Atherosclerosis in the carotid arteries increases stroke risk, yet current treatment decisions rely mainly on stenosis degree, which poorly reflects individual vulnerability. We present an ultrasound-based computational fluid dynamics (CFD) framework for patient-specific hemodynamic assessment. Using tracked 2D ultrasound and automated segmentation, we reconstructed carotid geometries for five healthy subjects and three patients with severe stenoses. CFD simulations quantified TAWSS, OSI, RRT, and helicity, visualized through risk maps. Healthy arteries showed localized risk near bifurcations, whereas stenosed geometries exhibited extensive disturbed flow and altered helicity patterns. This approach demonstrates the feasibility of ultrasound-driven CFD for personalized risk mapping and highlights helicity's potential as a diagnostic marker.
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