Modelling coronary flow and myocardial perfusion by integrating a structured-tree coronary flow model and a hyperelastic left ventricle model

Wang, Y. and Yin, X. (2024) Modelling coronary flow and myocardial perfusion by integrating a structured-tree coronary flow model and a hyperelastic left ventricle model. Computer Methods and Programs in Biomedicine, 243, 107928. (doi: 10.1016/j.cmpb.2023.107928) (PMID:38000321)

Abstract

Background and Objective: There is an increasing demand to establish integrated computational models that facilitate the exploration of coronary circulation in physiological and pathological contexts, particularly concerning interactions between coronary flow dynamics and myocardial motion. The field of cardiology has also demonstrated a trend toward personalised medicine, where these integrated models can be instrumental in integrating patient-specific data to improve therapeutic outcomes. Notably, incorporating a structured-tree model into such integrated models is currently absent in the literature, which presents a promising prospect. Thus, the goal here is to develop a novel computational framework that combines a 1D structured-tree model of coronary flow in human coronary vasculature with a 3D left ventricle model utilising a hyperelastic constitutive law, enabling the physiologically accurate simulation of coronary flow dynamics. Methods: We adopted detailed geometric information from previous studies of both coronary vasculature and left ventricle to construct the coronary flow model and the left ventricle model. The structured-tree model for coronary flow was expanded to encompass the effect of time-varying intramyocardial pressure on intramyocardial blood vessels. Simultaneously, the left ventricle model served as a robust foundation for the calculation of intramyocardial pressure and subsequent quantitative evaluation of myocardial perfusion. A one-way coupling framework between the two models was established to enable the evaluation and examination of coronary flow dynamics and myocardial perfusion. Results: Our predicted coronary flow waveforms aligned well with published experimental data. Our model precisely captured the phasic pattern of coronary flow, including impeded or even reversed flow during systole. Moreover, our assessment of coronary flow, considering both globally and regionally averaged intramyocardial pressure, demonstrated that elevated intramyocardial pressure corresponds to increased impeding effects on coronary flow. Furthermore, myocardial blood flow simulated from our model was comparable with MRI perfusion data at rest, showcasing the capability of our model to predict myocardial perfusion. Conclusions: The integrated model introduced in this study presents a novel approach to achieving physiologically accurate simulations of coronary flow and myocardial perfusion. It holds promise for its clinical applicability in diagnosing insufficient myocardial perfusion.

• Item Type: Articles
• Additional Information: Y. Wang acknowledges funding from the Chinese Scholarship Council and the fee waiver from the University of Glasgow.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Yin, Ms Xueqing and Wang, Yingjie
• Authors: Wang, Y., and Yin, X.
• College/School: College of Science and Engineering > School of Mathematics and Statistics
• Journal Name: Computer Methods and Programs in Biomedicine
• Publisher: Elsevier
• ISSN: 0169-2607
• ISSN (Online): 1872-7565
• Published Online: 21 November 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Computer Methods and Programs in Biomedicine 243:107928
• Publisher Policy: Reproduced under a Creative Commons license