Development and Validation of a Clinical Radiomics Nomogram for Predicting Early Recurrence After Microwave Ablation...

To develop and validate a non-invasive model for predicting early recurrence (ER) after microwave ablation (MWA) in patients with hepatocellular carcinoma (HCC) and comorbid type 2 diabetes (T2D).

This retrospective study enrolled 186 HCC patients with T2D who underwent MWA and were divided into training (n=149) and validation (n=37) cohorts. Preoperative clinical parameters and portal-venous phase MRI radiomic features were extracted. A radiomics score (RAD -score) was constructed using the K-nearest neighbors (KNN) algorithm after feature selection. A clinical model was built using logistic regression, and a nomogram integrating clinical factors and the RAD -score was established. Model performance was evaluated using ROC curves, calibration curves, and decision curve analysis (DCA). Kaplan--Meier curves, pathological analysis, and immunohistochemistry validated prognostic stratification.

Four core radiomic features were identified. The combined nomogram achieved AUCs of 0.877 (training) and 0.846 (validation), outperforming the clinical (AUC 0.718) and radiomics (AUC 0.774) models alone. In the validation cohort, the sensitivity, specificity, and negative predictive value were 80.0%, 83.8%, and 90.1%, respectively. DCA showed a significant net benefit across threshold probabilities of 0.1-0.9. High-risk patients had a 5.8-fold (training) and 2.51-fold (validation) higher recurrence risk with significantly shorter progression-free survival. Pathological and immunohistochemical analyses confirmed more aggressive tumor features (higher rates of microvascular invasion, poor differentiation, thick-trabecular type, CD34 expression, and glypican-3 expression) in the high-risk group.

The nomogram provides a satisfactory prediction of early recurrence within two years after MWA in HCC patients with T2D, enabling individualized postoperative surveillance and intervention.