Predictive value of deep learning-based cardiac ultrasound flow imaging for hypertrophic cardiomyopathy complicated with arrhythmias

AIM To explore the predictive value of deep learning-based cardiac ultrasound flow imaging for hypertrophic cardiomyopathy (HCM) complicated with arrhythmias.

METHODS The clinical data of 90 patients with hypertrophic cardiomyopathy from March 2020 to March 2023 were retrospectively collected. Based on the ratio of 4:1:1, they were divided into training group (60 cases), validation group (15 cases) and test group (15 cases) , and based on HCM complicated with arrhythmia or without arrhythmia, the cases in training group were divided into concurrent group and non-concurrent group. A deep learning model for cardiac ultrasound flow imaging was established, and image data, LVEF, LAVI, E/e’, vortex area change rate, circulation intensity change rate, mean blood flow velocity and mean EL value were extracted.

RESULTS The differences in general data between the three groups were not statistically significant and the differences in general data between patients in concurrent group and non-concurrent group in the training group were also not statistically significant But the LAVI, E/e’, vortex area change rate, circulation intensity change rate, mean blood flow velocity and average EL of concurrent group were significantly higher than those of non-concurrent group, while LVEF was significantly lower than that of non-concurrent group (P<0.05 or P<0.01). Multivariate logistic regression scores showed that vortex area change rate, circulation intensity change rate, mean blood flow velocity, mean EL, LAVI, and E/e’ were all risk factors for arrhythmia in HCM, while LVEF was a protective factor for arrhythmia in HCM. The AUC values of ROC curve in training group, validation group and test group were 0.985, 0.989 and 0.980, respectively.

CONCLUSION Deep learning-based cardiac ultrasound flow imaging can more accurately identify cardiac ultrasound images and has a high predictive value for hypertrophic cardiomyopathy complicated with arrhythmias. Vortex area change rate, circulation intensity change rate, mean flow velocity, mean EL, LAVI, and E/e’ are all risk factors for hypertrophic cardiomyopathy complicated with arrhythmias. LVEF is a protective factor for HCM accompanied by arrhythmia.