Cancer management and research · 2026
A Multiphase CT-Based Radiomics-Clinical Model to Identify Inadequate Future Liver Remnant Hypertrophy After Portal Vein Embolization Before Major Hepatectomy.
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Zhou Rui, Liu Dong, Huang Jian, Liu Fuchen, Zhou Wenxuan, Zou Minhao, Wu Xiaoqin, Liu Hui, Jia Ningyang
Аннотация
PURPOSE: To develop and internally validate a multiphase contrast-enhanced computed tomography (CT) based radiomics-clinical nomogram for pre-operative prediction of inadequate future liver remnant (FLR) hypertrophy after portal vein embolization (PVE), with the aim of guiding individualized surgical planning.
PATIENTS AND METHODS: We retrospectively enrolled patients who underwent PVE at our centre. Contrast-enhanced CT and clinical data were collected before and 2-5 weeks after PVE for calculated FLR (cFLR≥30% defined as adequate hypertrophy). After liver segmentation on triphasic CT, radiomic features were extracted and reduced by LASSO to build a Rad-signature. This signature was integrated with significant clinical variables into an MLP fusion model, visualised as a nomogram, and evaluated using ROC, calibration and decision-curve analyses.
RESULTS: A total of 98 patients were included in this study. The fusion model achieved an area under the receiver-operating-characteristic curve (AUC) of 0.913 (95% CI 0.846-0.981) in the training cohort and 0.833 (95% CI 0.605-1.000) in the internal test cohort, outperforming the clinical-only model (AUC 0.714; DeLong P = 0.017). Sensitivity and specificity in the test set were 0.824 and 1.000, respectively. Pre-PVE FLR, cFLR, serum pre-albumin, prior chemotherapy, hepatitis status and underlying cirrhosis were independent predictors of adequate hypertrophy. Decision-curve analysis demonstrated net clinical benefit within a threshold probability range of 20-80%.
CONCLUSION: The proposed multiphase CECT radiomics-clinical nomogram showed potential for identifying patients at high risk of insufficient FLR hypertrophy after PVE. This internally validated model holds promise for supporting personalised planning in hepatobiliary surgery.
PATIENTS AND METHODS: We retrospectively enrolled patients who underwent PVE at our centre. Contrast-enhanced CT and clinical data were collected before and 2-5 weeks after PVE for calculated FLR (cFLR≥30% defined as adequate hypertrophy). After liver segmentation on triphasic CT, radiomic features were extracted and reduced by LASSO to build a Rad-signature. This signature was integrated with significant clinical variables into an MLP fusion model, visualised as a nomogram, and evaluated using ROC, calibration and decision-curve analyses.
RESULTS: A total of 98 patients were included in this study. The fusion model achieved an area under the receiver-operating-characteristic curve (AUC) of 0.913 (95% CI 0.846-0.981) in the training cohort and 0.833 (95% CI 0.605-1.000) in the internal test cohort, outperforming the clinical-only model (AUC 0.714; DeLong P = 0.017). Sensitivity and specificity in the test set were 0.824 and 1.000, respectively. Pre-PVE FLR, cFLR, serum pre-albumin, prior chemotherapy, hepatitis status and underlying cirrhosis were independent predictors of adequate hypertrophy. Decision-curve analysis demonstrated net clinical benefit within a threshold probability range of 20-80%.
CONCLUSION: The proposed multiphase CECT radiomics-clinical nomogram showed potential for identifying patients at high risk of insufficient FLR hypertrophy after PVE. This internally validated model holds promise for supporting personalised planning in hepatobiliary surgery.