Performance of a magnetic resonance imaging-based radiomics score combined with apparent diffusion coefficient in predicting hepatocellular carcinoma recurrence and disease-free survival: a retrospective cohort study.

内容摘要

This study aimed to evaluate the prognostic value of apparent diffusion coefficient (ADC) measurements and a predefined magnetic resonance imaging (MRI)-based radiomics score for predicting early recurrence and disease-free survival (DFS) in patients with hepatocellular carcinoma (HCC) undergoing curative surgical resection. This retrospective study included 200 patients who underwent curative-intent resection for HCC between January 2021 and January 2025, with follow-up data reviewed through January 2026. Preoperative multiparametric MRI examinations, including DWI, ADC maps, and dynamic contrast-enhanced sequences, were reviewed. The predefined radiomics score was derived from a validated institutional MRI-based radiomics pipeline using ADC maps and contrast-enhanced MR images. In the present cohort, the score was analyzed together with region-of-interest (ROI)-based ADC measurements as a fixed imaging biomarker, without any additional feature selection, model training, or model retraining. Early recurrence was defined as recurrence within 12 months after surgery. Univariable and multivariable logistic regression analyses were performed to identify predictors of recurrence. Prognostic performance was evaluated using receiver operating characteristic analysis, and model discrimination was compared using the DeLong test. The DFS was assessed using Kaplan-Meier and Cox proportional hazards analyses. Early recurrence occurred in 66 of 200 patients (33.0%). In multivariable logistic regression analysis, tumor size [odds ratio (OR): 1.55, 95% confidence interval (CI): 1.27-1.89, P < 0.001), ADC (OR: 0.29, 95% CI: 0.18-0.46, P < 0.001), and radiomics score (OR: 4.74, 95% CI: 2.85-7.89, P < 0.001) were independent predictors of recurrence. The radiomics score alone achieved an area under the curve (AUC) of 0.767, whereas ADC achieved an AUC of 0.707. Combining the ADC and radiomics score significantly improved predictive performance (AUC: 0.837), outperforming both ADC alone (P < 0.001) and the radiomics score alone (P = 0.008). The full multivariable model demonstrated the highest discriminatory performance (AUC: 0.892). For survival analysis, larger tumor size, multiple lesions, lower ADC values, and higher radiomics scores were independently associated with shorter DFS. Patients classified as high-risk according to the optimal radiomics score cut-off exhibited significantly worse DFS than low-risk patients (log-rank P < 0.001). Measurements of the ADC and a predefined MRI-based radiomics score provided complementary prognostic information in patients with HCC. The combined ADC-radiomics score improved prediction of early recurrence and DFS compared with either parameter alone. These findings support further validation of quantitative MRI biomarkers for non-invasive risk stratification after curative HCC resection. The combined assessment of ROI-based ADC measurements and a predefined MRI-based radiomics score may help refine postoperative surveillance strategies after curative HCC resection, pending validation in independent cohorts.