Hypertrophic cardiomyopathy (HCM) is one of the leading causes of sudden cardiac death (SCD), particularly in young and middle-aged individuals. Current arrhythmic risk stratification mainly relies on clinical and imaging-based models, including the ESC HCM Risk-SCD score and guideline-recommended risk markers. However, these approaches show only moderate predictive accuracy at the individual level, highlighting the need for novel biomarkers able to improve risk prediction.
Cardiac magnetic resonance (CMR) plays a central role in phenotypic characterization and prognostic assessment of HCM, particularly through the evaluation of late gadolinium enhancement (LGE), a marker of myocardial fibrosis. Recent studies suggest that radiomic analysis of LGE images can identify quantitative features of myocardial scar heterogeneity that provide additional prognostic information beyond conventional fibrosis burden assessment. Radiomics applied to pre-contrast cine CMR sequences may also capture quantitative features related to myocardial shape, texture, and contractile dynamics, potentially associated with myocardial disarray, mechanical alterations, and electromechanical instability.
Integration of CMR radiomics with genetic data may allow a more comprehensive characterization of the arrhythmic substrate in HCM. In obstructive hypertrophic cardiomyopathy (oHCM), left ventricular outflow tract obstruction is a major determinant of symptoms and prognosis. Mavacamten, a selective cardiac myosin inhibitor, has been shown to significantly reduce LVOT gradient and improve symptoms and cardiac remodeling. However, it remains unknown whether CMR radiomics can detect phenotypic changes associated with mavacamten treatment and whether these changes may contribute to dynamic reassessment of arrhythmic risk.