Prognostic value of automated CT body composition in hepatocellular carcinoma: a volumetric versus single-slice comparison

Backgrounds/Aims: To compare the prognostic value of fully automated volumetric versus single-slice computed tomography (CT)-derived body composition analysis for predicting overall survival in patients with newly diagnosed hepatocellular carcinoma (HCC). Methods: In this retrospective study of 448 patients with newly diagnosed HCC, deep-learning algorithm was used to quantify volumetric (L1-L5) and single-slice (L3) skeletal muscle and adipose tissue metrics. Spearman correlation assessed the relationship between volumetric and single-slice body composition metrics. Cox proportional hazards models, adjusted for established clinical prognostic factors, were used to evaluate association between body composition parameters and overall survival. Harrell's C-index was used to compare prognostic performance of Cox models. Results: Strong correlations (correlation coefficient≥0.82) were observed between volumetric and single-slice measurements for muscle attenuation, visceral fat index, and subcutaneous fat index, while muscle index demonstrated only moderate correlation (correlation coefficient = 0.50). Single-slice low muscle index (HR, 1.63; 95% CI, 1.15-2.31; p = 0.006), single-slice low muscle attenuation (HR, 1.38; 95% CI, 1.01-1.88; p = 0.045) and volumetric low muscle attenuation (HR, 1.42; 95% CI, 1.03-1.95; p = 0.034) were identified as independent predictors of overall survival. Median follow-up was 6.6 years. The single-slice and volumetric models showed comparable discrimination (C-index, 0.816 vs. 0.817; p = 0.11). Conclusion: Automated single-slice muscle parameters at the L3 level provides significant prognostic stratification in patients with hepatocellular carcinoma, establishing it as a viable, time-efficient tool for routine oncologic practice. In contrast, automated volumetric body composition assessment did not provide superior discrimination compared with the single-slice approach.