Abstract

Introduction: Current CMR sequences cannot discriminate between different myocardial extracellular space (ECS), including collagen, non-collagen, and inflammation. We sought to investigate if CMR radiomics analysis can distinguish between non-collagen and inflammation from collagen in dilated cardiomyopathy (DCM). Methods: 132 DCM patients were scheduled for an invasive septal biopsy and underwent CMR at 3T incorporating native and post-contrast T1 mapping and late gadolinium enhancement (LGE). The radiomic features were computed from the mid-septal myocardium, near the biopsy region, on native T1, extracellular volume (ECV) map, and LGE images. Principal component analysis was used to reduce the number of calculated radiomic features to five. These features were then used in a regression model to discriminate between non-collagen and collagen ECS. Biopsy samples were used to quantify ECS, myocardial fibrosis, and inflammation. Results: Four histopathological phenotypes were identified as normal (G1, n=20), non-collagenous ECS expansion (G2, n=49), collagenous ECS expansion (G3, n=42), and severe fibrosis (G4, n=21). G2 was associated with the highest risk of myocardial inflammation (65%). While native T1 and ECV provided high diagnostic performance in differentiating G4 (AUC= 0.90 and 0.90), their performance in differentiating between G2 and G3 decreased (AUC= 0.59 and 0.55, respectively). Integration of ECV radiomics provided better discrimination and reclassification between G2 and G3 (AUC= 0.79, net reclassification index 0.83; 95% CI 0.45-1.22, p<0.001). A similar trend was observed with the addition of native T1 radiomics and LGE radiomics. Conclusions: The radiomic features extracted from native T1, ECV, and LGE provided incremental information that may improve our capability to discriminate non-collagenous ECS from collagen and could be useful for detecting subtle chronic inflammation in DCM patients.

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