The Diagnostic Value of 18F-FDG PET/CT Bone Marrow Uptake Pattern in Detecting Bone Marrow Involvement in Pediatric Neuroblastoma Patients

Predicting event-free survival after induction of remission in high-risk pediatric neuroblastoma: combining 123I-MIBG SPECT-CT radiomics and clinical factors

BACKGROUND

Accurately quantifying event-free survival after induction of remission in high-risk neuroblastoma can lead to better subsequent treatment decisions, including whether more aggressive therapy or milder treatment is needed to reduce unnecessary treatment side effects, thereby improving patient survival.

OBJECTIVE

To develop and validate a 123I-metaiodobenzylguanidine (MIBG) single-photon emission computed tomography-computed tomography (SPECT-CT)-based radiomics nomogram and evaluate its value in predicting event-free survival after induction of remission in high-risk neuroblastoma.

MATERIALS AND METHODS

One hundred and seventy-two patients with high-risk neuroblastoma who underwent an 123I-MIBG SPECT-CT examination were retrospectively reviewed. Eighty-seven patients with high-risk neuroblastoma met the final inclusion and exclusion criteria and were randomized into training and validation cohorts in a 7:3 ratio. The SPECT-CT images of patients were visually analyzed to assess the Curie score. The 3D Slicer software tool was used to outline the region of interest of the lumbar 3-5 vertebral bodies on the SPECT-CT images. Radiomics features were extracted and screened, and a radiomics model was constructed with the selected radiomics features. Univariate and multivariate Cox regression analyses were used to determine clinical risk factors and construct the clinical model. The radiomics nomogram was constructed using multivariate Cox regression analysis by incorporating radiomics features and clinical risk factors. C-index and time-dependent receiver operating characteristic curves were used to evaluate the performance of the different models.

RESULTS

The Curie score had the lowest efficacy for the assessment of event-free survival, with a C-index of 0.576 and 0.553 in the training and validation cohorts, respectively. The radiomics model, constructed from 11 radiomics features, outperformed the clinical model in predicting event-free survival in both the training cohort (C-index, 0.780 vs. 0.653) and validation cohort (C-index, 0.687 vs. 0.667). The nomogram predicted the best prognosis for event-free survival in both the training and validation cohorts, with C-indices of 0.819 and 0.712, and 1-year areas under the curve of 0.899 and 0.748, respectively.

CONCLUSION

123I-MIBG SPECT-CT-based radiomics can accurately predict the event-free survival of high-risk neuroblastoma after induction of remission The constructed nomogram may enable an individualized assessment of high-risk neuroblastoma prognosis and assist clinicians in optimizing patient treatment and follow-up plans, thereby potentially improving patient survival.

Predictive value of 18 F-FDG PET/CT versus bone marrow biopsy and aspiration in pediatric neuroblastoma

BACKGROUND

Neuroblastoma (NB) is the most prevalent solid extracranial malignancy in children, often with bone marrow metastases (BMM) are present. The conventional approach for detecting BMM is bone marrow biopsy and aspiration (BMBA). 18 F-fluorodeoxyglucose-positron emission tomography/computed tomography (18 F-FDG PET/CT) has become a staple for staging and is also capable of evaluating marrow infiltration. The consensus on the utility of 18 F-FDG PET/CT for assessing BMM in NB patients is still under deliberation.

METHODS

This retrospective study enrolled 266 pediatric patients with pathologically proven NB. All patients had pretherapy FDG PET/CT. BMBA, clinical, radiological, and follow-up data were also collected. The diagnostic accuracy of BMBA and 18 F-FDG PET/CT was assessed.

RESULTS

BMBAs identified BMM in 96 cases (36.1%), while 18 F-FDG PET/CT detected BMI in 106 cases (39.8%) within the cohort. The initial sensitivity, positive predictive value (PPV), specificity, and negative predictive value (NPV) of 18 F-FDG PET/CT were 93.8%, 84.9%, 90.6%, and 96.3%, respectively. After treatment, these values were 92.3%, 70.6%, 97.3%, and 99.4%, respectively. The kappa statistic, which measures agreement between BMBA and 18 F-FDG PET/CT, was 0.825 before treatment and 0.784 after treatment, with both values indicating a substantial agreement (P = 0.000). Additionally, the amplification of MYCN and a positive initial PET/CT scan were identified as independent prognostic factors for overall survival (OS).

CONCLUSION

18 F-FDG-PET/CT is a valuable method for evaluating BMM in NB. The routine practice of performing a BMBA without discrimination may need to be reassessed. Negative result from 18 F-FDG-PET/CT could potentially spare children with invasive bone marrow biopsies.

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.

Computed tomography-based radiomics to assess risk stratification in pediatric malignant peripheral neuroblastic tumors

This study aimed to develop and validate an analysis system based on preoperative computed tomography (CT) to predict the risk stratification in pediatric malignant peripheral neuroblastic tumors (PNTs). A total of 405 patients with malignant PNTs (184 girls and 221 boys; mean age, 33.8 ± 29.1 months) were retrospectively evaluated between January 2010 and June 2018. Radiomic features were extracted from manually segmented tumors on preoperative CT images. Spearman's rank correlation coefficient and the least absolute shrinkage and selection operator (LASSO) were used to eliminate redundancy and select features. A risk model was built to stratify low-, intermediate-, and high-risk groups. An image-defined risk factor (IDRFs) model was developed to classify 266 patients with malignant PNTs and one or more IDRFs into high-risk and non-high-risk groups. The performance of the predictive models was evaluated with respect to accuracy (Acc) and receiver operating characteristic (ROC) curve, including the area under the ROC curve (AUC). The risk model demonstrated good discrimination capability, with an area under the curve (AUC) of 0.903 to distinguish high-risk from non-high-risk groups, and 0.747 to classify intermediate- and low-risk groups. In the IDRF-based risk model with the number of IDRFs, the AUC was 0.876 for classifying the high-risk and non-high-risk groups. Radiomic analysis based on preoperative CT images has the potential to stratify the risk of pediatric malignant PNTs. It had outstanding efficiency in distinguishing patients in the high-risk group, and this predictive model of risk stratification could assist in selecting optimal aggressive treatment options.

Comparing the diagnostic value of 18F-FDG PET/CT scan and bone marrow biopsy in newly diagnosed pediatric neuroblastoma and ganglioneuroblastoma

Objective

This study aims to compare the diagnostic value of ¹⁸F-fluorodeoxyglucose (18-FDG) positron emission tomography (PET)/computed tomography (CT) (¹⁸F-FDG PET/CT) scan and bone marrow biopsy (BMB) for evaluating bone marrow infiltration (BMI) in newly diagnosed pediatric neuroblastoma (NB) and ganglioneuroblastoma (GNB).

Methods

We retrospectively reviewed 51 patients with newly diagnosed NB and GNB between June 1, 2019 and May 31, 2022. Each patient had undergone ¹⁸F-FDG PET/CT and BMB within 1 week and received no treatment. Clinical data were collected and statistically analyzed, including age, sex, pathologic type, and laboratory parameters. ¹⁸F-FDG PET/CT and BMB revealed the result of bone lesions.

Results

A concordance analysis showed that, in this study population, ¹⁸F-FDG PET/CT and BMB were in moderate agreement (Cohen's Kappa = 0.444; p = 0.001), with an absolute agreement consistency of 72.5% (37 of 51). The analysis of the receiver operating characteristic (ROC) curve determined that the areas under the ROC curve (AUCs) of SUV_BM and SUV/HE-SUVmax were 0.971 (95% CI: 0.911-1.000; p < 0.001) and 0.917 (95% CI: 0.715-1.000; p < 0.001) to predict bone-bone marrow involvement (BMI), respectively.

Conclusion

¹⁸F-FDG PET/CT detects BMI with good diagnostic accuracy and can reduce unnecessary invasive inspections in newly diagnosed pediatric NB and GNB, especially patterns C and D. The analysis of the semi-quantitative uptake of ¹⁸F-FDG, including SUV_BM and SUV_BM/HE-SUVmax, enables an effective differentiation between patterns A and B.

18F-FDG PET/CT-based radiomics nomogram could predict bone marrow involvement in pediatric neuroblastoma

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-022-01283-8.