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 (R2, 0.435; C statistic, 0.93; Dxy, 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.