ETD

• CMR
• hypertrophic cardiomyopathy

Background: Current diagnostic criteria for hypertrophic cardiomyopathy (HCM) depend mainly on absolute measurements of left ventricular (LV) wall thickness, often overlooking early phenotypic markers and individual demographic variability. Particularly, the role of wall thickness heterogeneity has been poorly investigated despite its potential relevance in early disease stages and genotype-positive individuals without hypertrophy.
Objectives: To evaluate whether the standard deviation of end-diastolic LV wall thickness (WTSD), a marker of segmental heterogeneity, may serve as an earlier phenotypic feature of HCM, and to compare its diagnostic performance to other wall thickness–derived parameters across healthy controls, mutation carriers without HCM diagnosis, and patients with guideline-based HCM.
Methods: CMR data were analyzed from 382 healthy subjects, 297 patients with established HCM, and 82 genotype-positive individuals without hypertrophy. WTSD and other wall thickness–derived parameters were calculated from short-axis cine images. Age- and sex-specific reference ranges were established in healthy controls. Diagnostic accuracy (sensitivity, specificity, AUC) was assessed for each parameter.
Results: WTSD values were significantly higher in HCM patients (4.3±1.1 mm) and mutation carriers (2.3±0.3 mm) compared to healthy controls (1.3±0.3 mm; p<0.0001 for both). WTSD outperformed all other parameters in distinguishing HCM patients from controls (AUC 0.98, sensitivity 97%, specificity 99%) and was the only metric with substantial discriminatory power in mutation carriers vs. controls (AUC 0.82, sensitivity 64%, specificity 99%). Diagnostic performance was consistently high across both sexes.
Conclusions: WTSD is a highly sensitive and specific marker for diagnosing HCM and may detect early phenotypic expression in genotype-positive individuals without conventional hypertrophy. This parameter should be considered for inclusion in future diagnostic algorithms to enhance early recognition and personalized risk stratification in HCM.