Use Case: Agent-Based Modeling for Atherosclerotic Plaque Progression in Carotid Arteries

Atherosclerosis is an inflammatory disease characterized by artery stenosis due to plaque formation composed of various elements such as foam cells, lipids, cholesterol, cellular waste products, elastin, collagen, fibrin, calcium, and others. Atherosclerosis within carotid arteries can lead to serious consequences, such as stroke and transitional ischemic attack (TIA). In order to timely predict plaque evolutions and patient state, this study introduces a novel computational model for simulation of plaque progression in the carotid artery, employing an agent-based method (ABM) coupled with finite element method (FEM) and using 3D patient-specific models of carotid arteries. The ABM is linked with an initial wall shear stress (WSS) profile, inducing pathological vascular remodeling by perturbing baseline cellular activity, promoting lipid infiltration, and facilitating accumulation within the arterial wall. In this model, the ABM incorporates shear stress and low-density lipoprotein (LDL) initial distribution from the lumen, initiating iterative calculations within the wall for lipid infiltration and accumulation, using a random number generator at each time step. After ABM iterations, both wall lipid distribution and wall geometry are changed. The fluid-structure solver runs, recalculating the lumen domain. The presented results demonstrate promising agreement between the proposed method and clinical measurements. This approach which integrates ABM and FEM for patient-specific models has potential for predicting the evolution of atherosclerotic plaque and can be used to address the needs for stratified and timely therapeutic vascular interventions in the era of personalized medicine.