Figure 2:

(A) Radiomic feature selection using the least absolute shrinkage and selection operator (Lasso) cox regression model. Tuning penalization parameter lambda using 5-fold cross validation and minimum criterion in lasso model. The partial likelihood deviance was plotted versus log lambda. Log Lamda = −2.4308, with lambda = 0.0880 was chosen. (B) Forest plot of the beta coefficients/weights of the 25 radiomic features selected in the radiomic risk score. Brown, green, and yellow represent features obtained from the necrotic core, enhancing region and edema of the tumor habitat respectively, from Gd-T1w MRI. (C) Kaplan-Meier curves for patients stratified into low-risk and high-risk groups according to the radiomic risk score (cutoff = −0.1044) in the training cohort and independent validation set respectively. X-axis represents the progression free survival days in days, and Y-axis represents the estimated survival function.