A Noninvasive Predictive Model of Portal Hypertension in Patients with HCC Based on Clinical Features and Intra- and Peritumoral Pre-Fusion Radiomic Features.
Authors
Affiliations (3)
Affiliations (3)
- Department of Hepatobiliary Surgery, the Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, People's Republic of China.
- Department of Hepatobiliary Surgery, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, People's Republic of China.
Abstract
To develop a non-invasive model integrating clinical features with intra- and peritumoral pre-fusion radiomic features to predict portal hypertension (PHT) in hepatocellular carcinoma (HCC) patients. This retrospective study included 884 HCC patients who underwent partial hepatectomy with intraoperative portal venous pressure measurement (January 2013-January 2020). Patients were randomly assigned to training (n = 707, 89 with PHT) and validation (n = 177, 23 with PHT) cohorts. Clinical predictors were identified using logistic regression. Radiomic features were extracted from intratumoral and peritumoral regions on portal venous phase CT images. Key features were selected using <i>t</i>-tests, correlation analysis, and LASSO regression. Following comparison of multiple feature sets via K-Nearest Neighbors, intra- and peritumoral pre-fusion radiomic features were selected. A logistic regression-based nomogram combining clinical predictors with this radiomic set was developed and compared with traditional models. Portal vein diameter (PVD), Child-Pugh score, and FIB-4 score were identified as independent risk factors for PHT. The combined clinical-radiomic model achieved superior predictive performance in both the training (AUC: 0.938, 95% CI: 0.918-0.959) and validation (AUC: 0.847, 95% CI: 0.760-0.935) cohorts. The clinical-only model outperformed all radiomics-based models in this study, suggesting that routinely available clinical parameters may provide a robust foundation for portal hypertension screening. This finding may serve as a reference for clinical resource allocation and indicates the potential existence of a simplified, cost-effective screening pathway without reliance on complex radiomic analysis. Notably, the combined clinical-radiomic model demonstrated superior predictive performance, highlighting the complementary value of radiomic features to clinical indicators to a certain extent. However, the incremental benefit should be carefully weighed against the added complexity and challenges of standardization. This study further suggests that portal vein diameter, Child-Pugh score, and FIB-4 score may serve as independent predictors, offering a preliminary reference for future exploration of non-invasive tools for portal hypertension prediction. External validation is still needed to further confirm the model's generalizability and clinical utility.