Value of radiomics in diagnosing the invasion degree and modeling of cystic lung adenocarcinoma

DONG Peng; CHENG Ping

Abstract：Objective To explore the value of radiomics in diagnosing the invasion degree and modeling of cystic lung ad-enocarcinoma,to deepen the understanding of this type of lung cancer,and to guide clinical stratified management.Methods 32 cases of cystic lung adenocarcinoma confirmed by pathology were retrospectively analyzed.According to pathological results,cystic lung adenocarcinoma was divided into relatively benign group(14 cases)and invasive group(18 cases).3D Slicer soft-ware was used to manually delineate the region of Interest(ROI)along the edge of the lesion,and Pyradiomics software was used to extract the ROI obtained.The least absolute shrinkage and Selection operator(LASSO)regression,T test and backward stepwise were used for feature dimensionality reduction and screening.P<0.05 was considered statistically significant.For the se-lected predictors,SPSS25.0 was used to calculate the area under the ROC curve(AUC)to evaluate the effectiveness of the no-mograph in differentiating cystic lung adenocarcinoma,and the survival and RMS toolkit of R software were used to draw the no-mograph.At the same time,Bootstrap method was used to test the prediction performance of the line graph model.Results Shape_LeastAxisLength and Shape_MinorAxisLength could better predict the invasion degree of cystic lung adenocarcinoma.Conclusion CT imaging features have important diagnostic value in predicting the invasion degree of cystic lung adenocarci-noma,which is expected to provide a non-invasive,quantitative,convenient and rapid diagnostic method for clinic.