2016 Spring.Includes bibliographical references.Cardiovascular disease is a leading cause of death accounted for 17.3 million people annually. Aortic valve calcification (AVC) and stenosis are the most common diseases among valvular heart diseases. Severe AVC and stenosis will need the standard surgical aortic valve replacement (SAVR) or transcatheter aortic valve replacement (TAVR) for patients who are at high risk for open heart surgery. Post-procedural paravalvular leak (PVL) is a common complication which occurs around the implanted stent in a significant population of patients who undergo valve replacement, requiring significant interventions. The overarching hypothesis of this research is that anatomic characteristics of patients’ native aortic valve play an important role in both calcification processes and post-procedural PVL occurrence. This hypothesis is studied through two specific Aims. Aim 1 was designed to determine what anatomic and biological parameters as well as hemodynamic factors are associated with severity of aortic valve calcification. In this aim, patient-specific geometric characteristics were extracted using 3D image reconstruction of patient CT data, and their relation with cusp specific calcification was evaluated using multiple regression analysis. The results of this analysis indicated that severity of calcification is significantly correlated with coronary calcification as well as the size of sinus of valsava and sinotubular junction (all p-values<0.05). In Aim 2, we investigated the relationship among patients’ calcification level and anatomic parameters of their native aortic valve as well as the risk of post-procedural PVL occurrence. Using a logistic regression analysis model we show that large calcification deposition (p-value<0.001) and large ratio of sinus of valsava to annulus (p-value<0.02) of native aortic valve can predict probability of post-procedural PVL occurrence. The overall significance of this study is that bioengineering analysis of pre-procedural CT data can be utilized towards better TAVR planning as well as basic understanding of the pathogenesis of AVC
