CT Radiomics to Predict Macrotrabecular-Massive Subtype and Immune Status in Hepatocellular Carcinoma

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which is expected to be noninvasively identified using radiomics approaches. Purpose To construct a CT radiomics model to predict the MTM subtype and to investigate the underlying immune infiltration patterns. Materials and Methods This study included five retrospective data sets and one prospective data set from three academic medical centers between January 2015 and December 2021. The preoperative liver contrast-enhanced CT studies of 365 adult patients with resected HCC were evaluated. The Third Xiangya Hospital of Central South University provided the training set and internal test set, while Yueyang Central Hospital and Hunan Cancer Hospital provided the external test sets. Radiomic features were extracted and used to develop a radiomics model with machine learning in the training set, and the performance was verified in the two test sets. The outcomes cohort, including 58 adult patients with advanced HCC undergoing transarterial chemoembolization and antiangiogenic therapy, was used to evaluate the predictive value of the radiomics model for progression-free survival (PFS). Bulk RNA sequencing of tumors from 41 patients in The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing from seven prospectively enrolled participants were used to investigate the radiomics-related immune infiltration patterns. Area under the receiver operating characteristics curve of the radiomics model was calculated, and Cox proportional regression was performed to identify predictors of PFS. Results Among 365 patients (mean age, 55 years ± 10 [SD]; 319 men) used for radiomics modeling, 122 (33%) were confirmed to have the MTM subtype. The radiomics model included 11 radiomic features and showed good performance for predicting the MTM subtype, with AUCs of 0.84, 0.80, and 0.74 in the training set, internal test set, and external test set, respectively. A low radiomics model score relative to the median value in the outcomes cohort was independently associated with PFS (hazard ratio, 0.4; 95% CI: 0.2, 0.8; P = .01). The radiomics model was associated with dysregulated humoral immunity involving B-cell infiltration and immunoglobulin synthesis. Conclusion Accurate prediction of the macrotrabecular-massive subtype in patients with hepatocellular carcinoma was achieved using a CT radiomics model, which was also associated with defective humoral immunity. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue.