Fully coupled patient-specific fluid-structure interaction modeling of post-TAVI hemodynamics compared with...

To develop a fully coupled, patient-specific fluid-structure interaction (FSI) framework for quantitative assessment of post-transcatheter aortic valve implantation (TAVI) hemodynamics and valve biomechanics, and to compare selected simulation-derived hemodynamic indices with post-procedural echocardiographic measurements. Patient-specific geometries were reconstructed from pre-operative computed tomography angiography in five subjects treated with SAPIEN 3 Ultra (S3) devices. Structural TAVI deployment was simulated using Abaqus/Explicit and subsequently coupled with FlowVision for performing a two-way post-TAVI FSI analysis. Personalized boundary conditions were derived from clinical measurements, including heart rate, blood pressure, and echocardiographic flow data. Predicted peak velocity, effective orifice area (EOA), and transvalvular pressure gradients (TPG) were quantitatively compared with post-procedural echocardiography using empirical cumulative distribution functions and area-based error metrics. The FSI framework reproduced realistic leaflet kinematics and patient-specific flow patterns, highlighting marked inter-patient variability despite identical device types. Average of predicted peak systolic velocity (2.66 ± 0.59 m/s) and TPG (22 ± 10.7 mmHg) showed good agreement with echocardiographic measurements as the area metric was below 10% for both peak TPG and velocity. Larger discrepancies were observed for EOA due to patient variability and reliability of echocardiographic measurements. The model additionally quantified biomechanical and hemodynamic parameters, including leaflet stress, time-averaged wall shear stress (TAWSS), and blood residence time (BRT). The proposed fully coupled FSI framework enables patient-specific analysis of post-TAVI hemodynamics and valve mechanics for S3 balloon-expandable intra-annular system. The preliminary comparison with echocardiographic measurements showed good agreement for peak velocity and peak TPG, while larger EOA discrepancies highlight the need for further clinical benchmarking using larger cohorts and more direct measurement modalities.