Abstract
Aortic valve replacement is a cornerstone treatment for severe aortic valve diseases, including stenosis and regurgitation. Suboptimal valve seating can elevate the transvalvular pressure gradient, while valve orientation and size may produce flow jets that impinge on the ascending aorta, potentially weakening the vessel wall. Such hemodynamic complications can compromise valve performance and patient outcomes. This study presents a computational fluid dynamics framework, derived from medical CT images, for preprocedural hemodynamic assessment of aortic valve replacement. The framework minimizes user input and delivers rapid results, enabling efficient evaluation of valve types, orientations, and their hemodynamic impact. The results demonstrate that non-optimal implantation angles substantially increase pressure drop across the valve, thereby imposing higher workload on the heart. This automated and efficient simulation framework demonstrates strong potential for clinical application, supporting precise planning and execution of valve implantation procedures to improve patient care.