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Updated: Jan 11, 2026

Four-Dimensional Computed Tomography-Guided Valve Sizing for Transcatheter Pulmonary Valve Replacement
Published on: January 20, 2022
The Virtual Transcatheter Aortic Valve Replacement (VTAVR) framework predicts optimal device landing zones tailored
Mohamed Abdelkhalek1, Zahra Keshavarz-Motamed1,2,3
1School of Biomedical Engineering, McMaster University, Hamilton, ON Canada.
Abstract:
VTAVR, a novel simulation for Transcatheter Aortic Valve Replacement (TAVR), optimizes device placement using routine patient-specific CT angiography data. It integrates image processing, geometric reconstruction, and centerline estimation for accurate valve deployment. The framework employs a kinematic simulator to optimize valve performance by adjusting parameters like expansion area, anchoring depth, and implantation height, aiming to reduce complications such as paravalvular leaks (PVL) and left bundle branch block (LBBB). In this retrospective study (N = 40; pre and post TAVR), VTAVR demonstrated high fidelity with average Surface Error of pre CT simulated device versus in-vivo post CT stent frame (L2 Norm) Median: 0.633 mm; IQR= [0.216-1.37 mm]. Median post-TAVR CT device diameters were 24.4 mm [22.0-25.9 mm] at the outflow, 24.4 mm [22.5-26.0 mm] at the midflow, and 24.9 mm [22.9-26.7 mm] at the inflow, showing no significant differences compared to VTAVR simulations (p < 0.001). Median implantation height was 8.1 mm [6.9-10.4 mm] vs 7.2 mm [6.7-8 mm], with VTAVR predicting similar heights (p < 0.05). Additionally, VTAVR accurately predicted the area cover index, with a median of 101.4% [91.9-105.3%] closely matching post-TAVR CT (p < 0.01). The system provides assessments of peri-procedural risk factors by quantifying geometrical "safety" margins, aiming to minimize common complications such as improper implantation depth and over-expansion. VTAVR's simulation of various deployment scenarios allows clinicians to foresee and address potential complications effectively, marking a significant advance in personalized cardiac interventions through virtual, non-invasive pre-procedural optimization.
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