Contemporary Review on Multi-Modality Imaging Evaluation and Management of Functional Mitral Regurgitation

Functional mitral regurgitation (FMR) is a prevalent valvular disorder driven by adverse remodeling of the left ventricle and/or left atrium. This review synthesizes the contemporary evidence on multimodality imaging and its role in mechanism-specific evaluation and management of FMR, with particular emphasis on distinguishing ventricular FMR (VFMR) from atrial FMR (AFMR). FMR is mechanistically heterogeneous, requiring precise phenotyping to guide therapy. A mechanism-based framework differentiating VFMR, driven by left ventricular dilation and leaflet tethering, from AFMR, driven by left atrial and annular enlargement with preserved ventricular function, is central to contemporary management. Echocardiography remains the cornerstone for real-time assessment of MR severity, hemodynamics, and valve–ventricle interactions. Cardiac magnetic resonance (CMR) provides the gold standard for volumetric quantification and myocardial tissue characterization, enabling improved risk stratification by assessing ventricular remodeling and fibrosis. Computed tomography (CT) offers high-resolution anatomic phenotyping and is essential for procedural planning, particularly for transcatheter edge-to-edge repair (TEER) and transcatheter mitral valve replacement (TMVR). Integration of multimodality imaging supports individualized selection between guideline-directed medical therapy alone, TEER, surgical intervention, or TMVR, based on the dominant mechanism and myocardial substrate. The discordant outcomes of landmark trials such as MITRA-FR and COAPT have underscored the importance of precision in patient selection, highlighting the controversial but clinically relevant proportionate/disproportionate FMR framework and the extent of myocardial fibrosis as key modifiers of treatment response. Emerging advances in advanced imaging and artificial intelligence hold promise for automated phenotyping, improved reproducibility, and earlier identification of patients most likely to benefit from intervention, ultimately enabling a more personalized, mechanism-driven approach to improving outcomes in FMR.