Radiomics Analysis of Cardiac Magnetic Resonance Images for Differentiating Fabry Disease from Hypertrophic Cardiomyopathy

Motivation: A timely differential diagnosis of patients with Fabry disease (FD) from those with hypertrophic cardiomyopathy (HCM) is essential for treatment planning. Goal(s): This study aimed to establish a radiomics classification model using CMR cine images to differentiate FD from HCM patients. Approach: Radiomics features were extracted from cine images at end-diastole and end-systole. The random forest (RF) classification model was combined with feature selection methods of mutual information, ANOVA, and Chi2. Results: The MI+RF model demonstrated good performance of AUC=0.92±0.02. Two selected features significantly differed between FD and HCM patients (p<0.05). Impact: The RF classification combined with cine image features selected by MI could distinguish FD from HCM. The selected features included shape and texture categories, illustrating the potential of radiomics features in identifying subtle morphological and myocardial texture changes in FD.