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Objective To investigate the diagnostic value of xSPECT/CT-based tomographic fusion imaging in children with bone metastases. Methods Clinical and imaging data of 152 children with suspected bone metastases examined in our department were collected. All children underwent whole-body bone imaging, xSPECT/CT, and SPECT/CT tomographic fusion imaging. xSPECT/CT and SPECT/CT tomographic fusion images were compared and analyzed to evaluate the diagnostic value of xSPECT/CT tomographic fusion imaging in children with bone metastases. The diagnostic confidence of nuclear medicine physicians of two methods was also compared. Results The sensitivity, specificity, and accuracy of xSPECT/CT tomographic fusion imaging in the diagnosis of bone metastases in children were 93.3%, 91.5%, and 92.8%, respectively; the sensitivity, specificity, and accuracy of SPECT/CT tomographic fusion imaging in the diagnosis of bone metastases in children were 85.7%, 85.1%, and 85.5%, respectively. xSPECT/CT tomographic fusion imaging could improve the diagnostic confidence of nuclear medicine physicians and the difference was statistically significant [5 （2-5） vs. 3 （2-4）, P < 0.05]. Conclusion xSPECT/CT tomographic fusion imaging can effectively enhance the diagnostic confidence and diagnostic efficacy of nuclear medicine physicians in the diagnosis of bone metastases in children, which can help to diagnose bone metastases in children at an early stage, and further improve their clinical prognosis.

Objective: To develop and validate an 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based radiomics nomogram for non-invasively prediction of bone marrow involvement (BMI) in pediatric neuroblastoma. Methods: A total of 133 patients with neuroblastoma were retrospectively included and randomized into the training set (n = 93) and test set (n = 40). Radiomics features were extracted from both CT and PET images. The radiomics signature was developed. Independent clinical risk factors were identified using the univariate and multivariate logistic regression analyses to construct the clinical model. The clinical-radiomics model, which integrated the radiomics signature and the independent clinical risk factors, was constructed using multivariate logistic regression analysis and finally presented as a radiomics nomogram. The predictive performance of the clinical-radiomics model was evaluated by receiver operating characteristic curves, calibration curves and decision curve analysis (DCA). Results: Twenty-five radiomics features were selected to construct the radiomics signature. Age at diagnosis, neuron-specific enolase and vanillylmandelic acid were identified as independent predictors to establish the clinical model. In the training set, the clinical-radiomics model outperformed the radiomics model or clinical model (AUC: 0.924 vs. 0.900, 0.875) in predicting the BMI, which was then confirmed in the test set (AUC: 0.925 vs. 0.893, 0.910). The calibration curve and DCA demonstrated that the radiomics nomogram had a good consistency and clinical utility. Conclusion: The 18F-FDG PET/CT-based radiomics nomogram which incorporates radiomics signature and independent clinical risk factors could non-invasively predict BMI in pediatric neuroblastoma. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the diagnostic performance of combined multiparametric 18F-fluorodeoxyglucose positron emission tomography (18FDG PET) with clinical characteristics in differentiating thymic epithelial tumors (TETs) from thymic lymphomas.Patients and Methods: A total of 173 patients with 80 TETs and 93 thymic lymphomas who underwent 18F-FDG PET/CT before treatment were enrolled in this retrospective study. All patients were confirmed by pathology, and baseline characteristics and clinical data were also collected. The semi-parameters of 18F-FDG PET/CT, including lesion size, SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), TLG (total lesion glycolysis), MTV (metabolic tumor volume) and SUVR (tumor-to-normal liver standard uptake value ratio) were evaluated. The differential diagnostic efficacy was evaluated using the receiver operating characteristic (ROC) curve. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI), and Delong test were used to evaluate the improvement in diagnostic efficacy. The clinical efficacy was evaluated by decision curve analysis (DCA).Results: Age, clinical symptoms, and metabolic parameters differed significantly between patients with TETs and thymic lymphomas. The ROC curve analysis of SUVR showed the highest differentiating diagnostic value (sensitivity = 0.763; specificity = 0.888; area under the curve [AUC] = 0.881). The combined diagnostics model of age, clinical symptoms and SUVR resulted in the highest AUC of 0.964 (sensitivity = 0.882, specificity = 0.963). Compared with SUVR, the diagnostic efficiency of the model was improved significantly. The DCA also confirmed the clinical efficacy of the model.Conclusions: The multiparameter diagnosis model based on 18F-FDG PET and clinical characteristics had excellent value in the differential diagnosis of TETs and thymic lymphomas. [ABSTRACT FROM AUTHOR]