Abstract

PurposeTo develop and validate an 18F-FDG PET/CT radiomics nomogram for non-invasive differentiation of high-risk and non-high-risk patients of the International Neuroblastoma Risk Group (INRG) Staging System (INRGSS). MethodOne hundred thirty-nine neuroblastoma patients were retrospectively enrolled and classified into a training set (n = 84) and validation set (n = 55). Radiomics features were extracted from 18F-FDG PET/CT images, a radiomics signature was constructed, and a radiomics score (Rad score) was calculated. Then, univariate and multivariate logistic regression analyses were used to screen out the independent clinical factors and construct the clinical model. A radiomics nomogram was developed based on the Rad score and independent clinical factors. The performance of the clinical model, Rad score, and nomogram was assessed by receiver operating characteristic (ROC) curves, calibration curves, and decision curves analysis (DCA). ResultsSeven radiomics features were selected to build the radiomics signature. The age at diagnosis, the INRG stage, neuron-specific enolase (NSE) and Rad score showed a significant difference between the high-risk and non-high-risk patients. The radiomics nomogram incorporating the Rad score and the above clinical factors demonstrated favorable predictive value for differentiating high-risk from non-high-risk, yielded AUCs of 0.988 and 0.971 in the training and validation sets, respectively. The calibration curves showed that the radiomics nomogram had the goodness of fit, and the DCA demonstrated that the radiomics nomogram was clinically useful. ConclusionsThe radiomics nomogram, which incorporates the Rad score and clinical factors can well predict high-risk and non-high-risk patients of the INRGSS. It may help the disease follow-up and management in clinical practice and assist in personalized and precise treatment of neuroblastoma.

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