Assessing Near-Wall Hemodynamics of Blood Flow in the Left Anterior Descending Segment of the Left Coronary Artery Using Computational Fluid Dynamics

Abstract

The objective of this study was to computationally investigate the flow mechanics and the near-wall hemodynamics associated with the different take-off angles in the left coronary artery of the human heart. It is hypothesized that increasing the take-off angles of the left coronary artery will significantly increase or decrease the likelihood of plaque (atherosclerosis) buildup in the left coronary artery bifurcations. Specifically, this study quantified the effects of the varying take-off angles on the branches along the left anterior descending (LAD) of the left coronary artery using computational fluid dynamics (CFD) simulations. The study compared five test cases of the different take off-angles of the left coronary artery (LCA) and four different branch angles between the LAD and the left circumflex (LCx). It also considered the branch angles of the coronary artery downstream the LAD. The LCA inlet boundary conditions was set as a pulsatile mass flow inlet and flow split ratios were set for the outlets boundary conditions. The nature of blood pulsatile flow characteristic was accounted for and the properties of blood which include the density (1,050 kg/m3) and dynamic viscosity (0.0046 Pa-s) were obtained from previous research. The results from the simulations are compared using established scales for the parameters evaluated. The parameters evaluated were: (i) Oscillatory Shear Index (OSI); which quantifies the extent in which the blood flow changes direction during a cardiac cycle (ii) Time Average Wall Shear Stress (TAWSS); which quantifies the average shear stress experienced by the wall of the artery and (iii) Relative Residence Time (RRT); which quantifies how long blood spends in a location along the artery during blood flow. These parameters are used to predict the likelihood of blood clots, atherosclerosis, endothelial damage, plaque formation, and aneurysm in the blood vessels. The data from the simulations were analyzed using functional macros to quantify and generate threshold values for the parameters.