Multitask Deep Learning Distinguishes HCM from Hypertensive Heart Disease on Native T1 Maps

A multitask deep learning model classified hypertrophic cardiomyopathy vs hypertensive heart disease on cardiac MRI native T1 maps with AUC 0.941 (95% CI 0.903-0.979), outperforming a clinical baseline AUC 0.757; external 20-patient test AUC 0.885.

• The retrospective single-center study included 174 patients (121 HCM, 53 HHD) with 3.0-T MOLLI native T1 maps, using patient-level stratified fivefold cross-validation.
• The multitask model's segmentation branch reached a Dice coefficient of 0.823, and Mamba baselines were inferior (AUC 0.633-0.719).
• On an independent external test set of 20 patients, the model achieved AUC 0.885 (sensitivity 0.917, specificity 0.625); larger multicenter validation is required.

Automated summary

RadPigeon summaries are original and for information only. They are not clinical advice.