Abstract 9848: Image Guided Computational Model of the Mitral Valve in Heart Failure with Functional Mitral Regurgitation - A Platform for Preclinical Procedure Planning

Abstract

Introduction: Therapeutic benefit of correcting functional mitral regurgitation (FMR) is increasingly recognized, since positive results from COAPT trial indicate a significant reduction in hospitalization rate and mortality. However, this benefit is strongly dependent on the extent of reduction in FMR with the MitraClip system, which is often variable and unpredictable. We report a patient-specific, 3D echo derived computational model of the mitral valve that faithfully mimics the FMR-like valve for procedure planning. Methods: FMR datasets were obtained in two pigs that received a myocardial infarction via percutaneous occlusion of the left circumflex artery. 3D echo was performed 3 months after infarction, and images were segmented to obtain annular and leaflet geometry, and papillary muscle (PM) locations in the ventricle. Chordal distribution was developed (Fig. A) based on anatomical measurements in hearts as they are not visible on echo. The PMs were sub-divided into three heads with marginal, strut and basal chordae emerging from these heads as seen in real hearts (Fig. B) . In FMR state, the PM locations are displaced, imposing a pre-strain on the chordae. Valve closure simulation was modeled by pre-straining the chordae and applying transvalvular pressure gradient on the leaflets, and stress analysis was performed. Results: Agreement in the truth dataset (echo image) and the model (simulated data) are shown in Fig. C , indicating fidelity of the model. Peak stresses were observed on A2 and P2 segments near the strut chordae insertion regions with maximum values of 7.62 and 4.93 MPa for each dataset (Fig. D) , which corresponds well with the previously reported findings. Conclusions: A proposed FMR modeling workflow allowed to obtain a realistic systolic configuration of the mitral valve. Such models may be used to virtually implement various FMR repair techniques, allowing to predict post-repair outcomes and optimize FMR repair at a patient-specific level.