PROJECT SUMMARY Mitral regurgitation (MR) is a prevalent and deadly disease characterized by the inability of the mitral valve (MV) leaflets to coapt properly, permitting backflow of blood from the left ventricle into the left atrium. The etiologies of MR are complex and diverse, ranging from myxomatous degeneration of the valvular tissue to myocardial infarction to non-ischemic cardiomyopathy. Several types of treatment are available, but the efficacy of these interventions remains suboptimal and unpredictable. One of these options is the relatively recent transcatheter edge-to-edge leaflet clipping technique called the MitraClip procedure (or TEER). Though the procedure is safe, its outcomes in clinical trials, particularly compared to other surgical and therapeutic treatments, have been highly contradictory, largely due to the multifactorial nature of MR. Therefore, it is clear that a predictive approach to treatment selection that accounts for patient specific variations in MV shape and deformation is necessary to optimize long- term patient outcomes. Our group has developed a noninvasive, image-based method for in vivo MV strain estimation which allows us to quantify MV shape and deformation directly from clinically available imaging data. We have also previously demonstrated that this technique can be used to identify predictive, presurgical factors of repair efficacy for ischemic MR patients undergoing undersized ring annuloplasty. However, previous work by our lab and others has focused on limited subsets of MR patients; in order to develop a comprehensive treatment selection guide, simulations must be grounded in a robust understanding of the altered MV biomechanical state in the full range of MR etiologies. Furthermore, the effects of the highly non-physiological focal stress of the MitraClip on the immediate and long-term shape and deformation of the MV leaflets remains almost completely unknown. We will additionally develop a fully predictive finite element simulation of the TEER procedure in order to preoperatively test various MitraClip scenarios directly on a 3D model of the patient's MV apparatus, use our understanding of the MV functional state to predict the 12-month outcomes of each configuration, and select the most optimal option. Therefore, in this study, we aim to (1) establish the pre-operative state of the MV across the MR spectrum and (2) elucidate and predict the consequences of the MitraClip on MV leaflet geometry, behavior, and remodeling in order to explain and ultimately predict the outcomes of this treatment in a patient-specific and quantitative manner.