Figure 2.

Flow chart of radiomic nomogram: Image segmentation and radiomics feature extraction of GST. Feature selection via LASSO binary logistic regression model. The parameter (λ) was screened by using 10-fold cross-validation method and parameter (λ) between two dotted lines was the optimal value by using the minimum criteria and the 1 standard error of the minimum criteria (the 1-SE criteria). LASSO coefficient profiles of the 28 radiological features. A coefficient profile plot was conducted against the log (λ) sequence. λ value of 0.019, with log (λ), -3.96 was selected (1-SE criteria) based on 10-fold cross-validation. Vertical line was drawn at the value selected, where resulted in 4 non-zero coefficients. Finally, radiomic and clinical features were fitted to construct the radiomic model. The performance of each model was evaluated by the area under ROC curve.