Prediction of Programmed Death Ligand 1 Expression in Extrahepatic Cholangiocarcinoma Based on MRI Radiomics Nomograms
10.3969/j.issn.1005-5185.2025.02.014
- VernacularTitle:基于MRI影像组学列线图预测肝外胆管癌程序性死亡配体1表达
- Author:
Jiong LIU
1
;
Xiaoyong WANG
1
;
Limin WANG
1
;
Xinqiao HUANG
1
;
Chunmei YANG
1
;
Jian SHU
1
Author Information
1. 西南医科大学附属医院放射科,四川 泸州 646000;核医学与分子影像四川省重点实验室,四川 泸州 646000
- Publication Type:Journal Article
- Keywords:
Extrahepatic cholangiocarcinoma;
Magnetic resonance imaging;
Programmed death ligand 1;
B7-H1 antigen;
Radiomics;
Nomograms
- From:
Chinese Journal of Medical Imaging
2025;33(2):179-185
- CountryChina
- Language:Chinese
-
Abstract:
Purpose To investigate the value of non-invasive preoperative prediction of programmed death ligand 1 expression status in extrahepatic cholangiocarcinoma using MRI radiomics combined with clinical features through nomograms.Materials and Methods A retrospective collection was made of 87 cases of extrahepatic cholangiocarcinoma diagnosed through surgical pathology in the Affiliated Hospital of Southwest Medical University from January 2011 to December 2021.These were randomly divided into training and testing sets at a 7∶3 ratio.Using 3D-Slicer software,regions of interest were manually delineated layer-by-layer on MRI images,and radiomic features were extracted.Data normalization,feature dimensionality reduction and selection were then performed.A Gaussian naive Bayes classifier was used to construct the radiomics model,and radiomics scores were obtained.Multivariate Logistic regression was used to screen clinical features,and individual clinical and combined models were constructed.The predictive performances of the three models were evaluated using the area under the receiver operating characteristic curve(AUC),and the goodness of fit and clinical net benefit of the combined model nomogram were assessed through calibration and decision curves.Results Nine radiomic features and three clinical features were finally selected.The clinical features included alanine transaminase(P=0.020),aspartate transaminase(P=0.025)and total bilirubin(P=0.026).The predictive performance of the combined model(training set AUC 0.813,testing set AUC 0.818)was superior to that of the individual clinical model(training set AUC 0.711,testing set AUC 0.705)and the radiomics model(training set AUC 0.769,testing set AUC 0.767).Calibration and decision curves indicated good fit and better clinical net benefit for the combined model nomogram.Conclusion Based on preoperative multi-sequence MRI images and the radiomics score,along with alanine transaminase,aspartate transaminase and total bilirubin as clinical features,the constructed combined model nomogram effectively predicts the programmed death ligand 1 expression status in extrahepatic cholangiocarcinoma.This provides guidance for the precise and personalized immunotherapy for patients.
