A lumped parameter model for evaluating coronary artery blood supply capacity

Author:

Cai Li123,Zhong Qian123,Xu Juan123,Huang Yuan4,Gao Hao5

Affiliation:

1. School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710129, China

2. NPU-UoG International Cooperative Lab for Computation and Application in Cardiology, Xi'an 710129, China

3. Xi'an Key Laboratory of Scientific Computation and Applied Statistics, Xi'an 710129, China

4. Department of Mathematics, University of Cambridge, Cambridge CB2 1TN, UK

5. School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QQ, UK

Abstract

<abstract><p>The coronary artery constitutes a vital vascular system that sustains cardiac function, with its primary role being the conveyance of indispensable nutrients to the myocardial tissue. When coronary artery disease occurs, it will affect the blood supply of the heart and induce myocardial ischemia. Therefore, it is of great significance to numerically simulate the coronary artery and evaluate its blood supply capacity. In this article, the coronary artery lumped parameter model was derived based on the relationship between circuit system parameters and cardiovascular system parameters, and the blood supply capacity of the coronary artery in healthy and stenosis states was studied. The aortic root pressure calculated by the aortic valve fluid-structure interaction (AV FSI) simulator was employed as the inlet boundary condition. To emulate the physiological phenomenon of sudden pressure drops resulting from an abrupt reduction in blood vessel radius, a head loss model was connected at the coronary artery's entrance. For each coronary artery outlet, the symmetric structured tree model was appended to simulate the terminal impedance of the missing downstream coronary arteries. The particle swarm optimization (PSO) algorithm was used to optimize the blood flow viscous resistance, blood flow inertia, and vascular compliance of the coronary artery model. In the stenosis states, the relative flow and fractional flow reserve (FFR) calculated by numerical simulation corresponded to the published literature data. It was anticipated that the proposed model can be readily adapted for clinical application, serving as a valuable reference for diagnosing and treating patients.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

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