AUTHOR=Meng Zhuangyuan , Zhang Haishan , Cai Yunhan , Gao Yuan , Liang Changbin , Wang Jun , Chen Xin , Guo Liang , Wang ShengZhang TITLE=Computational study of transcatheter aortic valve replacement based on patient-specific models—rapid surgical planning for self-expanding valves JOURNAL=Frontiers in Physiology VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2024.1407215 DOI=10.3389/fphys.2024.1407215 ISSN=1664-042X ABSTRACT=

Transcatheter aortic valve replacement (TAVR) is a minimally invasive interventional solution for treating aortic stenosis. The complex post-TAVR complications are associated with the type of valve implanted and the position of the implantation. The study aimed to establish a rapid numerical research method for TAVR to assess the performance differences of self-expanding valves released at various positions. It also aimed to calculate the risks of postoperative paravalvular leak and atrioventricular conduction block, comparing these risks to clinical outcomes to verify the method’s effectiveness and accuracy. Based on medical images, six cases were established, including the aortic wall, native valve and calcification; one with a bicuspid aortic valve and five with tricuspid aortic valves. The parameters for the stent materials used by the patients were customized. High strain in the contact area between the stent and the valve annulus may lead to atrioventricular conduction block. Postoperatively, the self-expanding valve maintained a circular cross-section, reducing the risk of paravalvular leak and demonstrating favorable hemodynamic characteristics, consistent with clinical observations. The outcomes of the six simulations showed no significant difference in valve frame morphology or paravalvular leak risk compared to clinical results, thereby validating the numerical simulation process proposed for quickly selecting valve models and optimal release positions, aiding in TAVR preoperative planning based on patients’geometric characteristics.