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Future of Imaging
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Imaging and the transformation of healthcare
WRITTEN BY: DR JANE PHILLIPS-HUGHES President, British Institute of Radiology
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t would have been difficult to predict the pace and scale of this development back in 1895. The pioneers of radiology early in the 20th century, who would ‘dark adapt’ their eyes prior to performing early fluoroscopic studies, would be amazed to see the new technologies that are already in use and on display at imaging conferences these days. Wearable devices such as portable Magnetoencephalography (MEG) brain scanners and wearable MRI gloves are now available, and no doubt there are more incredible new imaging devices in the pipeline. The potential for prediction and personalised medicine Medical imaging now provides more than just a demonstration of anatomy and pathology. Using molecular and hybrid imaging, f u nc t ion a l phys iolog ic a l a nd pharmacological information is available at molecular and cellular level. Th i s dat a c a n be combi ne d
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with genomic data to provide truly personalised medicine. Furthermore, the extraction of d i s t i nc t ive fe at u re s of diseases from large d at a s e t s of me d ic a l images using datacharacterisation algorithms is now underway. This process, referred to as radiomics, has t he potent ia l for predicting prognosis and therapeutic response for various conditions. It is a credit to mankind’s innate curiosity, thirst for knowledge and desire to keep moving forwards that research has brought us so far.
strongly in this publication – and in ever y imaging publication and conference t hese days. Indeed, many contemporary radiologists, radiographers and medical physicists have been alarmed about possible detrimental side-effects of the inexorable evolution of AI and machine learning. One of the main concerns is that those outside of our industry might mistakenly assume that these te ch nolog ie s repl ac e u s, and that this is the answer to the growing problem of work forc e shor t age s i n a n era where workload is growing exponentially.
There’s no need to fear artificial intelligence However, those early pioneers might well initially be alarmed to he a r ab out t he l ate s t a nd inescapable topic of ar t ificia l intelligence (AI), which features
AI is our assistant In fact, the overall consensus among imaging and AI experts throughout the world now is that, when established, AI will assist us, not replace us. It will play a role in improving service delivery via
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worklist management, triaging and prioritisation of cases, in theory allowing radiologists to devote time to other important clinical tasks. However, even this will take time, there will be teething problems and the role out of new technologies on a global scale will not be equal. There is still a lot of work to do – and there certainly remains a need to recruit many talented new individuals into our services. Read more at healthawareness.co.uk
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AI, big data and deep learning – the future of radiology WRITTEN BY: DR SRIDHAR REDLA Honorary Secretary and President Elect, The British Institute of Radiology
We are witnessing the third big transformation in the form of artificial or augmented intelligence. The discussion is no longer about “if it comes”, but “when it comes.”
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adiology has transformed to an extraordinary degree since Roentgen’s discovery of X-rays in 1895, comments Dr Jane Phillips-Hughes, President of the British Institute of Radiology. The 1970s and 1980s saw the introduction of cross-section imaging, in the form of ultrasound, computerised tomography (CT), magnetic resonance imaging (MRI), etc. The second transformation of the profession happened in the 1990s, with the introduction of picture archiving and communication system (PACS), which moved us on from the analog to the digital age. We can now access radiological investigations and results from most work computers. This transformed the working lives of not just radiologists, but the medical workforce as a whole. Now we are seeing the third major revolution in imaging! AI will complement the work of radiologists Without a doubt, AI will have a major positive impact on diagnostics, especially in regards to radiology and imaging. It has now been widely accepted that AI will not replace radiologists, but complement and augment the care provided. AI is expected to help with prioritisation, improving efficiency and accuracy – and thereby patient safety. The future will hopefully see AI seamlessly integrate into our PACS workstations, acting as a ‘third eye’, providing a more timely and accurate diagnosis. It is to be recognised, however, that the role of AI, its benefits and usage, will vary from country to country, based on the local healthcare system and its challenges. Data is the new ‘energy source’ for AI For AI to be successfully implemented, we must develop algorithms that are practical to the profession. For that we need clean data. The National Health Service is a huge source of data; given its organised structure and the fact that it is a freely accessible healthcare provider. Naturally, the big and small vendors would like this data to develop their machine learning programs and algorithms. This puts the radiology profession in a prime position, to direct the vendors and big players to work to our advantage. Applications of AI in radiology Any new algorithm should be properly validated and should be ‘vendor neutral’, so that it can be seamlessly integrated into any imaging system. One side of AI should help with the day-to-day, mundane tasks like workflow, scheduling, protocols, reporting, quality assessment, dose modulation etc. However, the machine learning aspect should be concentrated on the clinical applications.
More info The NHS has among the lowest numbers of doctors, nurses and hospital beds per capita in the western world* and radiology has an acute workforce crisis. The proposed Government funded AI lab should help ease the pressure on these healthcare professionals, provided the priorities are right. *https://www.kingsfund.org.uk/publications/spending-and-availability-health-care-resources
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Research sheds new light on lung cancer screening in Europe The European Society of Radiology (ESR) and European Respiratory Society (ERS) have published a new paper on lung cancer screening (LCS) in Europe.
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ndorsed by both societies, the paper contains a contemporary, non-systematic review of the literature and common practice in LCS in Europe and also refers to the results of a DutchBelgian randomised lung cancer screening trial (NELSON trial). Reviewing at current practices Intended as an update to a previous ESR-ERS working group white paper on lung cancer screening from 2015, the statement was published s i mu l t a n e o u s l y i n E u r o p e a n R ad iolo g y a nd t he E u rop e a n Respiratory Journal. Focusing on new findings and current discussions surrounding screening programmes, it reviews the evidence from LCS trials, offering a description of current practice, as well as aspects that have not received significant attention until now. The next steps in screening The ESR and ERS agree that Europe’s health systems need to adapt to allow citizens to benefit from organised pathways, rather than unsupervised initiatives, to allow early diagnosis of
Echoing the adoption of CT by radiotherapy departments solely for RT planning, dedicated MRdemand for higher quality soft-tissue imaging. lung cancer and reduce the mortality rate. The authors argue that now is the time to set up and conduct demonstration programmes focusing on methodology, standardisation, tobacco cessation, education on healthy lifestyles, cost-effectiveness and a central registry. Both the ESR and ERS anticipate that the publication of the paper will stimulate further discussion and action on the implementation of lung cancer screening programmes in European countries. The benefits of working together The paper was written by members of the ESR-ERS working group who have been collaborating on the statement since early 2018. Chaired by Professor HansUlrich Kauczor of Un iversit y H o s p i t a l Heidelberg, Germany, and the German Centre of Lung Research, the group consists
of 22 representatives from the ESR and ERS, including radiologists, pulmonologists, thoracic oncologists, thoracic surgeons, psychologists, epidemiologist, molecular biologists, health care managers and patients. In addition, members of the patient advisory committee of the European Lung Foundation (ELF) offered their unique perspective on screening programmes in Europe. Early diagnosis and lung cancer On publication of the joint statement, P r o fe s s o r K au c z o r s a i d , “A l l stakeholders involved are convinced that patients and citizens will benefit from early diagnosis of lung cancer and that screening will significantly reduce the mortality of the number one killer worldwide – cancer. “We emphasise the importance of advocacy by major European and national medical societies and patient organisations to raise public awareness.” The publication of the paper is another crucial milestone, following a joint event organised by ESR, ERS and Lung Cancer Europe (LuCE) at the European Parliament in November 2019. The event saw the launch of a factsheet on lung cancer, which called for an update to the 2003 European Council Recommendation on cancer screening, and for member states to share best practice and gradually implement lung cancer s c re en i n g prog r a m me s wh i le upholding the highest standards of care and patient safety.
Content provided by the European Society of Radiology Read more at healthawareness.co.uk
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The importance of radiation dose optimisation
MRI guided radiotherapy
The radiation dose for any imaging examination is a serious concern and can be a limitation when attempting to preserve the diagnostic quality of the image.
WRITTEN BY: TRINA HERBERT MR Radiotherapy Operational Superintendent The Royal Marsden NHS Foundation Trust
Technical advances in multi-modality imaging – for radiotherapy planning, treatment verification, and dosimetry adaptation – means better accuracy and improved quality of treatment.
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edical imaging is intrinsic to all aspects of the modern radiotherapy (RT) pathway. A patient’s cancer treatment pathway starts with imaging for diagnosis and staging of their disease. The use of medical imaging continues to be an integral part of their journey into and beyond treatment. Radiotherapy requires some form of medical imaging from which a treatment plan can be computed. Imag ing information needs to provide both the anatomical and tissue-density information necessary to design a personalised digital plan that will deliver specific doses of radiation to specifically identified anatomy. This includes both the tumour volume and any normal organs that function close to the tumour that might be affected by radiation dose. Over t wo decades ago, radiotherapy departments began installing dedicated CT scanners for radiotherapy planning, and training their own radiographers to operate them. This is now standard practice that has been followed by increasing interest in incorporating MR imaging into radiotherapy planning and most recently treatment delivery. As the use of MRI increased within radiotherapy, so did the need for extra education and training for therapeutic radiographers. Initially, this was met by attending specific external programmes and working with diagnostic radiography colleagues. Integrating MRI in RT planning The improved soft-tissue visibility provided by MRI scans is recognised as a benefit by oncologists who provide radiotherapy treatment. It improves treatment planning, particularly in anatomical areas where definition of tissue borders is challenging on CT images alone. Therapeut ic rad iog raphers have begun to collaborate closely with their counterparts in MRI departments to incorporate MRI into the radiotherapy planning pathway. Therapeutic radiographers have involved themselves in the
Echoing the adoption of CT by radiotherapy departments solely for RT planning, dedicated MRsimulators are now being installed to meet the increasing demand for higher quality soft-tissue imaging.
scanning of patients for radiotherapy planning purposes. This has included becoming educated in MRI safety and training in scanner operation. This integration also informs diagnostic radiographers of par ticular radiot herapy re qu i rement s s uch a s pat ient preparation, for example, bladder filling, reproducibility of position, immobilisation and optimisation of M R I sequences for accurate treatment planning and calculation. The m a nu f ac t u rer s of M R I scanning systems have recognised the increasing demand for MRI in radiotherapy. This has resulted in the development of MR-simulators. Echoing the adoption of CT by radiotherapy departments solely for RT planning, dedicated MR-simulators are now being installed to meet the increasing demand for higher quality soft-tissue imaging. Therapeutic radiographers are expanding their knowledge base in order to effectively operate t hese system s w it h in radiotherapy departments. Image-guided radiotherapy Medical imaging has long been used to verify the accuracy of patient positioning prior to delivering radiotherapy treatments. Plain X-ray films were superseded by electronic portal imaging using megavoltage X-rays that could be registered with
digitally reconstructed radiographs to assess and correct displacements in patient positioning. As imaging techniques developed, so did their use in radiotherapy treatment verification. Modern Linear Accelerators are designed to include cone beam CT scanners that acquire three dimensional images, used by therapeutic radiographers to con fir m and adjust patient positioning. They are also used to assess physiological parameters, such as appropriate bladder filling, monitoring weight loss, evaluating tumour response and considering appropr iate ac t ion to cl i n ic a l situation, for example lung collapse. t herapeut ic rad iog raphers a re involved with the interpretation of medical imaging as an intrinsic part of the radiotherapy pathway. MRI-guided radiotherapy (MRIgRT) The i nt roduc t ion of M R-Li nac te ch nolog y ha s ex pa nde d t he therapeutic radiographer role further. This hybrid technology combines a high-field MR scanner with highenergy X-ray treatment. therapeutic radiographers are being trained to acquire diagnostic-quality MRI scans for the purposes of re-planning patient’s treatments in a real-time scenario. The technology allows for target organs and organs at risk to be contoured to enable daily adaptation of treatment plans. The superior soft-tissue definition results in reduced inter-observer variability in contouring and may lead to a reduction of treatment margins. Wit h t r a i n i n g, t he r ap e ut ic radiographers working on this novel technology will be able expand their role by performing this task - a role that has previously been the domain of the oncologist. The incorporation of MRI technology into image-guided radiotherapy is the most recent example of improvements in medical imaging technology being adopted and adapted by the radiotherapy community.
WRITTEN BY: PROFESSOR PETER HOGG Professor of Radiography, University of Salford
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WRITTEN BY: DR ANDREW ENGLAND Senior Lecturer in Radiography, University of Salford
edical imaging is intrinsic to all aspects of the modern radiotherapy (RT) pathway. A patient’s cancer treatment pathway starts with imaging for diagnosis and staging of their disease. The use of medical imaging continues to be an integral part of their journey into and beyond treatment. We investigate and solve a range of clinically relevant imaging problems that practitioners face on a daily basis. Our research covers a range of imaging modalities and examinations. We use a range of methods within this research, including estimations of dose, modelling and measurement; image quality evaluations using physical and psychophysical measures; and observer performance assessment. Avoiding false diagnoses from blurred images Examples of this research include identification of causation for and minimisation of reasons leading to blurred full field digital mammography (FFDM) images. Blurred FFDM images can lead to false diagnoses and unnecessary repeat examinations. Repeat imaging can heighten client and family anxiety, increase overall breast screening costs and contribute to unnecessary radiation dosage. Lifetime radiation risk prediction models New mathematical models are being developed that aim to predict total lifetime radiation risk from screening mammography. These models are important as they can help clients make informed decisions about whether or not they wish to participate in screening. They also allow for comparisons between country-based screening programmes, intra-country screening regimes and FFDM machines. Improving computer screen display to avoid inaccuracies Identification of FFDM machine inaccuracies can lead to errors in practice, for instance inaccurate breast cancer risk classification for future screening and lesion localisation as part of biopsy processes. We are analysing computer screen display capabilities for technical checking and reporting on FFDM images. Our work here has already found that the technical checking monitors located in the clinical rooms might not be of an adequate standard to check images before sending them for reporting. We are also working to improve detection of interval cancers, which occur between screening rounds; we are working to improve FFDM positioning technique to ensure standardisation (and thus improve accuracy), minimise discomfort and improve lesion detection performance. We’re also assessing the impact of visual acuity in breast cancer detection performance with a view to setting standards for eyesight checking. Our practice-based research mainly relates to improving FFDM image quality and screening client experience during the imaging process. Examples of our research include identification and minimisation of compression force variability between and within practitioners. We were the first to prove the existence of this, initially focusing our work on a UK population. Since then, we have published a major piece of research that assessed the entire screening population of Norway. Impact from this has been high, with an international software company introducing an automated method to assess practitioner variability. This, it is hoped, will allow for easy identification of outliers and the ability to implement solutions on a global scale. Many aspects of this research have Sponsored by a close relationship with student learning on our undergraduate and postgraduate programmes, particularly the MSc Advanced Medical Imaging. Read more at salford.ac.uk/courses/postgraduate/advanced-medical-imaging HEALTHAWARENESS.CO.UK
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Image of the future: why hospitals must collaborate Radiology is vital to healthcare but its workforce may not be able to keep up with patient demand or implement new technology due to staff shortages. Networks will enable imaging teams to pool resources and improve access to expert opinion.
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maging technolog y is both constantly advancing – with t he ad vent of au g mente d scanners and rapidly developing artificial intelligence programmes – and completely crucial to day-today patient care, with 123,000 NHS scans conducted every single day in England. Politicians are starting to realise that imaging is not only hugely important to NHS care, but also hugely under-resourced. One solution that is gaining more attention is imaging networks, where radiology teams working across different hospital sites can access each other’s equipment and patient scans to share workload and expertise. Collaboration seems obvious, as it will improve the lives of patients and clinicians, and potentially save procurement costs, which can
instead be used for innovation. But the NHS IT landscape is fragmented and competitive. Cross-hospital imaging networks Net work i ng is a solut ion t hat makes sense to the Royal College of Radiologists (RCR). In 2014 we urged the NHS to support the creation of imaging networks. Two years later, we published guidance to help radiology teams buy shared IT and create crosshospital imaging networks. We know they work, thanks to organic networks that have been established by motivated imaging leads. For example, in Devon, r ad iolog y t r a i ne e s p o ol t hei r expertise across three trusts to share out-of-hours scan reporting and improve resilience.
The aim is that by 2023, radiology services will be grouped into 18 virtual networks, mapped to cover existing patient management pathways to ensure radiology scans are read as soon as possible, by the best local expert In Scotland, a regional network connecting hospital radiology IT across the south-east has meant radiologists are now reporting thousands of pooled X-ray and CT scans a month.
WRITTEN BY: DR CAROLINE RUBIN Vice President for Clinical Radiology, The Royal College of Radiologists
L a s t y e a r, N H S E n g l a n d / Improvement (NHSE/I) backed us up. Radiology networks are now a core focus of the Long Term Plan, and a national strategy document for England was published in November. The aim is that by 2023, radiology services will be grouped into 18 virtual networks, mapped to cover ex i s t i ng pat ient m a n agement pathways to ensure radiology scans are read as soon as possible, by the best local expert.
In addition to robust frameworks for str uct ure and gover nance, networks will need clear regional leadership, as well as centralised help to source the crucial new IT solutions they will need in order to function. The RCR is confident radiology networks will be a vital component of t he f ut u re of N H S i mag i ng prov i sion, but t hey w i l l ne e d sustained political will, funding and practical support to ensure their success.
Mapping the networks NHSE/I is now working on network implementation and IT guidance for local leaders, but the devil is most definitely in the detail. Correctly mapping the networks to local radiology capacity and expertise and set patient pathways will be an intricate task.
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