Whole-tumoral metabolic heterogeneity in 18F-FDG PET/CT is a novel prognostic marker for neuroblastoma.

BACKGROUND: Neuroblastoma (NB) is a highly heterogeneous tumor, and more than half of newly diagnosed NB are associated with extensive metastases. Accurately characterizing the heterogeneity of whole-body tumor lesions remains clinical challenge. This study aims to quantify whole-tumoral metabolic heterogeneity (WMH) derived from whole-body tumor lesions, and investigate the prognostic value of WMH in NB. METHODS: We retrospectively enrolled 95 newly diagnosed pediatric NB patients in our department. Traditional semi-quantitative PET/CT parameters including the maximum standardized uptake value (SUVmax), the mean standardized uptake value (SUVmean), the peak standardized uptake value (SUVpeak), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were measured. These PET/CT parameters were expressed as PSUVmax, PSUVmean, PSUVpeak, PMTV, PTLG for primary tumor, WSUVmax, WSUVmean, WSUVpeak, WMTV, WTLG for whole-body tumor lesions. The metabolic heterogeneity was quantified using the areas under the curve of the cumulative SUV-volume histogram index (AUC-CSH index). Intra-tumoral metabolic heterogeneity (IMH) and WMH were extracted from primary tumor and whole-body tumor lesions, respectively. The outcome endpoints were overall survival (OS) and progression-free survival (PFS). Survival analysis was performed utilizing the univariate and multivariate Cox proportional hazards regression. The optimal cut-off values for metabolic parameters were obtained by receiver operating characteristic curve (ROC). RESULTS: During follow up, 27 (28.4%) patients died, 21 (22.1%) patients relapsed and 47 (49.5%) patients remained progression-free survival, with a median follow-up of 35.0 months. In survival analysis, WMTV and WTLG were independent indicators of PFS, and WMH was an independent risk factor of PFS and OS. However, IMH only showed association with PFS and OS. In addition to metabolic parameters, the International Neuroblastoma Staging System (INSS) was identified as an independent risk factor for PFS, and neuron-specific enolase (NSE) served as an independent predictor of OS. CONCLUSION: WMH was an independent risk factor for PFS and OS, suggesting its potential as a novel prognostic marker for newly diagnosed NB patients.

18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging of pediatric neuroblastoma: a multi-omics parameters method to predict MYCN copy number category.

Background: The MYCN copy number category is closely related to the prognosis of neuroblastoma (NB). Therefore, this study aimed to assess the predictive ability of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomic features for MYCN copy number in NB. Methods: A retrospective analysis was performed on 104 pediatric patients with NB that had been confirmed by pathology. To develop the Bio-omics model (B-model), which incorporated clinical and biological aspects, PET/CT radiographic features, PET quantitative parameters, and significant features with multivariable stepwise logistic regression were preserved. Important radiomics features were identified through least absolute shrinkage and selection operator (LASSO) and univariable analysis. On the basis of radiomics features obtained from PET and CT scans, the radiomics model (R-model) was developed. The significant bio-omics and radiomics features were combined to establish a Multi-omics model (M-model). The above 3 models were established to differentiate MYCN wild from MYCN gain and MYCN amplification (MNA). The calibration curve and receiver operating characteristic (ROC) curve analyses were performed to verify the prediction performance. Post hoc analysis was conducted to compare whether the constructed M-model can distinguish MYCN gain from MNA. Results: The M-model showed excellent predictive performance in differentiating MYCN wild from MYCN gain and MNA, which was better than that of the B-model and R-model [area under the curve (AUC) 0.83, 95% confidence interval (CI): 0.74-0.92 vs. 0.81, 95% CI: 0.72-0.90 and 0.79, 95% CI: 0.69-0.89]. The calibration curve showed that the M-model had the highest reliability. Post hoc analysis revealed the great potential of the M-model in differentiating MYCN gain from MNA (AUC 0.95, 95% CI: 0.89-1). Conclusions: The M-model model based on bio-omics and radiomics features is an effective tool to distinguish MYCN copy number category in pediatric patients with NB.