Construction and evaluation of a nomogram for preoperative prediction of microvascular invasion and vascular encirulation of tumor cell nests in double-positive hepatocellular carcinoma
10.3760/cma.j.cn113884-20250718-00227
- VernacularTitle:术前预测微血管侵犯和血管包绕肿瘤细胞巢双阳性肝细胞癌列线图的构建和评估
- Author:
Jiyun ZHANG
1
;
Xueqin ZHANG
;
Qi QU
;
Jifeng JIANG
;
Chunyan GU
;
Yixing YU
;
Tao ZHANG
Author Information
1. 南通大学附属南通第三医院（南通市第三人民医院）影像科，南通 226001
- Publication Type:Journal Article
- Keywords:
Carcinoma, hepatocellular;
Magnetic resonance imaging;
Microvessels;
Disodium gadoxetic acid;
Tumor cell nest
- From:
Chinese Journal of Hepatobiliary Surgery
2025;31(11):811-816
- CountryChina
- Language:Chinese
-
Abstract:
Objective:A nomogram model for predicting double positivity of microvascular invasion (MVI) and vascular endothelial-to-mesenchymal transition (VETC) in patients with hepatocellular carcinoma (HCC) was constructed and its predictive performance was evaluated.Methods:A retrospective analysis was conducted on 326 HCC patients who were treated at the Third People's Hospital of Nantong and the First Affiliated Hospital of Soochow University from January 2013 to June 2023, including 240 males and 86 females, with an average age of (58.7±9.0) years. The 326 patients were randomly divided into a training set ( n=228) and a test set ( n=98) at a ratio of 7: 3 using the random number table method. The training set was divided into a double-positive group ( n=54) and a control group ( n=174) based on whether the HCC patients were double positive for MVI and VETC. Univariate and multivariate logistic regression analyses were performed to identify the influencing factors of double positivity of microvascular invasion in HCC patients, and a nomogram for predicting double positivity of microvascular invasion patterns was constructed based on the multivariate. The predictive performance and clinical net benefit of the nomogram were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results:There were statistically significant differences in alpha-fetoprotein, gamma-glutamyl transferase, and phosphatidylinositol proteoglycan between the two groups (all P<0.05). Multivariate logistic regression analysis showed that LI-RADS category ( OR=8.58, 95% CI: 1.87-39.38), intratumoral hemorrhage ( OR=2.16, 95% CI: 1.14-4.07), and intratumoral arteries ( OR=2.59, 95% CI: 1.19-5.64) were all influencing factors of double positivity of microvascular invasion patterns in HCC patients (all P<0.05). Based on the multivariate results, a nomogram was constructed. In the training set, the area under the ROC curve for predicting double positivity of microvascular invasion patterns in HCC patients was 0.769 (95% CI: 0.720-0.814). In the test set, the area under the ROC curve for predicting double positivity of microvascular invasion patterns in HCC patients was 0.756 (95% CI: 0.622-0.850). The calibration curve showed a good fit between the predicted model and the ideal curve. Decision curve analysis showed that the clinical applicability was good when the threshold was 0.01-0.80 in the training set and 0.01-0.65 in the test set. Conclusion:The nomogram model based on LI-RADS category, intratumoral hemorrhage, and intratumoral arteries can effectively predict double positivity of microvascular invasion patterns in HCC patients and has good clinical applicability.
