Cardiac Magnetic Resonance Radiomics for Diagnosis, Phenotyping and Risk Stratification of Cardiomyopathies.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is the reference non-invasive imaging modality for evaluating cardiomyopathies, providing comprehensive assessment of cardiac morphology, function, and tissue characterization. Radiomics has recently emerged as an advanced image analysis technique that extracts quantitative imaging biomarkers from routine CMR images, potentially enhancing disease characterization beyond conventional visual assessment. This systematic review summarizes current evidence on the role of CMR-based radiomics in the diagnosis, phenotypic characterization and risk stratification of cardiomyopathies. METHODS: A structured search identified English-language, peer-reviewed studies published up to August 2026 investigating CMR-based radiomics in hypertrophic, dilated, arrhythmogenic, and infiltrative cardiomyopathies, including cardiac amyloidosis, Fabry disease, and cardiac sarcoidosis. Study selection followed PRISMA 2020 guidelines. Methodological quality was assessed using the Methodological Index for Non-Randomized Studies (MINORS) and the Radiomics Quality Score 2.0 (RQS 2.0) The authors have reviewed and edited the output and take full responsibility for the content of this publication. RESULTS: Current evidence indicates that CMR radiomics provides incremental diagnostic information beyond conventional CMR by quantifying myocardial tissue heterogeneity. Radiomic features derived from cine imaging, late gadolinium enhancement, native T1/T2 mapping, and extracellular volume maps showed promising performance in differentiating cardiomyopathy subtypes, distinguishing pathological from physiological remodeling, and identifying infiltrative and inflammatory myocardial diseases. Multiparametric radiomic models generally outperformed individual imaging biomarkers, with preliminary evidence supporting applications in risk stratification and outcome prediction. However, studies were predominantly retrospective, involved small cohorts, used heterogeneous imaging and radiomics workflows, and rarely included external validation. RQS 2.0 assessment demonstrated low-to-moderate methodological quality. CONCLUSIONS: CMR-based radiomics shows considerable potential for improving diagnosis and phenotypic characterization of cardiomyopathies. However, methodological standardization, multicenter prospective validation, and demonstration of incremental clinical value are required before routine clinical implementation.