The construction of the clinical-CT imaging model for predicting the incidence of brain metastasis in lung cancer
10.3969/j.issn.1002-1671.2025.03.011
- VernacularTitle:基于临床-CT影像构建肺癌脑转移风险预测模型的研究
- Author:
Yue ZHU
1
;
Zhihuai ZHOU
;
Jian WANG
;
Wenjing CHEN
;
Yanchen DU
Author Information
1. 蚌埠医科大学第二附属医院放射科,安徽 蚌埠 233040;蚌埠医科大学影像学院,安徽 蚌埠 233030
- Publication Type:Journal Article
- Keywords:
lung cancer;
brain metastasis;
prediction model;
computed tomography
- From:
Journal of Practical Radiology
2025;41(3):404-409
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of constructing a risk prediction model of brain metastasis in lung cancer based on clinical-CT imaging.Methods The clinical and CT imaging data of 208 patients with lung cancer confirmed by surgical pathology or puncture biopsy were analyzed retrospectively,including 98 patients in the metastasis group and 110 patients in the non-metastasis group.Univariable and binary logistic regression analyses were performed between the two groups,and the clinical,CT imaging,and clinical-CT imaging models were constructed according to the selected independent risk factors.Prediction model performance was eval-uated with receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA).Results Multivariate analysis showed that T stage,pathological type,radiotherapy and chemotherapy,surgery,long diameter(LD),short diameter(SD),minimum CT value(CTmin)were the independent risk factors for predicting brain metastasis in lung cancer(P<0.05).The area under the curve(AUC)of clinical,CT imaging and clinical-CT imaging models were 0.925,0.764,0.941,respectively.DeLong test analysis showed that the AUC of clinical-CT imaging model,clinical model and CT imaging model was statistical difference(Z=2.093,5.777,all P<0.05).The calibration curve suggested a good fit of the clinical-CT imaging model.The DCA suggested that the clinical-CT imaging model demonstrates good clinical benefits.Conclusion The clinical-CT imaging model can effectively predict the occurrence of brain metastasis in lung cancer,which is helpful to guide the development of accurate diagnosis and treatment plan.
