To develop a spatiotemporal hybrid perception deep learning (DL) model using contrast-enhanced ultrasound (CEUS) videos for diagnosis of hepatocellular carcinoma (HCC) in liver imaging reporting and data system (LI-RADS) category LR-M liver nodules.

This study conducted a retrospective analysis of patients diagnosed with LR-M nodules by CEUS from the First Affiliated Hospital of Sun Yat-sen University and the First Affiliated Hospital of Guangxi Medical University. Using pathological and comprehensive diagnostic results as the gold standard, the patients were categorized into HCC and non-HCC. A multi-scale spatiotemporal split-phase parallel feature extraction of CEUS video using R(2+1)D-18 convolutional neural network is used to construct a diagnostic model for HCC, and the information integrity and computational efficiency are balanced by a frame sampling strategy (15/30/45 frames), supplemented by gradient-weighted class activation mapping (Grad-CAM) visualisation to explain the decision basis. The diagnostic efficacy of the model is evaluated using accuracy, sensitivity, specificity, positive predictive value, negative predictive value and receiver operating characteristic (ROC) curve.

A total of 176 LR-M patients from the First Affiliated Hospital of Sun Yat-sen University were divided into training and validation sets in a 7:3 ratio, while 46 LR-M patients from the First Affiliated Hospital of Guangxi Medical University served as the test set. When using 45-frame videos as input, with sensitivities of 91.67% and 84.21%, specificities of 96.43% and 81.48%, and area under curves (AUCs) of 0.940 and 0.828 in the validation and test sets. The model had a higher detection rate of HCC compared with the alpha-fetoprotein (AFP) index (validation set: 50.00%, test set: 31.58%; both P value < 0.05), and the combined use of the DL model with AFP could optimize the overall diagnostic efficacy.

The DL model with CEUS spatiotemporal perception enables accurate diagnosis of HCC in LR-M category liver lesions, demonstrating significantly superior performance over AFP. Moreover, the combined diagnosis of the both can reduce unnecessary liver biopsy.