Cardiovascular magnetic resonance feature tracking for rejection surveillance after cardiac transplantation.

BACKGROUND

Endomyocardial biopsy (EMB) is the standard invasive method for monitoring acute cardiac allograft rejection (ACAR); however, non-invasive alternatives are increasingly proving to be dependable.

OBJECTIVES

We aimed to identify and validate dependable cardiovascular magnetic resonance (CMR) strain indices for ACAR detection.

METHODS

We analyzed 160 CMR scans, including long- and short-axis cines, as well as T1/T2 maps from 54 transplant recipients. Uniparametric and multiparametric models integrating left ventricular strain metrics and tissue characteristics were developed to classify histological rejection grades (0, 1 R, ≥2 R) and evaluate therapeutic response.

RESULTS

Regression analysis using generalized linear mixed-models identified significant differences between rejection groups, with global radial strain (GRS) (z-value = 3.1, p = 0.002) and global circumferential strain (GCS) (z-value = 2.5 p<0.008) outperforming global longitudinal strain (GLS) in discriminating ≥2 R from 1 R rejection. Diagnostic performance for detecting ≥2 R rejection was excellent, particularly for GCS (AUC = 0.852, negative predictive value [NPV] = 98.3%) and GRS (AUC = 0.826, NPV = 95.8% (95.8/100)), with enhanced accuracy in the anterolateral mid-basal segments (AUC>0.886, NPV>97.9%). Strain metrics effectively monitored recovery post-therapy for ≥2 R rejection, showing significant improvements (GRS Δ24.5±7.1%, GCS Δ15.9±4.6%, GLS Δ27.4±11.8%, all p<0.02). Furthermore, as strained-based detection of ≥2 R rejection correlated with increases in edema detected using T1/T2 mapping (all p<0.001), integrating strain with T1/T2 mapping significantly enhanced diagnostic accuracy, with T2+GRS (AUC = 0.931, NPV = 98.2) and T1+T2+GCS (AUC = 0.943, NPV = 97.5) as the most effective models.

CONCLUSION

Segmental CMR strain analysis demonstrates excellent diagnostic accuracy and negative predictive value for detecting high-grade ACAR and monitoring post-therapy recovery. This non-invasive approach, particularly when integrated with multiparametric models combining global strain and tissue mapping, has the potential to reduce reliance on invasive EMBs for ACAR surveillance in cardiac transplant recipients.