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Abstract #4123

Convolutional neural networks to differentiate hypertrophic cardiomyopathy from hypertensive heart disease based on cardiac cine imaging

Qiming Liu1, Yezi Chai1, Meng Jiang1, and Chenxi Hu2
1Department of Cardiology, Ren Ji Hospital,Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Institute of Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, shanghai, China


Differentiating hypertrophic cardiomyopathy (HCM) from hypertensive heart disease (HHD) is important yet challenging. In this study, we compared 9 convolutional neural network (CNN) models based on cardiac MR cine imaging only for differentiation of the two diseases. We show that the dynamic information contained in cine about myocardial contraction and relaxation is crucial for accurate differentiation. By leveraging this information, we achieved a testing accuracy of 86.8% ± 3.5% in a cohort including 190 HCM and 113 HHD subjects. The results show that cine-based CNN is reasonably accurate for differentiation of HCM and HHD.

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