Sensitivity of Post-TAVR Hemodynamics to the Distal Aortic Arch Anatomy: A High-Fidelity CFD Study.

Abstract

Patient-specific simulations of transcatheter aortic valve (TAV) using computational fluid dynamics (CFD) often rely on assumptions regarding proximal and distal anatomy due to the limited availability of high-resolution imaging away from the TAV site and the primary research focus being near the TAV. However, the influence of these anatomical assumptions on computational efficiency and resulting flow characteristics remains uncertain. This study aimed to investigate the impact of different distal aortic arch anatomies-some of them commonly used in literature-on flow and hemodynamics in the vicinity of the TAV using large eddy simulations (LES). Three aortic root anatomical configurations with four representative distal aortic arch types were considered in this study. The arch types included a 90-degree bend, an idealized distal aortic arch anatomy, a clipped version of the idealized distal aortic arch, and an anatomy extruded along the normal of segmented anatomical boundary. Hemodynamic parameters both instantaneous and time-averaged such as Wall Shear Stress (WSS), and Oscillatory Shear Index (OSI) were derived and compared from high-fidelity CFD data. While there were minor differences in flow and hemodynamics across the configurations examined, they were generally not significant within our region of interest i.e., the aortic root. The choice of extension type had a modest impact on TAV hemodynamics, especially in the vicinity of the TAV with variations observed in local flow patterns and parameters near the TAV. However, these differences were not substantial enough to cause significant deviations in the overall flow and hemodynamic characteristics. The results suggest that under the given configuration and boundary conditions, the type of outflow extension had a modest impact on hemodynamics proximal to the TAV. The findings contribute to a better understanding of flow dynamics in TAV configurations, providing insights for future studies in TAV-related experiments as well as numerical simulations. Additionally, they help mitigate the uncertainties associated with patient-specific geometries, offering increased flexibility in computational modeling.