Assessment of Left Ventricular Myocardial Fibrosis in Adult Patients With Ebstein Anomaly: A Retrospective Cohort Study Based on Cardiac Magnetic Resonance and Histopathological Samples

Background: The association between Ebstein anomaly and myocardial fibrosis, particularly in the left ventricle, has been controversial. We aimed to assess the prevalence of replacement fibrosis with a focus on the left ventricle (LV) using cardiac magnetic resonance (CMR), make a histopathological association between LV fibrosis and CMR findings, and explore whether LV fibrosis is an independent risk factor for cardiovascular disease mortality using a derived risk score. Methods: We performed a 12-year (2009–2021) retrospective cohort of adult patients with Ebstein anomaly who underwent CMR. The CMR evaluation included a comprehensive assessment of myocardial fibrosis by late gadolinium enhancement (LGE). Four postmortem samples were obtained from our cohort and stained using Masson trichrome to characterize LV fibrosis. We used Cox-regression analysis to identify and derive a prediction score that associated LV fibrosis with cardiovascular disease mortality. Results: We included 57 adults with Ebstein anomaly (52% men; median age, 29.52 [interquartile range, 21.24–39.17] years), of whom 12 died during follow-up. LGE prevalence by CMR was observed in 52.6% in any chamber; LV-LGE in 29.8%. Histopathological findings revealed a mid-wall pattern with predominantly interstitial fibrosis and minimal replacement fibrosis. LV-LGE was associated with increased risk of cardiovascular disease mortality (hazard ratio, 6.02 [95% CI, 1.22–19.91]) attributable to lateral and mid-wall LV segment involvement. Our mortality score achieved an overall good prediction capacity (R 2 , 0.435; C statistic, 0.93; D xy , 0.86). Conclusions: There is a high prevalence of LV fibrosis replacement in adults with Ebstein anomaly, characterized by specific CMR and histological patterns. Furthermore, LV-LGE fibrosis is an independent predictor of cardiovascular disease mortality, which could be integrated into risk assessment in clinical management.