18F-FDG PET/MRI Multiparametric Imaging Features for Predicting MYCN Amplification Status in Children With High-Risk Neuroblastoma.

Abstract

Background: This study aimed to explore the value of multiparameter imaging features of ¹⁸F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MRI) in predicting MYCN amplification status in children with high-risk neuroblastoma (HR-NB) and to construct a combined predictive model.

Methods: A retrospective analysis of the clinical and PET/MRI imaging data of 121 children with HR-NB who were examined at our center between December 2018 and December 2025. According to the tumor MYCN amplification status, patients were divided into amplification (MNA group) and non-amplified (MYCN-NA group) groups. The differences in clinical characteristics and PET/MRI parameters between the two groups were also compared. Multivariate logistic regression analysis was used to identify the independent predictive factors. The predictive performance of each parameter and the combined model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. The combined model was visualized using nomograms.

Results: The imaging-defined risk factor (IDRF) positivity rate, proportion of stage M cases, and detection rates of tumor necrosis and hemorrhage were significantly higher in the MNA group than in the MYCN-NA group (all p < 0.05). The MNA group demonstrated a significantly larger mean diameter, higher maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), and a significantly lower mean apparent diffusion coefficient (ADC_mean) (all p < 0.001). Multivariate regression analysis showed that SUV_max (odds ratio (OR) = 1.71, 95% CI: 1.02-2.86, p = 0.042), MTV (OR = 1.075, 95% CI: 1.009-1.145, p = 0.026), and ADC_mean (OR = 0.34, 95% CI: 0.16-0.72, p = 0.004) were independent predictors of MYCN amplification. The combined model predicted MYCN amplification with an AUC of 0.916 (95% CI: 0.867-0.965), sensitivity of 83.3%, and specificity of 81.0%, outperforming all single parameters. Calibration and decision curve analyses indicated good calibration and clinical utility of the combined model.

Conclusion: The predictive model constructed by combining SUV_max, MTV, and ADC_mean can noninvasively distinguish MYCN amplification status in HR-NB patients.