Development and validation of models to predict serosal invasion in advanced gastric cancer using the enhanced CT imaging-based radiomics features and clinical features
10.3969/j.issn.1005-202X.2023.12.010
- VernacularTitle:基于增强CT影像组学模型和临床特征模型评估进展期胃癌浆膜侵犯
- Author:
Cuixia WAN
1
,
2
;
Xiangguang CHEN
;
Zhiqi YANG
;
Ting DONG
;
Sheng ZHANG
;
Guihua JIANG
Author Information
1. 广东医科大学梅州临床医学院,广东梅州 514031
2. 梅州市人民医院(梅州市医学科学院)放射科,广东梅州 514031
- Keywords:
gastric cancer;
serosal invasion;
clinicopathological feature;
radiomics feature;
CT
- From:
Chinese Journal of Medical Physics
2023;40(12):1518-1522
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the predictive value of the enhanced CT imaging-based radiomics model and the clinical model for the serosal invasion in advanced gastric cancer.Methods The data were collected from 351 patients with advanced gastric cancer who underwent abdominal enhanced CT examination within 2 weeks before surgery,and the patients were randomly divided into a training group(n=247)and a validation group(n=104)in a ratio of 7:3.The 3190 radiomics features which were extracted from the arterial and venous phase CT images using A.K software were dimensionally reduced for constructing a radiomics model.The pathological features between serosal invasion positive and negative groups were compared,and the significant features were used to establish a clinical model.The model's performance was evaluated using receiver operating characteristic curve.Results In the training and validation groups,N staging and M staging were different in serosal invasion positive and negative groups(P<0.05).A total of 14 radiomic features were ultimately selected from the arterial and venous phase images.In the validation group,the diagnostic efficacy of the radiomic model for predicting serosal invasion in advanced gastric cancer was higher than that of the clinical model based on the combination of N staging and M staging(AUC:0.854 vs 0.793).Conclusion Both the radiomics model based on the enhanced CT imaging and the clinical model based on the combination of N staging and M staging can successfully predict serosal invasion in advanced gastric cancer,but the former performs better.
