The influence of inlet flow asymmetry on the carotid bifurcation hemodynamics

Abstract

Abstract Arterial bifurcations are known to be high-risk areas for the initiation of atherosclerosis. The appearance and growth of atherosclerotic plaques in the bifurcation of the carotid artery can result in severe consequences such as cerebrovascular accidents. The common signs of an atherogenic risk center around the surpassing critical values by certain hemodynamic indices, which are distributed over the artery wall. These indices are related to the effect of blood flow on the arterial wall, and their distribution is influenced by both the bifurcation’s geometric shape and the flow structure at its inlet. The objective of this study is to carry out a comparative analysis of hemodynamic indices in personal-specific models of carotid bifurcation with centrally symmetric and asymmetric input flows. The examined geometric models of bifurcation are based on computed angiography data obtained from the individuals free of apparent pathology. By using computational fluid dynamics within these models, the distribution of hemodynamic indices in a steady periodic flow is calculated and critical zones are determined for them. All the models are divided into two groups – those with symmetric and those with asymmetric input flows. For each model with asymmetric input flow, an alternative geometry is designed to ensure inlet flow symmetry, and comparative numerical calculations of the blood flow are carried out. The results of comparative analysis reveal that the distribution of hemodynamic indices is simpler for the group with symmetric input flow. A comparison of the averages between these two groups with symmetrical and natural asymmetric input flows indicates a 55% better result for the latter group. Furthermore, for almost all models with asymmetric input flow, their alternative models give worse hemodynamic results. Thus, hemodynamic indices in simpler models with symmetrical input flow can serve as an upper estimate for indices in models with natural asymmetric flow. A total of 89 models are included in the study.