Journal of gastrointestinal oncology · 2026
An exploratory nomogram model with 18F-FDG PET/CT metabolic parameters for predicting high-risk status of microvascular invasion in hepatocellular carcinoma patients prior to liver transplantation.
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Li Shichang, Guo Ai'nan, Wang Xue, Tian Ying, Zhang Fang, Wei Lingge, Fu Peng
Аннотация
BACKGROUND: There are still difficulties in dividing patients into an microvascular invasion (MVI) high-risk and non-high-risk group among hepatocellular carcinoma (HCC) patients based on the pathology findings. This study investigated preoperative fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) (18F-FDG PET/CT) quantitative metabolic parameters and developed an exploratory nomogram model with these parameters for predicting high-risk MVI in patients with HCC scheduled for liver transplantation.
METHODS: A retrospective analysis was conducted involving 79 HCC patients undergoing liver transplantation with preoperative 18F-FDG PET/CT at the Third Hospital of Hebei Medical University from 2021 to 2024. Patients were stratified as non-high risk [n=42 (MVI-negative, 27 and low-risk MVI, 15)] or high risk (n=37) based on histopathologic findings. Clinical variables and PET/CT parameters were analyzed using univariate analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression. A predictive nomogram integrating the tumor-to-mediastinum standardized uptake value (SUV) max ratio (TMRmax) and maximum tumor diameter was developed and internally validated. Model performance was evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration plots.
RESULTS: LASSO regression identified TMRmax and tumor diameter as significant factors that are associated with high-risk MVI. Multivariate analysis confirmed the independence of these two predictors: TMRmax [odds ratio (OR) =1.757, 95% confidence interval (CI): 1.124-2.746; P=0.01] and tumor diameter (OR =1.247, 95% CI: 1.067-1.456; P=0.005). ROC curve analysis indicated that a TMRmax ≥2.1 achieved a sensitivity of 70.27% and a specificity of 64.29% [area under the ROC curve (AUC) =0.716], while a tumor diameter ≥8.3 cm had a sensitivity of 51.35% and a specificity of 90.48% (AUC =0.729). The combined model demonstrated improved predictive performance (C-index =0.779, 95% CI: 0.672-0.865) with the nomogram demonstrating good calibration.
CONCLUSIONS: TMRmax and tumor diameter may be closely associated with high-risk MVI in HCC. The exploratory model combining TMRmax and tumor diameter may help on preoperative risk stratification. Due to the small sample size from a single center, the results of this study warrant validation.
METHODS: A retrospective analysis was conducted involving 79 HCC patients undergoing liver transplantation with preoperative 18F-FDG PET/CT at the Third Hospital of Hebei Medical University from 2021 to 2024. Patients were stratified as non-high risk [n=42 (MVI-negative, 27 and low-risk MVI, 15)] or high risk (n=37) based on histopathologic findings. Clinical variables and PET/CT parameters were analyzed using univariate analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression. A predictive nomogram integrating the tumor-to-mediastinum standardized uptake value (SUV) max ratio (TMRmax) and maximum tumor diameter was developed and internally validated. Model performance was evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration plots.
RESULTS: LASSO regression identified TMRmax and tumor diameter as significant factors that are associated with high-risk MVI. Multivariate analysis confirmed the independence of these two predictors: TMRmax [odds ratio (OR) =1.757, 95% confidence interval (CI): 1.124-2.746; P=0.01] and tumor diameter (OR =1.247, 95% CI: 1.067-1.456; P=0.005). ROC curve analysis indicated that a TMRmax ≥2.1 achieved a sensitivity of 70.27% and a specificity of 64.29% [area under the ROC curve (AUC) =0.716], while a tumor diameter ≥8.3 cm had a sensitivity of 51.35% and a specificity of 90.48% (AUC =0.729). The combined model demonstrated improved predictive performance (C-index =0.779, 95% CI: 0.672-0.865) with the nomogram demonstrating good calibration.
CONCLUSIONS: TMRmax and tumor diameter may be closely associated with high-risk MVI in HCC. The exploratory model combining TMRmax and tumor diameter may help on preoperative risk stratification. Due to the small sample size from a single center, the results of this study warrant validation.