SHA24/007003

Page 1

10th Gulf Heart Association Conference, Riyadh 2013

CT Functional Flow Reserve Koen Nieman, MD, FESC Departments of Cardiology & radiology Erasmus MC, Rotterdam, The Netherlands


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Coronary CT Angiography

Meijboom, JACC 2008


Decision making

Tonino, et al, NEJM 2009

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Wijns et al, Nucl Cardiol 2007


52-years-old Man

• • • • •

1995 A-Flutter ablation; pos fam Hx CVD Progessive angina unresponsive to betablockers and nitrates XECG: 3 mm ↓ST on XECG  severe Mid-LAD lesion Everolimus-eluting, bioresorbable poly-lactic acid scaffold Prospective, open-label, FIM trial in de novo 1VD (N=30)


5yr CT FU

7 6 5 4 3

3.7 mm2

2 1 0

5.9 mm2 (5.0 mm2)

5.0 mm2

Max area stenosis: 35%


5yr CT FU

7 6 5 4 3

3.7 mm2

2 1 0

5.9 mm2 (5.0 mm2)

5.0 mm2

Max area stenosis: 35%


0.87 0.76

FFRinv 0.75 0.71


Computational FFR simulation


How does it work?


Simplified Inflow:

Output P - aorta

Vessel model:

Outflow:

LV mass P - Venous

Computational flow: - Blood is a Newtonian fluid with a given viscosity - Assess flow and pressure at rest - Re-assess assuming low peripheral resistance


Is the model sufficient? Supply

Functional obstr. Microvascular obstr.

Perfusion pressure

Demand Scar hibernation

Bypass / collaterals

Assumptions: LV mass and vessel diameter equal flow Simulated pressure drop equals myocardial ischemia


CT image processing

“Reality”

Sample

Interpolated

Fixed


Accuracy of the CTA?

Busch Eur Rad 2007

Kappa 0.72 Dewey,, IJCI 2007


FFRCT versus FFRinv

Koo, et al, JACC 2011


Koo, et al, JACC 2011


Diagnostic performance of CTA (per patient analysis) Meta-analysis

Discover-FLOW

[Sun, JCCT 2012]

[Koo, JACC 2011]

Sens

99%

94%

Spec

91%

25%

PPV

94%

58%

NPV

99%

80%


DeFACTO Trial • Assess the value of CTA + FFR-CT to detect hemodynamically significant CAD • Multicenter randomized controlled trial

• • • •

N = 252 (285), suspected/known CAD Age 63, 70% male Selected after ICA been planned (<2M) S = 17  15 patients per site per year


Methodology • • • • • •

64+ CT technology Blinded corelab: CTA, FFR-inv, FFR-CT CTA >50% = angiographically significant FFR <0.80 = hemodynamically significant CTA >90%  FFR-CT = FFR-inv = 0.50 [17%] CTA <30%  FFR-CT = FFR-inv = 0.90 [45%]

Hypothesis • CTA/FFR-CT accuracy with 95%CI >70%



N=285 N=252 172 FFR-CT <0.80 116 FFR-inv <0.80

56 FFR-inv >0.80

80 FFR-CT >0.80 13 FFR-inv <0.80

67 FFR-inv >0.80

CTA >50% 64 58-70

FFRCT <0.80 73 67-78

Sensitivity

84 77-90

90 84-95

Specificity

42 34-51

54 46-83

PPV NPV

61 53-67 72 61-81

67 60-74 84 74-90

Accuracy


0.81

0.68

FFR-CT vs FFR-inv: R = 0.63, underestimation by FFR-CT: 0.06


Min et al, JAMA 2012


Technical Feasibility?


Conclusions • Need for Fx assessment after positive CT • Advantages of CT-FFR: – No further testing required – Lesion specific assessment – Prediction of effect of intervention

• Drawbacks of (HeartFlow) CT-FFR: – It is just not the same as invasive FFR, which is not the same as myocardial ischemia – Methodological uncertainties of FFR-CT – Practical limitations – Modest accuracy – Delay and expenses


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Future 1-Stop Shop?

0.86

0.92

Myocardial Perfusion CT

Hybrid PET-CT

Simulated FFR on CTA

0.93



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