Background. Mitral valve (MV) abnormalities, such as mitral valve prolapse and mitral annular disjunction (MAD/MVP), are associated with ventricular arrhythmias. However, precise mechanisms connecting specific valve morphologies to arrhythmias remain poorly understood. Our recent unpublished findings from statistical shape analysis identified left ventricle (LV) shape modes significantly associated with arrhythmia prevalence. This work further integrates our findings with analysis of MV structure. Methods. We introduced quantitative metrics derived from medial cardiac MRI long-axis views in a patient cohort of MAD and MVP (n=63) from Oslo University Hospital, engineered to capture specific aspects of leaflet geometry (including arc length and tortuosity) and valve conformation (such as tenting area). Statistical analyses investigated associations between these metrics, previously identified shape modes, myocardial tissue characteristics derived from clinical imaging (e.g. diffuse fibrosis), and clinical outcomes. Results. Significant connections emerged between MV morphology and LV structure. LV shape modes correlated with mitral annular dimensions (e.g., M1 r=0.28, M2r=0.51 with systolic diameter) and diffuse myocardial fibrosis (M1 r=0.37, M5 r=0.39). M5 also strongly negatively correlated with mid-inferolateral wall thickness (r=-0.6) and positively with MV arc length (r=0.33). An arrhythmia-linked mode, M3, negatively correlated with diffuse fibrosis (r=-0.31) and anterior leaflet tortuosity (r=-0.4). In addition, increased leaflet arc length was significantly associated with arrhythmias and strongly correlated with systolic MA diameter (r=0.56). Tenting area correlated positively with annular size (r=0.44), wall thickness (r=0.39), and diffuse fibrosis (r=0.43). Conclusion. Quantitative analysis integrating LV shape modes and MRI-derived MV metrics reveals links between valve structure, myocardial fibrosis, LV remodeling, and arrhythmia in MAD/MVP. Further exploration of these MRI-derived biomarkers could refine understanding of arrhythmic MV disease and improve risk stratification strategies for MAD/MVP patients.