Investigating the hemodynamics of human carotid arteries involves a detailed examination of blood flow dynamics within the individualized vascular structures on the left and right sides of the neck. This study focuses on exploring and analyzing the unique hemodynamic characteristics of these arteries in a subject-specific context, offering valuable insights into blood circulation patterns and fluid dynamics associated with these vital blood vessels. To achieve this, we developed Computational Fluid Dynamics (CFD) prototypes for both the left and right carotid arteries using MRI scans from an individual. These CFD models were simulated under various physiological conditions, and the generated data were analyzed with machine and deep learning models to understand variations in flow characteristics. The findings revealed statistically significant differences in parameters such as wall shear stress and blood velocity between the two (left-sided and right-sided) arteries. Further analysis identified potential unhealthy conditions in the subject's left carotid artery. The Shapely Additive Explanations (SHAP) analysis gave in-depth knowledge, revealing that blood velocity in the common carotid artery (CCA) is the primary factor affecting blood flow in the internal (ICA) and external carotid arteries (ECA). Higher CCA velocity boosts velocities in the ICA and ECA, while lower CCA velocity reduces them. Additionally, blood velocity and viscosity are the main factors influencing wall shear stress (WSS) in each artery segment, with higher values increasing WSS and lower values reducing it. Other factors, like blood density and reference pressure, have minimal impact on blood flow and WSS.
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