Radiomic Analysis in Hepatocellular Carcinoma: Prospects and Clinical Benefits (Review)

Introduction: Hepatocellular carcinoma (HCC) is associated with high mortality due to challenges in early diagnosis, the subjectivity of imaging assessments, and the lack of reliable, non-invasive methods for predicting tumor aggressiveness and treatment response.Purpose: To evaluate the potential and evidence base of radiomic image analysis in addressing key clinical challenges in HCC.Materials and methods: A review of current scientific literature, including Russian and international studies from 2023 to 2025, was conducted. The methodology of radiomics and its effectiveness were analyzed for the following applications: differential diagnosis of HCC, prediction of microvascular invasion (MVI), and evaluation or prediction of the effectiveness of transarterial chemoembolization (TACE) and radiofrequency ablation (RFA).Results: Radiomic models demonstrated high accuracy (with sensitivity up to 96 %) in the differential diagnosis of HCC. The integration of 3D radiomic features with clinical and laboratory data enabled the prediction of MVI, achieving sensitivity rates of 76–82 % and specificity of 82–85 %. Combined clinical–radiomic models showed strong performance in predicting response to TACE (AUC up to 0.92) and RFA (AUC up to 0.87), as well as in assessing recurrence risk—outperforming traditional approaches.Conclusion: Radiomic analysis is a promising non-invasive tool for assessing HCC aggressiveness and guiding treatment selection. It outperforms conventional imaging in predicting MVI and therapeutic response to local treatments such as TACE and RFA.