Prognostic value of feature-tracking right ventricular longitudinal strain in heart transplant recipients.

OBJECTIVES

The prognostic value of cardiac magnetic resonance feature tracking (CMR-FT)-derived right ventricular longitudinal strain (RVLS) post-heart transplantation has not been studied. This study aimed to evaluate the prognostic significance of CMR-FT-derived RVLS, in patients post- heart transplantation and to directly compare its value with that of conventional RV ejection fraction (RVEF).

METHODS

In a cohort of consecutive heart transplantation recipients who underwent CMR for surveillance, RVLS from the free wall was measured by CMR-FT. The composite endpoint was all-cause death or major adverse cardiac events. The Cox regression model was used to examine the independent association between RVLS and the endpoint.

RESULTS

A total of 96 heart transplantation recipients were retrospectively included. Over a median follow-up of 41 months, 20 recipients reached the composite endpoint. The multivariate Cox analysis showed that the model with RVLS (hazard ratio [HR]:1.334; 95% confidence interval [CI]:1.148 to 1.549; p < 0.001; Akaike information criterion [AIC] = 140, C-index = 0.831) was better in predicting adverse events than the model with RVEF (HR:0.928; 95% CI: 0.868 to 0.993; p = 0.030; AIC = 149, C-index = 0.751). Furthermore, receiver operating characteristic curves revealed that the accuracy for predicting adverse events was greater for RVLS than RVEF (area under the curve: 0.85 vs 0.76, p = 0.03).

CONCLUSIONS

CMR-FT-derived RVLS is an independent predictor of adverse events in post-heart transplantation, and its predictive value was better than RVEF. Therefore, our study highlighted the importance of evaluating RVLS for risk stratification after heart transplantation.

KEY POINTS

• CMR-RVLS is an independent predictor of adverse events post-heart transplantation and provides greater predictive value. • CMR-RVLS may help clinicians to risk stratification in heart transplantation recipients.