Association of Computed Tomography Radiomics Signature with Progression-free Survival in Neuroblastoma Patients

Aims To investigate the association of computed tomography radiomics signature with progression-free survival (PFS) in neuroblastoma patients. Materials and methods We retrospectively included 167 neuroblastoma patients who were divided into a training set and a test set through stratified sampling at a ratio of 7:3. Regions of interest of the primary tumours were delineated on pretreatment contrast-enhanced computed tomography images and radiomics features were extracted from them. The intraclass correlation coefficient, Pearson correlation coefficient, and least absolute shrinkage and selection operator Cox regression algorithm were applied to select radiomics features and construct the radiomics signature. The effectiveness of the signature in predicting PFS was evaluated using the concordance index (C-index) and 95% confidence interval in both the training and the test sets. The time-dependent receiver operator characteristic curve of the radiomics signature was plotted and the area under the curve (AUC) was calculated. A calibration curve was used to assess the difference between the predicted probability of the radiomics signature and the observed probability at different time points. Results The radiomics signature was composed of six features, which achieved a C-index of 0.733 (95% confidence interval 0.664–0.803) in the training set and 0.734 (95% confidence interval 0.608–0.861) in the test set. In the training set, the radiomics signature yielded an AUC of 0.707, 0.737, 0.788, 0.859 and 0.829 for 1-, 2-, 3-, 4- and 5-year PFS, respectively. Similarly, the radiomics signature exhibited an AUC of 0.738, 0.807, 0.761, 0.787 and 0.818 for 1-, 2-, 3-, 4- and 5-year PFS, respectively, in the test set. The calibration curves showed no significant difference between the predicted probability of the radiomics signature and the observed probability for up to 5 years. Conclusions Computed tomography radiomics features exhibit a significant correlation with the PFS of neuroblastoma patients, particularly in terms of long-term outcomes.