Image-based computational simulation of sub-endothelial LDL accumulation in a human right coronary artery

Abstract

Accumulation of low density lipoproteins (LDL) in the vessel wall is suggested as the initiator of atherosclerosis and coronary stenosis. This process is associated with the performance of endothelium layer that regulates entering of macromolecules to the vessel wall. Therefore, the present study aims to investigate sub-endothelial accumulation of LDL molecules in a coronary tree and predict atherosclerosis prone sites. Non-Newtonian blood flow is simulated for normal and hypertensive conditions through the lumen of a right coronary artery reconstructed from computed tomography (CT) images. A three-pore model is implemented as the endothelium boundary condition and hence, plasma flow and LDL transport are simulated within the arterial wall. Based on the pore model, endothelium pathways divide into normal junctions, vesicles and leaky junctions. Most of LDL molecules pass through the leaky junctions that arise at locations with low wall shear stress (WSS). Results indicate that increase in the number of leaky junctions at branch points with low WSS can lead to both elevated levels of sub-endothelial LDL accumulation and atherosclerosis risk. Findings reveal that at the branch points with disturbed flow, sub-endothelial concentration of LDL for the hypertensive condition is higher than the normal condition, however for the rest of regions with uniform geometry and unidirectional flow, this is reversed. Comparisons of non-Newtonian and Newtonian flows show mean increases of 34% and 13% in the sub-endothelial concentrations of Newtonian flows during the normal and hypertensive conditions, respectively.