Work

B-mode ultrasound and contrast-enhanced ultrasound-based radiomics interpretable analysis for the prediction of macrotrabecular-massive subtype of hepatocellular carcinoma

Year: 2025

Type: article

Abstract: Background This study aimed to develop and validate an interpretable radiomics model using quantitative features from B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) for predicting macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC). Methods From October 2020 to September 2023, 344 patients (mean age: 58.20 ± 10.70 years; 275 men) with surgically resected HCC were retrospectively enrolled from three medical centers. Radiomics features were extracted from BMUS and CEUS, followed by a multiple-step feature selection process. BMUS R model (based on BMUS radiomics features), BM + CEUS R model (based on BMUS and CEUS radiomics features) and hybrid R+C model (integrated clinical indicators and radiomic features) were established. These radiomics models’ performance was compared with conventional clinic-radiological (C C+R ) model using area under the receiver operating characteristic curve (AUC). SHapley Additive exPlanations (SHAP) method was used to interpret model performance. The model’s potential for predicting recurrence-free survival (RFS) was further analyzed. Results Among ten distinct machine learning classifiers evaluated, the AdaBoost algorithm demonstrated the highest classification performance. The AUCs of the BM + CEUS R model for identifying MTM-HCC were higher than the BMUS R model and the conventional clinic-radiological model in both validation (0.880 vs. 0.720 and 0.658, both p < 0.05) and test sets (0.878 vs. 0.605 and 0.594, both p < 0.05). No statistical differences were observed between the BM + CEUS R model and the hybrid R+C model in either set ( p > 0.05). Additionally, the AdaBoost-based BM + CEUS R model showed promising in stratifying early recurrence-free survival, with p < 0.001. Conclusion The AdaBoost-based BM + CEUS R model shows promise as a tool for preoperatively identifying MTM-HCC and may also be beneficial in predicting prognosis.

Source: The Ultrasound Journal

DOI: 10.1186/s13089-025-00452-2