Clinical and CT radiomics features for predicting microsatellite instability-high status of gastric cancer
10.13929/j.issn.1003-3289.2024.01.015
- VernacularTitle:临床及CT影像组学特征预测胃癌微卫星高度不稳定状态
- Author:
Pengchao ZHAN
1
;
Liming LI
;
Dongbo LYU
;
Chenglong LUO
;
Zhiwei HU
;
Pan LIANG
;
Jianbo GAO
Author Information
1. 郑州大学第一附属医院放射科,河南郑州 450052
- Keywords:
stomach neoplasms;
microsatellite instability;
tomography,X-ray computed;
radiomics
- From:
Chinese Journal of Medical Imaging Technology
2024;40(1):77-82
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of clinical and CT radiomics features for predicting microsatellite instability-high(MSI-H)status of gastric cancer.Methods Totally 150 gastric cancer patients including 30 cases of MSI-H positive and 120 cases of MSI-H negative were enrolled and divided into training set(n=105)or validation set(n=45)at the ratio of 7∶3.Based on abdominal vein phase enhanced CT images,lesions radiomics features were extracted and screened,and radiomics scores(Radscore)was calculated.Clinical data and Radscores were compared between MSI-H positive and negative patients in training set and validation set.Based on clinical factors and Radscores being significant different between MSI-H positive and negative ones,clinical model,CT radiomics model and clinical-CT radiomics combination model were constructed,and their predictive value for MSI-H status of gastric cancer were observed.Results Significant differences of tumor location and Radscore were found between MSI-H positive and negative patients in both training and validation sets(all P＜0.05).The area under the curve(AUC)of clinical model,CT radiomics model and combination model for evaluating MSI-H status of gastric cancer in training set was 0.760,0.799 and 0.864,respectively,of that in validation set was 0.735,0.812 and 0.849,respectively.AUC of clinical-CT radiomics combination model was greater than that of the other 2 single models(all P＜0.05).Conclusion Clinical-CT radiomics combination model based on tumor location and Radscore could effectively predict MSI-H status of gastric cancer.
