Comparison of three different methods to detect bone marrow involvement in patients with neuroblastoma

Evaluating Bone Marrow Involvement in Pediatric Neuroblastoma: Traditional Methods and Emerging Technologies-A Systematic Review

Neuroblastoma (NB) is the most common extracranial solid neoplasm affecting the pediatric population. It shows a high prevalence of bone marrow infiltration (BMI), which substantially impacts the disease's staging and prognostic assessment. Conventional methodologies, including bone marrow biopsy (BMB) and aspirate (BMA), have been extensively employed; nevertheless, the advent of novel technologies presents a promising avenue for diagnostic accuracy. This systematic review is designed to critically analyze and compare the established techniques (BMB and BMA) versus novel diagnostic approaches-such as immunocytology, RT-qPCR, and multiparametric flow cytometry (FCM), along with functional imaging like MIBG scintigraphy and FDG-PET/CT-in assessing BMI in pediatric NB. An exhaustive search was performed across the PubMed and Embase databases, identifying 2694 scholarly articles. Following a meticulous screening process and the application of inclusion criteria centered on diagnostic accuracy, sensitivity, and specificity about BMI, a total of 140 articles were selected for qualitative analysis. While BMB remains the gold standard for diagnosing and staging BMI in NB, recent advances in molecular techniques and functional imaging have shown superior sensitivity and specificity. Immunocytology and RT-qPCR can detect minimal residual disease (MRD) with higher sensitivity compared to traditional methods. Functional imaging modalities, particularly FDG-PET/CT and MIBG scintigraphy, have demonstrated improved accuracy in assessing bone marrow involvement with the added advantage of evaluating the entire bone marrow, overcoming the limitations of focal sampling in BMB. The integration of advanced molecular diagnostics and functional imaging with traditional biopsy methods enhances the accuracy of BMI in NB.

A multiparameter diagnostic model based on 2-[18F]FDG PET/CT metabolic parameters and clinical variables can differentiate high-risk and non-high-risk pediatric neuroblastoma under the revised Children's Oncology Group classification system

Background

It is crucial to assist neuroblastoma (NB) pediatric patients in accurate risk stratification based on the revised Children's Oncology Group (COG) classification system through non-invasive examinations. This study assessed the diagnostic efficacy of integrating multiparametric 2-[18F]fluoro-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) metabolic parameters with clinical variables to differentiate between high- and non-high-risk pediatric NB according to the revised COG classification system.

Methods

A retrospective study was conducted involving a total of 89 pediatric NB patients, including 71 high-risk and 18 non-high-risk patients, who underwent pre-treatment 2-[18F]FDG PET/CT imaging. All patients were confirmed by pathology, and clinical variables were collected. The metabolic parameters of 2-[18F]FDG PET/CT were evaluated, including maximum standard uptake value (SUVmax), mean standard uptake value (SUVmean), metabolic tumor volume (MTV) and total lesion glycolysis (TLG). The differences in diagnostic efficacy were evaluated by comparing the differences between receiver operating characteristic (ROC) curves. The DeLong test, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were utilized to assess the enhancement in diagnostic performance. The clinical utility of the diagnostic model was evaluated through decision curve analysis (DCA).

Results

The ROC curve analysis of TLG showed the highest differentiating diagnostic value [sensitivity =0.620, 95% confidence interval (CI): 0.496-0.730; specificity =0.833, 95% CI: 0.577-0.956; area under the curve (AUC) 0.764, 95% CI: 0.648-0.881; cut-off =234.70] among metabolic parameters of 2-[18F]FDG PET/CT. After multivariate forward stepwise logistic regression (LR) analysis, the combined diagnostics model of age, gender, the International Neuroblastoma Risk Group Staging System (INRGSS) stage (L1/L2 vs. M/MS) and TLG resulted in the highest AUC of 0.932 (95% CI: 0.867-0.998; sensitivity =0.901, 95% CI: 0.802-0.956; specificity =0.889, 95% CI: 0.604-0.978). Compared to TLG, the diagnostic efficiency of the model demonstrated a significant improvement [Z=3.089, P<0.001; IDI =0.388, P<0.001; NRI (categorical) =0.736, P<0.001]. The DCA further validated the clinical efficacy of the model.

Conclusions

The multiparameter diagnosis model based on 2-[18F]FDG PET/CT metabolic parameters and clinical parameters had excellent value in the differential diagnosis of high- and non-high-risk pediatric NB under the revised COG classification system.

Comparison of Bone Marrow Biopsy and Flow Cytometry in Demonstrating Bone Marrow Metastasis of Neuroblastoma

OBJECTIVE

This study aimed to compare bone marrow aspirate (BMA) multicolor flow cytometry (MFC) analysis and bone marrow biopsy (BMB) in detecting bone marrow (BM) involvement in children with neuroblastoma (NB) at diagnosis and during follow-up.

MATERIALS AND METHODS

A total of 132 BM samples from 39 patients (M/F ratio: 19/20; median age: 38 months) with neuroblastoma were simultaneously obtained for evaluation. The samples were investigated for BM involvement using BMB and MFC.

RESULTS

A comparison between MFC (n: 60) and BMB (n: 60) was possible for 120 samples. When BMB was considered as the reference standard, MFC had diagnostic sensitivity, specificity, positive predictive value, and negative predictive value of 86%, 58%, 54%, and 88%, respectively, and values of 90%, 57%, 60%, and 89%, respectively, at diagnosis. The median proportion of CD45-/CD56+ cells in MFC was 0.028% (range 0-35%). The event-free survival (EFS) rates for MFC (+) and MFC (-) patients according to the analysis results of the BM samples at the time of diagnosis were 70.6% and 81.8%, respectively (p = 0.607), and the overall survival (OS) rates were 88.2% in MFC (+) patients and 90.9% in MFC (-) patients (p = 0.583).

CONCLUSION

Multicolor flow cytometry may be used as an adjunct to cytomorphology to achieve more sensitive and accurate results as an objective, quantitative method with fast results in detecting bone marrow involvement in children with NB.

Predicting Bone Marrow Metastasis in Neuroblastoma: An Explainable Machine Learning Approach Using Contrast-Enhanced Computed Tomography Radiomics Features

PURPOSE

To predict bone marrow metastasis in neuroblastoma using contrast-enhanced computed tomography (CECT) radiomics features and explainable machine learning.

METHODS

This cohort study retrospectively included a total of 345 neuroblastoma patients who underwent testing for bone marrow metastatic status. Tumor lesions on CECT images were delineated by two radiologists, and 1409 radiomics features were extracted. Correlation analysis, Least Absolute Shrinkage and Selection Operator regression, and one-way analysis of variance were used to identify radiomics features associated with bone marrow metastasis. A predictive model for bone marrow metastasis was then developed using the support vector machine algorithm based on the selected radiomics features. The performance of the radiomics model was evaluated using the area under the curve (AUC), 95% confidence interval (CI), accuracy, sensitivity, and specificity.

RESULTS

The radiomics model included 16 features, with a predominant focus on texture features (12/16, 75%). In the training set, the model demonstrated an AUC of 0.891 (95% CI: 0.848-0.933), an accuracy of 0.831 (95% CI: 0.829-0.832), a sensitivity of 0.893 (95% CI: 0.840-0.946), and a specificity of 0.757 (95% CI: 0.677-0.837). In the test set, the AUC, accuracy, sensitivity, and specificity were 0.807 (95% CI: 0.720-0.893), 0.767 (95% CI: 0.764-0.770), 0.696 (95% CI: 0.576-0.817), and 0.851 (95% CI: 0.749-0.953), respectively.

CONCLUSION

Radiomics features extracted from CECT images are associated with the presence of bone marrow metastasis in neuroblastoma, providing potential new imaging biomarkers for predicting bone marrow metastasis in this disease.

Case series on clinical applications of liquid biopsy in pediatric solid tumors: towards improved diagnostics and disease monitoring

Background and aims

Solid tumors account for about 30% of all pediatric cancers. The diagnosis is typically based on histological and molecular analysis of a primary tumor biopsy. Liquid biopsies carry several advantages over conventional tissue biopsy. However, their use for genomic analysis and response monitoring of pediatric solid tumors is still in experimental stages and mostly performed retrospectively without direct impact on patient management. In this case series we discuss six clinical cases of children with a solid tumor for whom a liquid biopsy assay was performed and demonstrate the potential of liquid biopsy for future clinical decision making.

Methods

We performed quantitative real-time PCR (RT-qPCR), droplet digital PCR (ddPCR) or reduced representation bisulphite sequencing of cell-free DNA (cfRRBS) on liquid biopsies collected from six pediatric patients with a solid tumor treated between 2017 and 2023 at the Princess Máxima Center for Pediatric Oncology in the Netherlands. Results were used to aid in clinical decision making by contribution to establish a diagnosis, by prognostication and response to therapy monitoring.

Results

In three patients cfRRBS helped to establish the diagnosis of a rhabdomyosarcoma, an Ewing sarcoma and a neuroblastoma (case 1-3). In two patients, liquid biopsies were used for prognostication, by MYCN ddPCR in a patient with neuroblastoma and by RT-qPCR testing rhabdomyosarcoma-specific mRNA in bone marrow of a patient with a rhabdomyosarcoma (case 4 and 5). In case 6, mRNA testing demonstrated disease progression and assisted clinical decision making.

Conclusion

This case series illustrates the value of liquid biopsy. We further demonstrate and recommend the use of liquid biopsies to be used in conjunction with conventional methods for the determination of metastatic status, prognostication and monitoring of treatment response in patients with pediatric solid tumors.

Development and validation of a CT-based radiomics signature for identifying high-risk neuroblastomas under the revised Children's Oncology Group classification system

BACKGROUND

To develop and validate a radiomics signature based on computed tomography (CT) for identifying high-risk neuroblastomas.

PROCEDURE

This retrospective study included 339 patients with neuroblastomas, who were classified into high-risk and non-high-risk groups according to the revised Children's Oncology Group classification system. These patients were then randomly divided into a training set (n = 237) and a testing set (n = 102). Pretherapy CT images of the arterial phase were segmented by two radiologists. Pyradiomics package and FeAture Explorer software were used to extract and process radiomics features. Radiomics models based on linear discriminant analysis (LDA), logistic regression (LR), and support vector machine (SVM) were constructed, and the area under the curve (AUC), 95% confidence interval (CI), and accuracy were calculated.

RESULTS

The optimal LDA, LR, and SVM models had 11, 12, and 14 radiomics features, respectively. The AUC of the LDA model in the training and testing sets were 0.877 (95% CI: 0.833-0.921) and 0.867 (95% CI: 0.797-0.937), with an accuracy of 0.823 and 0.804, respectively. The AUC of the LR model in the training and testing sets were 0.881 (95% CI: 0.839-0.924) and 0.855 (95% CI: 0.781-0.930), with an accuracy of 0.823 and 0.804, respectively. The AUC of the SVM model in the training and testing sets were 0.879 (95% CI: 0.836-0.923) and 0.862 (95% CI: 0.791-0.934), with an accuracy of 0.827 and 0.804, respectively.

CONCLUSIONS

CT-based radiomics is able to identify high-risk neuroblastomas and may provide additional image biomarkers for the identification of high-risk neuroblastomas.

Ferroptosis Inducers Kill Mesenchymal Stem Cells Affected by Neuroblastoma

Bone marrow (BM) is the most common site of neuroblastoma (NB) metastasis, and its involvement represents poor patient prognosis. In accordance with the "seed and soil" theory of tumor metastasis, BM provides a favorable environment for NB metastasis while bone marrow mesenchymal stem cells (BMSCs) have been recognized as a central part of tumor stroma formation. Yet, there is currently no effective method for intervening these BMSCs. We found that BMSCs affected by NB (NB-BMSCs) could significantly promote NB growth and migration. Additionally, tumor cell-endowed BMSCs showed stronger resistance to several chemotherapeutic agents. Surprisingly, NB-BMSCs were more sensitive to ferroptosis than normal BMSCs. NB-BMSCs had lower levels of intracellular free iron while synthesizing more iron-sulfur clusters and heme. Moreover, the Xc^-/glutathione/glutathione peroxidase 4 (Xc^-/GSH/GPX4) pathway of the anti-ferroptosis system was significantly downregulated. Accordingly, ferroptosis inducers erastin and RAS-selective lethal 3 (RSL3) could significantly kill NB-BMSCs with limited effects on normal BMSCs. BMSCs from NB patients with BM metastasis also showed poor anti-ferroptosis ability compared with those from NB patients without BM metastasis. In vivo studies suggested that co-injection of mice with BMSCs and NB cells could significantly promote the growth of tumor tissues compared with injecting NB cells alone. However, treatment with erastin or RSL3 resulted in the opposite effect to some extent. Our results revealed that NB-BMSCs were vulnerable to ferroptosis from downregulation of the Xc^-/GSH/GPX4 pathway. Ferroptosis inducers could effectively kill NB-BMSCs, but not normal BMSCs. This study provides possible new ideas for the treatment of tumor-associated BMSCs in NB patients.

Lidocaine relieves spinal cord ischemia-reperfusion injury via long non-coding RNA MIAT-mediated Notch1 downregulation

Microglial activation and inflammatory response play a critical role in spinal cord ischemia-reperfusion injury (SCIRI). This study aimed to investigate whether lidocaine relieves SCIRI via modulating MIAT-mediated Notch1 downregulation. Mouse SCIRI was induced by the obstruction of the aortic arch. Lidocaine was injected after reperfusion. Microglial activation and inflammatory response were assessed by Iba1, interleukin 1 beta (IL-1β), and tumor necrosis factor alpha (TNF-α) levels. The interaction between MIAT and Notch1 was assessed by RNA pull-down and RNA immunoprecipitation assays. Lidocaine treatment relieved SCIRI by reducing Iba1 and serum TNF-α and IL-1β levels. After lidocaine treatment, MIAT expression was elevated in lipopolysaccharide- (LPS-) induced BV2 cells. The interference of MIAT and the overexpression of MIAT and Notch1 restored TNF-α and IL-1β levels in supernatants. Notch1 protein was existent in MIAT-pull-down compounds, and the expression of MIAT was markedly elevated in Notch1-immunoprecipitants. The overexpression of MIAT markedly promoted the degradation of Notch1 and increased the level of ubiquitin-bound Notch1 complex. The therapeutic effect of lidocaine on SCIRI mice could be reversed by adeno-associated virus-mediated MIAT knockdown. In conclusion, lidocaine treatment relieved SCIRI via inhibiting microglial activation and reducing the inflammatory response. The molecular mechanism was partly through MIAT-mediated Notch1 downregulation.