Predicting the histological type of thymoma based on CT radiomics nomogram
10.3969/j.issn.1002-1671.2024.10.009
- VernacularTitle:基于CT影像组学列线图预测胸腺瘤组织学分型
- Author:
Qingsong BU
1
;
Haoyu ZHU
;
Tao WANG
;
Lei HU
;
Xiang WANG
;
Xiaofeng LIU
;
Jiangning DONG
;
Xingzhi CHEN
;
Shujian WU
Author Information
1. 池州市人民医院医学影像科,安徽 池州 247100
- Keywords:
thymoma;
computed tomography;
radiomics
- From:
Journal of Practical Radiology
2024;40(10):1615-1619
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the value of a nomogram model based on contrast-enhanced CT radiomics in predicting the histological type of thymoma.Methods A total of 154 patients(101 in low-risk group and 53 in high-risk group)with thymoma confirmed by pathology were retrospectively selected.The cases were randomly divided into training set(n=107)and validation set(n=47)at a ratio of 7∶3.The three-dimensional volume of interest(VOI)of the whole lesion on the image from the arterial phase of contrast-enhanced CT was manually delineated,and the radiomics features were extracted.Based on the selected radiomics features,the radiomics model was constructed and the model Radiomics score(Radscore)was calculated.Clinical risk factors were screened to construct a clinical model,and a nomogram model was constructed by fusing Radscore and clinical risk factors.The receiver operating characteristic(ROC)curve,area under the curve(AUC),accuracy,sensitivity and specificity were compared to analyze the predictive efficacy and difference of different models for high-risk and low-risk thymoma.The decision curve and calibration curve were drawn to evaluate the clinical value and fitting performance of the nomogram model.Results Eleven radiomics features were selected to construct the radiomics model,and five clinical risk factors[myasthenia gravis(MG),morphology,border,surrounding tissue invasion and CT value in arterial phase]were used to construct the clinical model.In the training set,the AUC of the nomogram model(0.88)was higher than that of the radiomics model(0.80)and the clinical model(0.79),and the difference was statistically significant(Z=2.233,2.713,P=0.026,0.007,respectively).In the validation set,the AUC of the nomogram model was higher than that of the radiomics and clinical models,but the difference was not statistically significant.The calibration curve showed that the nomogram model had good fitting performance,and the decision curve showed that the nomogram model had high clinical benefit.Conclusion The nomogram model based on contrast-enhanced CT can effectively predict high-risk and low-risk thymoma,which is helpful to guide clinicians to make relevant decisions.
