| IEEE Access | |
| Functional Assessment of Stenotic Coronary Artery in 3D Geometric Reconstruction From Fusion of Intravascular Ultrasound and X-Ray Angiography | |
| Xiaoqing Wang1  Changnong Peng1  Zhigeng Pan2  Xin Liu3  | |
| [1] Department of Cardiology, Shenzhen Sun Yat-Sen Cardiovascular Hospital, Shenzhen, China;Guangdong Industrial Institute of Virtual Reality, Foshan University, Foshan, China;Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; | |
| 关键词: Coronary angiography; intravascular ultrasound; 3-D reconstruction; fractional flow reserve (FFR); computational fluid dynamics (CFD); TIMI (thrombolysis in myocardial infarction); | |
| DOI : 10.1109/ACCESS.2018.2870950 | |
| 来源: DOAJ | |
【 摘 要 】
We aimed to present an alternative method for calculating fractional flow reserve (FFR) from 3-D reconstruction of a coronary artery, based on coronary (X-ray) angiography and intravascular ultrasound (IVUS), to evaluate the ischemic-risk of stenosis and the relationship between FFR and geometrical features of the coronary lesion. The reconstruction of the 3-D catheter trajectory was obtained by the vertical intersection of spatial surfaces which were derived from the 2-D catheter curves in the angiography plane. Computational fluid dynamics was applied to calculate the hemodynamics in the coronary arteries and coronary flow-based FFR (fFFR) was obtained. Twenty-two stenotic coronary arteries were included in this paper for the evaluation of the proposed method. Good correlation between fFFR and the measured pressure wire-derived FFR was found (F = 0.916 and P <; 0.01). Based on our computer modeling, the fFFR values correlated negatively with the severity of the stenosis (r = -0.784 and P <; 0.01). However, fFFR had no significant correlation with coronary curvature, lesion length, and angle. Our method therefore provides a coronary vascular model-based means for computing FFR, and makes full use of the advantages of IVUS examination to diagnose the diseases.
【 授权许可】
Unknown