Available herein is a multiscale model of leukocyte TEM and plaque evolution in the left anterior descending (LAD) coronary artery. The approach integrates cellular behaviors via agent-based modeling (ABM) and hemodynamic effects via computational fluid dynamics (CFD). In this computational framework, the ABM implements the diffusion kinetics of key biological proteins, namely Low Density Lipoprotein (LDL), Tissue Necrosis Factor alpha (TNF-α), Interlukin-10 (IL-10) and Interlukin-1 beta (IL-1β), to predict chemotactic driven leukocyte migration into and within the artery wall. The ABM also considers wall shear stress (WSS) dependent leukocyte TEM and compensatory arterial remodeling obeying Glagov’s phenomenon. Overall this multi-scale and multi-physics approach appropriately captures and integrates the spatiotemporal events occurring at the cellular level in order to predict leukocyte transmigration and plaque evolution.
Atherosclerosis affects millions of people worldwide and is characterized by a plaque , build-up of fatty material, leukocytes, and extracellular matrix inside the artery wall. Over time plaque enhances and blocks blood flow thereby altering the hemodynamics. If the plaque ruptures, the occlusion may cause a life-threating stroke or myocardial infarction. Although it is known that local biochemical and hemodynamics influence leukocyte adhesion and trans-endothelial migration (TEM) into the wall, their effects on the growth rates of plaques are less known. There-fore, we have developed a three-dimensional computational approach to appropriately capture and integrate crucial spatiotemporal events, in order to predict leukocytes migration from the blood into the artery wall. The approach integrates cellular behaviors via agent-based modeling (ABM) and hemodynamic effects via computational fluid dynamics (CFD). Collectively, understanding how mechanobiological events are integrated within an artery will help eluci-date emergent behaviors and predict plaque evolution.