Development of a predictive model for KRAS mutation in patient with colorectal cancer based on CT radiomics
10.3969/j.issn.1002-1671.2024.01.013
- VernacularTitle:基于CT影像组学构建结直肠癌KRAS突变的预测模型
- Author:
Yuntai CAO
1
,
2
;
Zhan WANG
;
Jialiang REN
;
Junlin ZHOU
Author Information
1. 青海大学附属医院医学影像中心,青海 西宁 810001
2. 兰州大学第二医院放射科,甘肃 兰州 730030
- Keywords:
KRAS mutation;
colorectal cancer;
radiomics;
computed tomography
- From:
Journal of Practical Radiology
2024;40(1):56-59,144
- CountryChina
- Language:Chinese
-
Abstract:
Objective To utilize sophisticated CT-driven radiomics to prognosticate the mutation situation of KRAS in patients with colorectal cancer(CRC).Methods A total of 393 patients who underwent KRAS mutation testing and preoperative triphasic enhanced CT were analyzed retrospectively.All patients were divided into training group(n=276)and validation group(n=117)with a ratio of 7∶3.The characteristics tightly associated with KRAS mutation were extracted and screened to construct three models,include clinical,radiomics,and clinical-radiomics fusion models for prediction of KRAS mutation.The performance and clinical utility of these three models were assessed via receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The study identified significant correlations between KRAS mutation and CEA,CA199,and a set of 13 radiomics features,respective-ly.Based on these clinical indicators and radiomics features,clinical,radiomics,and clinical-radiomics fusion models were constructed to prognosticate KRAS mutation.The radiomics model construc-ted in this study had good performance for the prediction of KRAS mutation status in CRC patients.Most notably,a clinical-radiomics nomogram that amalgamated both clinical risk factors and radiomics parameters emerged as the most effective predictor of KRAS mutation,with an area under the curve(AUC)of 0.782 and 0.744 in the training group and validation group,respectively.Conclusion The refined CT radiomics model serves as a robust,non-invasive,quantitative tool for the assessment of KRAS mutation status in CRC patients.
