| dc.description.abstract |
Cerebrovascular diseases, including ischemic stroke and intracranial hemorrhage, remain leading global health burdens. The Circle of Willis (CoW), a critical arterial network for cerebral perfusion, is highly influenced by hematological factors, such as blood viscosity and hematocrit levels, as well as anatomical variations like hypoplasia, agenesis, and asymmetry. This study employs Computational Fluid Dynamics (CFD) simulations on patient-specific CoWs’ geometries to investigate the combined impact of hematocrit variation, stenosis morphology, and anatomical abnormalities on intracranial hemodynamics. Using ANSYS software and modeling blood as a non-Newtonian Carreau fluid under pulsatile flow, key hemodynamic indices as wall shear stress (WSS), time average wall shear stress, oscillatory shear index, velocity, translesional pressure ratio, pressure drop index, and stroke risk index, were computed to characterize cerebrovascular behavior under diverse physiological and pathological states. The influence of varying hematocrit levels on wall shear stress and cerebral perfusion is observed using computational fluid dynamics models in normal and aneurysmal geometries. Elevated hematocrit increased blood viscosity and WSS, while lower hematocrit led to reduced shear forces. The WSS-viscosity relationship was nonlinear: low WSS regions were linked to endothelial apoptosis and aneurysm formation, whereas high WSS areas correlated with increased rupture risk. Stenosis geometry and CoW integrity as key determinants of hemodynamic cooperation were identified through nine design of experiments framework. Irregular stenosis and anatomical incompleteness impaired collateral flow, particularly during occlusion, elevating ischemic susceptibility. Hemodynamic metrics indicated that local stress variations promoted atherogenesis and increased thromboembolic risk. Results emphasize the correlation among CoW morphology, hematological factors, and flow dynamics in cerebrovascular pathology. CFD modeling, integrated with clinical data, offers a robust platform for individualized risk assessment and therapeutic planning. Future research incorporating real-time imaging and AI-driven analysis may enhance predictive accuracy and improve stroke prevention strategies.
Keywords: Stroke; Ischemic Stroke; Hematological and Morphological Variation; Circle of Willis; Cerebrovascular Hemodynamics; Computational Fluid Dynamics |
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