Ultrasounic-radiomics models for predicting the response to Atezolizumab plus Bevacizumab in patients with unresectable hepatocellular carcinoma

Abstract

Background Atezolizumab plus Bevacizumab is an effective treatment for unresectable hepatocellular carcinoma, but the assessment methods are limited. Objective To establish an early predictive model using Ultrasounic-radiomics (UR) for predicting the therapeutic efficacy of Atezolizumab plus Bevacizumab in unresectable hepatocellular carcinoma. Methods We retrospectively analyzed 170 patients with unresectable hepatocellular carcinoma, extracting 1560 imaging features pre- and one-week post-treatment. Separate UR models were established to predict treatment efficacy. Model performance was evaluated using calibration curves and the area under the receiver operating characteristic curve (AUC). Results Two UR models were ultimately established. The pre-treatment UR model achieved an AUC of 0.790 in the train group and 0.706 in the validation group. The post-treatment UR model achieved an AUC of 0.855 in the train group and 0.704 in the validation group. Using a cutoff value of 0.528 to divide patients into high-risk and low-risk groups, the Kaplan-Meier survival curves showed statistically significant differences between the two groups. The hazardous and moderate-risk groups’ Kaplan-Meier survival curves revealed statistically significant distinctions. Conclusion The UR models show promise in predicting the efficacy and prognosis of combined targeted therapy and immunotherapy in unresectable hepatocellular carcinoma, particularly highlighting the importance of ultrasound assessments three months post-treatment.