Integrating Computational and Biological Hemodynamic Approaches to Improve Modeling of Atherosclerotic Arteries

• Published in: Advanced science 2024-07, Vol.11 (26), p.e2307627-n/a
• Main Authors: Vuong, Thao Nhu Anne Marie, Bartolf‐Kopp, Michael, Andelovic, Kristina, Jungst, Tomasz, Farbehi, Nona, Wise, Steven G., Hayward, Christopher, Stevens, Michael Charles, Rnjak‐Kovacina, Jelena
• Format: Article
• Language: English
• Subjects: Animals; Atherosclerosis; Atherosclerosis - physiopathology; Blood clots; Calcification; cardiovascular disease; Cell adhesion & migration; Collagen; computational modeling; Computer Simulation; Copyright; Coronary vessels; Cytokines; Endothelium; Growth factors; haemodynamics; Hemodynamics; Hemodynamics - physiology; Humans; Inflammation; Lipids; Models, Cardiovascular; Morphology; Pathophysiology; R&D; Research & development; Review; Smooth muscle; tissue engineering; Tomography; Veins & arteries
• ISSN: 2198-3844; 2198-3844
• DOI: 10.1002/advs.202307627

Atherosclerosis is the primary cause of cardiovascular disease, resulting in mortality, elevated healthcare costs, diminished productivity, and reduced quality of life for individuals and their communities. This is exacerbated by the limited understanding of its underlying causes and limitations in current therapeutic interventions, highlighting the need for sophisticated models of atherosclerosis. This review critically evaluates the computational and biological models of atherosclerosis, focusing on the study of hemodynamics in atherosclerotic coronary arteries. Computational models account for the geometrical complexities and hemodynamics of the blood vessels and stenoses, but they fail to capture the complex biological processes involved in atherosclerosis. Different in vitro and in vivo biological models can capture aspects of the biological complexity of healthy and stenosed vessels, but rarely mimic the human anatomy and physiological hemodynamics, and require significantly more time, cost, and resources. Therefore, emerging strategies are examined that integrate computational and biological models, and the potential of advances in imaging, biofabrication, and machine learning is explored in developing more effective models of atherosclerosis. This review describes and critically evaluates computational and biological models of atherosclerosis, focusing on the hemodynamics of occluded coronary arteries. It examines emerging strategies that integrate computational and biological models and explores the advances in imaging, biofabrication, single‐cell omics, and machine learning for model refinement, validation, and application in discovery research, diagnostics, and drug and medical device development and testing.