A Preliminary Study of Radiomics for Predicting the Traditional Chinese Medicine Syndromes of Non-small Cell Lung Cancer Based on Contrast-Enhanced CT Image
10.16466/j.issn1005-5509.2025.02.005
- VernacularTitle:基于增强CT影像组学预测非小细胞肺癌中医证型的初步研究
- Author:
Caiyong ZHAO
1
;
Huanguo LI
1
;
Junhua GUO
1
Author Information
1. 浙江中医药大学附属杭州市中医院 杭州 310007
- Publication Type:Journal Article
- Keywords:
non-small cell lung cancer;
TCM differentiation typing;
contrast-enhanced computed tomography;
radiomics;
model;
deficiency syndrome;
excess syndrome;
forecast
- From:
Journal of Zhejiang Chinese Medical University
2025;49(2):153-159
- CountryChina
- Language:Chinese
-
Abstract:
[Objective]To investigate the value of radiomics based on contrast-enhanced computed tomography(CT)image in predicting the traditional Chinese medicine(TCM)differentiation typing of primary non-small cell lung cancer(NSCLC).[Methods]A total of 130 patients diagnosed as NSCLC by pathology from July 2018 to October 2023 in Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University were retrospectively analyzed.According to the diagnostic criteria of TCM,all the enrolled patients were divided into deficiency syndrome group(67 cases)and excess syndrome group(63 cases),and then assigned to training cohort(91 cases)and validation cohort(39 cases)in a ratio of 7:3.The largest diameter slice of lesion on cross-sectional images was selected and the regions of interest were contoured at unenhanced,arterial and venous phases respectively,and then the radiomics features were extracted.The linear correlation among features and L1 regularization were used for feature selection,and then logistic regression was used to construct the radiomics model based on radiomics features of each phase.The receiver operating characteristic(ROC)curve was used to evaluate the effectiveness of the model in predicting deficiency and excess syndromes of NSCLC.The Delong test was used for comparison of area under curve(AUC)between the two models.[Results]In the training cohort,a total of 7 radiomics models were constructed,including three single-phase radiomics models,three two-phase combination radiomics models and one three-phase combination radiomics model.The AUC of combination radiomics model was higher than that of the single-phase radiomics model.The AUC of three-phase combination radiomics model was the largest,which was 0.876[95%confidence interval(CI)(0.807～0.945)]and 0.755[95%CI(0.603～0.908)]in the training cohort and validation cohort respectively.[Conclusion]The radiomics model based on contrast-enhanced CT image has high efficacy in predicting the TCM differentiation typing of NSCLC,and the three-phase combination radiomics model demonstrates the best diagnostic efficacy.
