Myocardial late gadolinium enhancement is strongly associated with ventricular arrhythmias in mitral valve prolapse

Abstract

Abstract The prognosis of patients with mitral valve prolapse (MVP) largely depends on the presence of ventricular arrhythmias. This study aims to identify association between Cardiac MRI (CMR) based findings with ventricular arrhythmias in MVP patients. Consecutive patients ( n = 45, mean age 56 ± 17 y) with MVP underwent CMR scans. Premature ventricular beats (PVC) and ventricular tachycardia (VT) were recorded by 24-hour Holter monitoring and exercise stress testing. Myocardial late gadolinium enhancement (M -LGE) was calculated as percentage of left ventricular (LV) mass and was analyzed by tertiles – 1st tertile (0%), 2nd (1–4%) and 3rd tertile ≥ 5% of the LV mass. Mitral annular disjunction (MAD) was measured in millimeters in a 3-chamber steady state free precession (SSFP) sequence. Papillary muscle fibrosis (PM - LGE) presence was recorded using the LGE sequence. The combined clinical endpoint (CEP) was defined as the presence of VT, multiple (> 10%) or multiform PVC, ablation due to ventricular arrhythmia and implantable cardioverter defibrillator insertion. M-LGE > 0% in 27 patients (64%) was recorded. The CEP was documented in 47%, 46% and 93% of the 1st, 2nd and 3rd M - LGE% tertiles, respectively (p value = 0.014). A multivariable logistic regression analysis assessing associations with CEP, including LV ejection fraction, PM-LGE, and M-LGE%, was performed. M - LGE% remains strongly associated with CEP as a continuous variable, as well as in the 3rd tertile: OR 1.43; 95%CI 1.05–1.94, p = 0.02 and OR 13.41 95%CI 1.49–120.67, p = 0.02, respectively. Myocardial fibrosis detected by CMR - LGE, particularly when ≥ 5% of LV mass was strongly associated with arrhythmic risk in MVP. CMR - based fibrosis quantification should be considered in routine evaluation to improve risk stratification.

The authors' abstract, as published at the source. The International Journal of Cardiovascular Imaging, 2026 · DOI ↗