Model Prediction
The five-times repeated 3-fold cross-validation logistic regression models with the 2 selected radiomics features yielded a mean AUC value of 0.879 (SD=0.04) on the training and 0.865 (SD=0.08) on the testing set (prediction cut off = 0.3) for MYCN amplification status prediction (Figure 4A). After the first binary outcome identification (i.e. MYCN amplified versus not amplified), a following analysis considering also the additional “gain” mutational status was ran. Interestingly out of the 11 gain patients, nine were located under the amplification prediction cutoff threshold of 0.3. Figure 4B discloses the gain patients in the general model. This may support the existence of a common radiomics pattern between non amplified and gain patients, confirming the similar clinical behavior within the two classes. In order to test the ability of the two selected radiomics features to predict survival outcomes, actual OS data were plotted with radiomics based predictions and relative Kaplan-Meier curves were designed. Log-rank tests have been done between observed and predicted amplified and not amplified patients curves (p=0.003 and 0.05 respectively), while no statistical significant difference has been observed between the observed and actual curves (p=not significant), (Figure 5).