Respiratory failure Severe hypoxia-induced myocyte necrosis and arrhythmia

Diarrhoea (COVID-19 symptom) Acute kidney injury Multiorgan failure Severe sepsis Malabsorption Potential mechanisms triggering arrhythmia in COVID-19 Channelopathies

Acute MI

Brugada syndrome – fever LQTS/CPVT – concomitant use of antiviral therapy or other QT-prolonging drugs

Due to demand/supply imbalance, plaque rupture and arterial thrombotic event secondary to hypercoagulable state

Prolonged QTc-inducing malignant ventricular arrhythmias

Sepsis and high inflammatory state

Off-label use of combined antiviral therapy (hydroxychloroquine/azithromycin)

Physiological stress and cytokine storm Stress-induced cardiomyopathy

ACE2 = angiotensin-converting enzyme 2; COVID-19 = coronavirus disease 2019; CPVT = catecholaminergic polymorphic ventricular tachycardia; LQTS = long QT syndrome; QTc = corrected QT interval; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2.

There is a small amount of emerging literature on the incidence of ventricular arrhythmias. In a single-centre study by Guo et al. of 187 hospitalised patients with COVID-19, the incidence was 5.9% for ventricular tachycardia (VT) and VF.19 VT/VF was also associated with elevated cardiac troponin levels and this raises the question of whether aggressive immunosuppressive therapy is warranted in patients with severe COVID-19. However, there are other known triggers that may induce ventricular arrhythmias in the context of COVID-19. Off-label antiviral therapies (hydroxychloroquine and/or azithromycin) that have been trialled in COVID-19 are well-known to cause prolonged QT interval and thus increase the risk of polymorphic VT.20 These drugs should be avoided outside the setting of a clinical trial, especially in those with underlying long QT syndrome (LQTS), and all healthy patients should be monitored with serial ECG on a periodic basis. COVID-19 can also cause diarrhoea, malabsorption, acute kidney injury and electrolyte imbalance, which may pose a risk of ventricular and atrial arrhythmias.21–23 In addition, there is an increased risk of MI during the acute phase in patients with cardiac comorbidities, secondary to supply/demand imbalance, plaque rupture, severe hypoxia causing myocyte necrosis or arterial embolism due to hypercoagulable state, which can trigger malignant ventricular arrhythmias.24–26

Risk of Sudden Cardiac Death There are no specific data on patients with channelopathies or inherited cardiomyopathies and COVID-19. However, COVID-19 could occur in patients with risk of sudden cardiac death with underlying diagnosed Brugada syndrome (BrS), congenital LQTS, catecholaminergic polymorphic ventricular tachycardia (CPVT), arrhythmogenic cardiomyopathy and hypertrophic cardiomyopathy. It seems likely that

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patients with cardiomyopathy may also have an increased risk of complications from COVID-19 and therefore should take precautions. The primary concern with BrS is fever-induced malignant ventricular arrhythmia, and therefore fever should be aggressively treated with paracetamol. If this fails to control fever, patients should have continuous ECG monitoring and access to emergency cardiac support and defibrillation until the fever settles. Although it is obvious that patients with a diagnosis of LQTS should not receive QT prolonging drugs, electrophysiologists will need to remind their colleagues that many patients with out-of-hospital cardiac arrest secondary to long QT, present as a result of iatrogenic intervention and, in the absence of drugs or electrolyte disturbance, may have a normal QT interval. A cautious approach is necessary when recruiting for COVID treatment trials. QTc interval should be monitored closely and QT-prolonging drugs should be stopped in the case of QTc >500 ms or if QTc increases by >60 ms from baseline.27 Electrolyte imbalances are often seen during acute illness, which should be promptly corrected particularly when associated with ECG changes. These include prolonged QTc (potential risk for torsades de pointes ventricular arrhythmia), visible U wave, atrial tachyarrhythmias and mild ST depression in severe hypokalaemia, QTc prolongation primarily by prolonging the ST segment in hypocalcaemia and QTc prolongation, atrial/ventricular ectopics and tachyarrhythmias in hypomagnesaemia.22 Patients with CPVT are often treated with beta-blockers and flecainide, which can interact with antiviral therapies, including hydroxychloroquine, azithromycin and lopinavir/ritonavir, causing serious arrhythmias. Intensivists will have a genuine challenge in

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EP in the Era of COVID-19 managing these patients for whom beta-blockade is critical to avoid torsades de pointes, but for whom noradrenaline and other inotropes are necessary for maintaining blood pressure.

Phased Return of Elective Electrophysiology Procedures Prioritising patient healthcare needs is of paramount importance during the pandemic in order to effectively utilise limited resources. Certain categories of EP procedures were deemed non-urgent to preserve resources to treat patients affected by COVID-19. Admissions with acute symptoms, such as complete heart block, symptomatic VT and symptomatic intractable arrhythmia, may not have significantly changed during the pandemic. However, the public may be reluctant to seek medical advice, and late presentations of acute cardiac events with their long-term sequelae have been described.28 In most healthcare systems, redeployment of staff has also had a huge impact on continuing EP elective work. Resuming elective work should be done in a safe and sustainable manner. Creating a model that suits the specific hospital is important to optimise the chances of a normal return to clinical services. We would recommend the following principles to guide recovering services.

Minimising Patient Exposure to the Public and Healthcare Workers It is obvious that patients travelling to receive healthcare advice or treatment are emerging from isolation and are particularly exposed if interacting with healthcare services that also manage COVID patients. Patient exposure can be minimised by establishing ‘clean’ services working on the principle that if the patient does have to meet a healthcare professional, then that professional should be dedicated to only looking after patients who do not have COVID symptoms. This can be achieved by: • All clinic consultations and preadmission visits being carried out via telephone or online video consultation. • All prolonged ECG monitoring (Holter) being posted to the patient and instructing them by phone how to attach them. • Increased use of patient administered and owned ECG monitoring. Apple Watch and AliveCor Kardia are the most well-known, but there is a plethora of equally effective and cheap technologies available for online purchasing. • Posting pre-admission blood tests and swabs to the patient. Some blood tests can be delivered via point-of-care or finger prick systems, avoiding the patient having to attend a clinical service. COVID-19 swabs are notoriously difficult to perform adequately by the general public and may be harder to deliver reliably. • All device follow-ups being performed remotely when possible. At St Bartholomew’s Hospital, we have been sending out remote monitoring systems to patients with remote-capable devices, but some patients with legacy devices will have their follow-up deferred if they are at low risk and asymptomatic. • In-person investigations (echo and MRI) being delivered in isolated or community services, remote from acute COVID-19 care services.

Appropriate Triage of Elective Care Patients with time-critical conditions should be given priority, regardless of their risk of exposure to the general public. This includes those with

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complete heart block and pacing-dependent patients reaching the end of their device battery life. Persistent AF is our biggest dilemma because although most of these patients have no prognostic benefit from ablation, they are time critical in that delaying their ablation procedure results in poorer outcomes. We have been assessing their risk of COVID-19 and their AF symptoms and making joint decisions with the patients about when and if they have their procedure. Other patients with non-time critical conditions (symptomatic supraventricular tachycardia) are now being given dates for procedures, particularly if they are at low risk of COVID-19 and/or they are having to seek emergency room assistance for their condition. This process takes a lot of time and discussion with patients. Therefore, although our catheterisation labs are not as busy, our clinicians are, because they are spending time making these difficult decisions and prioritising. This also has created a lot of work for administrators, who are responsible for patient scheduling.

Minimising Procedure Risks to Staff While it is good practice to screen patients for COVID-19 ahead of admission, we can never be certain that patients will be free of the virus. There are specific considerations that can be given to EP procedures to help reduce risk to staff, primarily around minimising aerosolising procedures. This could include: • minimising procedures under general anaesthetic; • minimising the use of transoesophageal echo; and • minimising use of diathermy. There is some evidence that diathermy can produce particles containing viral material. Vaporisation of protein and fat from heated tissues causes surgical smoke, which contains chemicals, biological particles, viruses and bacteria. This smoke from tissue pyrolysis is known to be potentially hazardous, especially at the current time.29,30 For many decades we implanted devices without the use of diathermy and we would suggest that this can be avoided or minimised for the moment.

Other Considerations The use of hospitals not normally involved in national healthcare provision, e.g. independent or field hospitals, may provide capacity for investigations or procedures, not normally available. Staff should have access to appropriate personal protective equipment and training in proper hygiene, donning and doffing it, but should use this only in higher risk situations in order to to preserve supplies.

Conclusion COVID-19 can cause a wide range of cardiovascular complications, of which arrhythmias are one of the most common. Furthermore, the pandemic has had an unprecedented impact on healthcare systems globally, certainly affecting elective procedures. However, on the positive side, digital health and telemedicine have played an important role in EP during the pandemic, and will change the way we work, well beyond the end of the COVID-19 crisis.

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