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作者:

Ge, X. (Ge, X..) | Liu, Y. (Liu, Y..) | Tu, S. (Tu, S..) | Simakov, S. (Simakov, S..) | Vassilevski, Y. (Vassilevski, Y..) | Liang, F. (Liang, F..)

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摘要:

Although fractional flow reserve (FFR) and coronary flow reserve (CFR) are both frequently used to assess the functional severity of coronary artery stenosis, discordant results of diagnosis between FFR and CFR in some patient cohorts have been reported. In the present study, a computational model was employed to quantify the impacts of various pathophysiological factors on FFR and CFR. In addition, a hyperemic myocardial ischemic index (HMIx) was proposed as a reference for comparing the diagnostic performances of FFR and CFR. Obtained results showed that CFR was more susceptible than FFR to the influence of many pathophysiological factors unrelated to coronary artery stenosis. In particular, the numerical study proved that increasing hyperemic coronary microvascular resistance significantly elevated FFR while reducing CFR despite fixed severity of coronary artery stenosis, whereas introducing aortic valve disease only caused a significant decrease in CFR with little influence on FFR. These results provided theoretical evidence for explaining some clinical observations, such as the increased risk of discordant diagnostic results between FFR and CFR in patients with increased hyperemic microvascular resistance, and significant increase in CFR after surgical relief of severe aortic valve disease. When evaluated with respect to the predictive value for hyperemic myocardial ischemia, the performance of FFR was found to be considerably compromised in the presence of severe coronary vasodilation dysfunction or aortic valve disease, whereas the relationship between CFR and HMIx remained relatively stable, suggesting that CFR may be a more reliable indicator of myocardial ischemia under complex pathophysiological conditions. © 2019 John Wiley & Sons, Ltd.

关键词:

aortic valve disease; CFR; FFR; microvascular dilation dysfunction; myocardial ischemia; numerical simulation

作者机构:

  • [ 1 ] [Ge, X.]School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
  • [ 2 ] [Ge, X.]Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE), Shanghai Jiao Tong University, Shanghai, 200240, China
  • [ 3 ] [Liu, Y.]College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China
  • [ 4 ] [Tu, S.]Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China
  • [ 5 ] [Simakov, S.]Moscow Institute of Physics and Technology, Dolgoprudny, 141700, Russian Federation
  • [ 6 ] [Simakov, S.]Institute for Personalized Medicine, Sechenov University, Moscow, 119991, Russian Federation
  • [ 7 ] [Vassilevski, Y.]Moscow Institute of Physics and Technology, Dolgoprudny, 141700, Russian Federation
  • [ 8 ] [Vassilevski, Y.]Institute for Personalized Medicine, Sechenov University, Moscow, 119991, Russian Federation
  • [ 9 ] [Vassilevski, Y.]Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, 119333, Russian Federation
  • [ 10 ] [Liang, F.]School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
  • [ 11 ] [Liang, F.]Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE), Shanghai Jiao Tong University, Shanghai, 200240, China
  • [ 12 ] [Liang, F.]Institute for Personalized Medicine, Sechenov University, Moscow, 119991, Russian Federation

通讯作者信息:

  • [Liang, F.]School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong UniversityChina

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来源 :

International Journal for Numerical Methods in Biomedical Engineering

ISSN: 2040-7939

年份: 2019

2 . 1 0 0

JCR@2022

ESI学科: COMPUTER SCIENCE;

ESI高被引阀值:58

JCR分区:2

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 15

ESI高被引论文在榜: 0 展开所有

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