Radiomics predicts poorly differentiated hepatocellular carcinoma and uncovers ribosomal-immune dysregulation mechanism.

ABSTRACT: Hepatocellular carcinoma (HCC) shows marked spatial heterogeneity, limiting biopsy-based Edmondson-Steiner (ES) grading. We developed a multicenter radiogenomic framework to noninvasively predict ES grade and explore underlying molecular mechanisms. Arterial-phase DCE-MRI from 295 patients and The Cancer Imaging Archive (TCIA) cases were analyzed using three tumor regions (body, edge, and out). An integrated volume-of-interest (VOI) random forest (RF) model was trained with selected features and externally validated. Radiogenomic analysis correlated radscore with TCIA transcriptomic profiles using weighted gene co-expression network analysis (WGCNA). The model achieved high discrimination (area under the curve [AUC] 0.959 internally; 0.860 externally). Radscore-associated modules revealed

SUBMITTER: Gao Y 

PROVIDER: S-EPMC12925126 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature