Computational Modeling of Transcatheter Aortic Valves

Transcatheter aortic valve replacement (TAVR) is an established therapy alternative to surgical valve replacement in high-risk and intermediate-risk patients with severe aortic stenosis. Currently, although TAVR is an alternative and less-invasive treatment for highrisk and intermediate-risk patients, surgical aortic valves replacement (SAVR) was still considered as the gold standard for low-risk patients. TAVR could potentially be applied to lower-risk younger patients if the indications can be safely expanded to the patients and transcatheter aortic valve (TAV) long-term durability can match with that of surgical bioprostheses. In contrast to surgical aortic valves (SAVs), there have been limited clinical data on the long-term durability of TAV devices. In the absence of enough long-term valve durability data, accurate structural simulations and computational modeling become an integral part of the evaluation. Thus, the objectives of this dissertation were to employ invitro experiments and inverse finite element (FE) analyses to obtain accurate material properties of soft tissue employed in commercial available TAVs and then to implement them in computational simulations to determine leaflet stress and strain distributions for proper assessment of the TAVs long-term durability. Therefore, the main goal of this study was to develop an automated computational framework to minimize the peak stress on the leaflets under and optimize the TAV leaflet shape under physiological loading conditions.