The establishment and evaluation of the imaging model
glial cell hyperplasia and low grade glioma
REGRESSION
The delineation results of both observers demonstrated good intergroup agreement, as determined by ICC analysis (ICC ≥ 0.85). Out of the 1781 characteristics in each model of T1WI, T2WI, DWI, and T1-enhanced, the Person-test maintained the 14 features with the highest linear correlation coefficient. Then the LASSO, SVM, and RF models were established, which AUCs for distinguishing between glial cell hyperplasia and low grade glioma were 0.782, 0.779, 0.780 (Table 
The comparison of the three model performance
The ROC curve of the three radiomics model
The results of Delong’s test
The 24 best feature information and the corresponding feature weight
Univariate and multivariate logistic regression analysis1.009(0.965–1.054)0.6980.917(0.276–3.044)0.887Bold suggests statistical significance at the level of P < 0.05. OR, odds ratio