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Coronary artery disease
Original article
Computational fluid dynamic measures of wall shear stress are related to coronary lesion characteristics
  1. Jun-Bean Park1,
  2. Gilwoo Choi2,3,
  3. Eun Ju Chun4,
  4. Hyun Jin Kim2,
  5. Jonghanne Park1,
  6. Ji-Hyun Jung1,
  7. Min-Ho Lee5,
  8. Hiromasa Otake6,
  9. Joon-Hyung Doh7,
  10. Chang-Wook Nam8,
  11. Eun-Seok Shin9,
  12. Bernard De Bruyne10,
  13. Charles A Taylor2,11,
  14. Bon-Kwon Koo1,12
  1. 1Department of Medicine, Seoul National University Hospital, Seoul, South Korea
  2. 2HeartFlow, Inc., Redwood City, California, USA
  3. 3Department of Surgery, Stanford University Medical Center, Stanford, California, USA
  4. 4Department of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, South Korea
  5. 5Department of Medicine, Soonchunhyang University Hospital, Seoul, South Korea
  6. 6Department of Medicine, Kobe University Graduate School of Medicine, Kobe, Japan
  7. 7Department of Medicine, Inje University Ilsan Paik Hospital, Goyang-si, Gyeonggi-do, South Korea
  8. 8Department of Medicine, Keimyung University Dongsan Medical Center, Daegu, South Korea
  9. 9Department of Cardiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, South Korea
  10. 10Cardiovascular Center Aalst, OLV-Clinic, Aalst, Belgium
  11. 11Department of Bioengineering, Stanford University, Stanford, California, USA
  12. 12Institute of Aging, Seoul National University, Seoul, South Korea
  1. Correspondence to Dr Bon-Kwon Koo, Department of Internal Medicine and Cardiovascular Center, Seoul National University Hospital, 101 Daehang-ro, Chongno-gu, Seoul 110-744, Korea; bkkoo{at}snu.ac.kr

Abstract

Objective To assess the distribution of pressure and shear-related forces acting on atherosclerotic plaques and their association with lesion characteristics using coronary CT angiography (cCTA)-based computational fluid dynamics (CFD) model of epicardial coronary arteries.

Methods Patient-specific models of epicardial coronary arteries were reconstructed from cCTA in 80 patients (12 women, 63.8±9.0 years). The pressure and wall shear stress (WSS) in left anterior descending coronary arteries were assessed using CFD. High-risk plaques were defined as the presence of at least one of the following adverse plaque characteristics: low-density plaque, positive remodelling, napkin-ring sign and spotty calcification.

Results At resting condition, 39.5% of stenotic segments (% diameter stenosis 52.3±14.4%) were exposed to high WSS (>40 dyne/cm2). When the stenotic lesion was subdivided into three segments, the distribution of WSS was different from that of pressure change and its magnitude was highest at minimal lumen area (p<0.001). High pressure gradient, proximal location, small lumen and short length were independent determinants of WSS (all p<0.05). The plaques exposed to the highest WSS tertile had a significantly greater proportion of high-risk plaques. The addition of WSS to % diameter stenosis significantly improved the measures of discrimination and reclassification of high-risk plaques (area under the curves from 0.540 to 0.718, p=0.031; net reclassification index 0.827, p<0.001).

Conclusions The cCTA-based CFD method can improve the identification of high-risk plaques and the risk stratification for coronary artery disease patients by providing non-invasive measurements of WSS affecting coronary plaques.

https://doi.org/10.1136/heartjnl-2016-309299

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