A Clinical-Imaging Nomogram for Predicting Post-Hepatectomy Recurrence in Hepatocellular Carcinoma with Microvascular Invasion.

PURPOSE: This study aimed to develop an individualized nomogram incorporating clinical and imaging features for predicting recurrence in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) after hepatectomy. METHODS: A total of 317 pathologically confirmed MVI-positive HCC patients who underwent curative resection between January 2016 and December 2022 were analyzed retrospectively. Independent risk factors for recurrence-free survival (RFS) were identified through univariate and multivariate Cox regression analyses. A nomogram was developed based on these factors, and its performance was evaluated by the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, and calibration curves. Its clinical utility was assessed with decision curve analysis (DCA). RESULTS: The developed nomogram incorporated four independent predictors for estimating RFS, including MVI grade, AFP, liver cirrhosis, and smooth tumor margin. The model demonstrated good discriminative ability, with a C-index of 0.758 (95% confidence interval [CI]: 0.720-0.803) in the training cohort and 0.702 (95% CI: 0.642-0.790) in the validation cohort. Calibration curves showed good agreement between predictions and observations. Stratified by the nomogram score, patients in the high-risk group had significantly worse RFS than those in the low-risk group (Log-rank p < 0.0001). Additionally, DCA demonstrated the clinical utility of the nomogram across a wide range of threshold probabilities. CONCLUSION: The proposed clinical-imaging nomogram provides individualized risk estimates for post-hepatectomy recurrence in MVI-positive HCC patients. This tool facilitates risk stratification, aids clinicians in tailoring postoperative surveillance and adjuvant therapy, and helps identify high-risk patients for timely intervention.