Construction of a nomogram prediction model for PD-L1 expression in non-small cell lung cancer using spectral CT parameters and clinical features
10.3969/j.issn.1005-202X.2025.04.004
- VernacularTitle:基于能谱CT参数及临床特征构建非小细胞肺癌PD-L1表达的列线图预测模型
- Author:
Kaibo ZHU
1
;
Liangna DENG
1
;
Haisheng WANG
1
;
Jianqiang LIU
1
;
Pan LUO
1
;
Junlin ZHOU
1
Author Information
1. 兰州大学第二医院放射科/兰州大学第二临床医学院/甘肃省医学影像重点实验室/医学影像人工智能甘肃省国际科技合作基地,甘肃 兰州 730030
- Publication Type:Journal Article
- Keywords:
non-small cell lung cancer;
nomogram;
spectral CT;
programmed cell death ligand 1
- From:
Chinese Journal of Medical Physics
2025;42(4):443-449
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the preoperative prediction of the expression level of programmed cell death ligand 1(PD-L1)in non-small cell lung cancer(NSCLC)by a nomogram model constructed with clinical data,conventional CT signs and spectral CT parameters.Methods A retrospective analysis was conducted on 52 patients with pathologically confirmed NSCLC and undergoing preoperative spectral CT examination.The patients were categorized into positive and negative groups according to PD-L1 expression level,and their clinical data,conventional CT signs and spectral CT parameters were collected.Specifically,clinical data included gender,age,Ki-67 and tumor markers;conventional CT signs included tumor density,margins,calcification,spiculation,lobulation,pleural indentation and cavitation;and spectral CT parameters measured in the arterial and venous phases included effective atomic number(Eff-Z),iodine concentration(IC),water concentration(WC)and normalized iodine concentration(NIC).Intergroup differences were analyzed,and multivariate Logistic regression was used to identify independent predictors and establish the prediction model which was evaluated for prediction performance and accuracy using receiver operating characteristic(ROC)curves,calibration curve and decision curve analyses.Results For clinical data,only the difference in gender between two groups had statistical significance(P<0.05).The spectral CT parameters(IC,NIC and Eff-Z)in the arterial and venous phases of PD-L1 positive group were all greater than those of PD-L1 negative group,with statistically significant differences(P<0.05).Multivariate Logistic regression analysis identified gender(P=0.024),venous-phase Eff-Z(P=0.002),and venous-phase IC(P=0.003)as independent predictive factors for PD-L1 expression.The nomogram prediction model constructed with these independent predictors had an area under curve of 0.80,a sensitivity of 88.00%,and a specificity of 59.00%.The calibration curve showed that the predicted values had a high consistency with the actual values.The decision curve revealed that when the high-risk threshold was between 0.10 and 0.83,the model could achieve the maximum net benefit.Conclusion The nomogram model constructed with spectral CT parameters and clinical data has certain value in predicting the expression level of PD-L1 in NSCLC.
