Computer simulation help predict the frame deformation following a Venus-A transcatheter aortic valve implantation in patients with pure aortic regurgitation: a retrospective study.

Abstract

Background: Patient-specific computer simulation of transcatheter aortic valve implantation (TAVI) predicts the interaction between an implanted device and the surrounding anatomy. In this study, we validated the predictive value of computer simulation for the frame deformation following a Venus-A TAVI implant in patients with pure aortic regurgitation (AR). Furthermore, we used the validated computational model to evaluate the anchoring mechanism within the same cohort.

Methods: This was a retrospective study. FEops HEARTguide technology was used to simulate the virtual implantation of a Venus-A valve model in a patient-specific geometry. The predicted frame deformation was quantitatively compared to the postoperative device deformation at multiple levels. The outward forces acting on the frame were extracted for each patient and the total outward force acting around the aortic annular (AA) and sinotubular junction (STJ) planes were recorded.

Results: Thirty patients were enrolled in the study with 10 in the migration group and 20 in the non-migration group. The dimensions of the simulated and observed frames had good correlations at Dmax (R²=0.88), Dmin (R²=0.91), perimeter (R²=0.92), and area (R²=0.92). The predicted outward force acting on the frame at the AA level was comparable between the migration and no-migration groups. The predicted outward force acting on the frame at the STJ level was always significantly higher in the migration group than the no migration group at different bandwidths: 3 mm (P=0.002), 5 mm (P=0.005), 10 mm (P=0.002).

Conclusions: Patient-specific computer simulation of TAVI accurately predicted frame deformation in Chinese patients with pure AR. The forces at the STJ facilitated stabilization of the device within the aortic root, which might be used as a discriminator to identify patients at risk of device migration prior to intervention.