Abstract
A vast amount of work has been dedicated to the effects of hemodynamics and cytokines on leukocyte adhesion and trans-endothelial migration (TEM) and subsequent accumulation of leukocyte-derived foam cells in the artery wall. However, a comprehensive mechanobiological model to capture these spatiotemporal events and predict the growth and remodeling of an atherosclerotic artery is still lacking. Here, we present 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. Interestingly, using fully developed steady blood flow does not result in a representative number of leukocyte TEM as compared to pulsatile flow, whereas passing WSS at peak systole of the pulsatile flow waveform does. Moreover, using the model, we have found leukocyte TEM increases monotonically with decreases in luminal volume. At critical plaque shapes the WSS changes rapidly resulting in sudden increases in leukocyte TEM suggesting lumen volumes that will give rise to rapid plaque growth rates if left untreated. 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.
Highlights
Cardiovascular Diseases (CVD) are still the leading cause of death in the United States
Since our goal is to model leukocyte trans-endothelial migration (TEM) and plaque evolution as a function of hemodynamics the wall composition is considered uniform throughout, with no distinction between media and adventitia. 60% of the arterial wall is considered fixed with extracellular matrix (ECM), namely collagen and elastin, and the remaining 40% is composed of cells and soluble factors [45,46,47]
We identified a simplifying assumption for handshaking between the agent based model (ABM) and computational fluid dynamics (CFD) that generated approximately the same total leukocyte transmigration as if we include the complete pulsatile flow history
Summary
Cardiovascular Diseases (CVD) are still the leading cause of death in the United States. The most common cause of CVD is atherosclerosis [1]. Atherosclerosis is a local inflammatory disease characterized initially by the recruitment of leukocytes into the arterial wall. Through a cascade of events the arterial wall may develop a plaque, comprising of leukocyte-derived foam cells, lipids, calcium and other constituents [2]. When an atherosclerotic plaque ruptures, it may block blood flow completely, which results in a possibly life-threating stroke or myocardial infarction. Transmigration through, the endothelium of blood vessels is an essential event in inflammation and the pathogenesis of atherosclerosis. The recruitment steps involved in the leukocyte transmigration cascade (i.e., capture, rolling, activation and adhesion) are well established [4,5,6]; a model which can predict the effects of these events is lacking. We present an agent based model (ABM) for simulating the complex behavior of discrete autonomous agents (i.e. cells) in order to assess their effects on the artery and to deepen the understanding of the pathophysiology of atherogenesis
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