Value of CT radiomics combined with morphological features in predicting the prognosis of patients with non-small cell lung cancer
Objective To explore the predictive value of CT radiomics and morphological features for the prognosis and survival in non-small cell lung cancer(NSCLC)patients.Methods The clinic data of 300 NSCLC patients(300 lesions)were downloaded from the Cancer Imaging Archive,with 210 randomly selected as the training set and 90 as the test set.According to the prognosis and survival,the patients were divided into two groups with survival period≤3 and＞3 years.3D Slicer software was used to delineate the regions of interest layer by layer in CT images,and the radiomics features were extracted from each region of interest.Both t-test and least absolute shrinkage and selection operator were utilized for radiomics feature screening.Three types of prediction models,namely radiomics model,morphological model and combined model,were constructed with Logistic regression,whose performances were evaluated using the receiver operating characteristic(ROC)curve.Results The differences in radiomics labels and mediastinal lymph node metastasis between the training set and the test set were statistically significant.For radiomics model,morphological model and combined model,the area under the ROC curve was 0.784(95%CI:0.722-0.847),0.734(95%CI:0.664-0.804)and 0.748(95%CI:0.680-0.815)in the training set,and 0.737(95%CI:0.630-0.844),0.665(95%CI:0.554-0.777)and 0.687(95%CI:0.578-0.797)in the test set,which demonstrated that radiomics model had the best diagnostic performance.Conclusion The CT radiomics model can effectively predict the prognosis and survival in NSCLC patients.
NETL
NSTL
万方数据
维普
