Limited incremental value and cross-cohort transferability of CT radiomics for survival prediction after TACE in hepatocellular carcinoma.

PURPOSE: To evaluate whether pretreatment CT radiomics adds information for overall survival (OS) prediction among patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE), and assess frozen imaging-model performance in an independent cohort. METHODS: This retrospective study included 221 WAW-TACE and 98 HCC-TACE-SEG patients with pretreatment arterial and portal venous CT. Incremental value of a tumor-radiomics Random Survival Forest score (R1) beyond cohort-specific clinical Cox models (C0) was evaluated within each cohort using 5-fold cross-validation repeated 10 times. External validation was restricted to frozen WAW-trained R1 models (Top-K = 5, 10, 15) applied to HCC-TACE-SEG without refitting; the combined C0 + R1 model was not externally validated. RESULTS: WAW-TACE included 162 deaths and HCC-TACE-SEG 86 deaths. In WAW-TACE, C0, R1 Top-K = 15, and C0 + R1 achieved C-indices of 0.646 ± 0.043, 0.593 ± 0.049, and 0.639 ± 0.045, respectively. Corresponding HCC-TACE-SEG estimates were 0.496 ± 0.087, 0.530 ± 0.072, and 0.495 ± 0.094. Thus, R1 did not consistently improve cohort-specific clinical reference models. In frozen external application, Top-K = 5, 10, and 15 achieved C-indices of 0.463 (95% CI 0.397-0.532), 0.535 (0.468-0.608), and 0.528 (0.460-0.598), respectively. CONCLUSION: The evaluated models showed no consistent incremental value for OS prediction within these TACE cohorts and limited frozen-model discrimination in the clinically distinct HCC-TACE-SEG cohort. These findings do not support clinical use of these models or establish a general limitation of CT radiomics.