Computational modeling of atherosclerotic plaque progression through an efficient 3D agent-based modeling approach

Abstract

Since atherosclerosis has been declared as the leading cause of mortality worldwide, the imminent need for the design and development of straightforward computational modeling workflows to improve the existing cardiovascular disease risk stratification models is more important than ever. Agent-based modelling (ABM) is a promising computational approach which can be utilized for decision making in various domains from the healthcare sector to industrial applications. In the present study, we propose a straightforward approach for atheromatic plaque progression in the coronary and peripheral arteries using specialized mathematical models and computational simulations which will enable the accurate prediction of the cardiovascular disease evolution. The model incorporates the realistic 3D geometry of the artery and is the first ABM implemented in C#. According to our results, the 3D ABM was able to simulate the Trans Endothelial Migration of Lymphocytes, Monocytes and Neutrophils, the artery wall cells, endothelium cells and plaque cells reducing the time step for each cycle from 40 seconds to 0.04 seconds per cycle.

TAXINOMISIS: A cloud – based platform for risk profiling and patient specific management of the carotid artery disease

“…The proposed platform has been developed based on the data collected during the clinical study of the TAXINOMIS project [6], [7]. This data has been used to build the relative models and validate them through a set of studies [8], [9], [10], [11], [12], [13], [14], [15].…”