Neuroblastic Tumors Research Articles

Robot-Assisted Laparoscopic Adrenalectomy: Extended Application in Children

Minimally invasive surgery for paediatric adrenal tumours has evolved, but robot-assisted laparoscopic adrenalectomy (RALA) in children remains poorly studied. The current prospective study aims to demonstrate the safety and efficacy of RALA in treating children with adrenal tumours. A prospective institutional analysis of children presenting with neuroblastic and endocrine tumours treated with RALA was undertaken over a six year-period. For each child, clinical parameters were collected relating to diagnosis, surgery and outcomes. A total 50 RALA were performed; 23 for unilateral neuroblastic tumours (87% neuroblastomas) and 27 for endocrine tumours. Eight neuroblastic tumours (35%) had image-defined risk factors (all due to tumour invading the renal pedicle). Median length of stay was two days. Resection margins were macroscopically clear in all cases. After median follow-up of 2.9 years (1.6-3.9), two children are under treatment for metastatic relapse (high-risk disease) and three died due to refractory disease. Sixteen children had endocrine tumours: pheochromocytoma (n=13), or bilateral nodular adrenocortical hyperplasia with Cushing's syndrome (n=14). One child required non-emergent conversion, and one complication occurred (grade IIIb) after median follow-up of 3.3 years (1.0-5.7). The current study is the largest reported experience in the literature and confirms the safety and effectiveness of RALA in carefully selected children with adrenal tumours. Through an iterative process and in the setting of a dedicated paediatric robotic surgical team indications have been clarified and extended. The current study confirms RALA has particularly utility in patients with severe disease (IDRF+metastatic neuroblastomas) or genetic predisposition syndromes.

Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology

A deep learning model using attention-based multiple instance learning (aMIL) and self-supervised learning (SSL) was developed to perform pathologic classification of neuroblastic tumors and assess MYCN-amplification status using H&E-stained whole slide images from the largest reported cohort to date. The model showed promising performance in identifying diagnostic category, grade, mitosis-karyorrhexis index (MKI), and MYCN-amplification with validation on an external test dataset, suggesting potential for AI-assisted neuroblastoma classification.

Characterisation of Paediatric Neuroblastic Tumours by Quantitative Structural and Diffusion-Weighted MRI

Purpose: To determine the diagnostic accuracy of quantitative diffusion-weighted (DW) MRI apparent diffusion coefficient (ADC) and tumour volumes to differentiate between malignant (neuroblastoma (NB)) and benign types of neuroblastic tumours (ganglioneuroma (GN) and ganglioneuroblastoma (GNB)) using different region-of-interest (ROI) sizes. Materials and Methods: This single-centre retrospective study included malignant and benign paediatric neuroblastic tumours that had undergone DW MRI at diagnosis. The outcome was diagnostic accuracy of the tumour volume from structural and ADC DW MRI, in comparison to histopathology (reference standard). Results: Data from 40 patients (NB, n = 24; GNB, n = 6; GN, n = 10), 18 (45%) females and 22 (55%) males, with a median age at diagnosis of 21 months (NB), 64 months (GNB), and 133 months (GN), respectively, ranging from 0 to 193 months, were evaluated. The area under the receiver operating characteristic (AUROC) curve for ADC for discriminating between neuroblastic tumours’ histopathology for a small ROI was 0.86 (95% CI: 0.75–0.98), and for a large ROI, 0.83 (95% CI: 0.71–0.96). An ADC cut-off value of 1.06 × 10−3 mm2/s was able to distinguish malignant from benign tumours with 83% (68–98%) sensitivity and 75% (95% CI: 54–98%) specificity. Tumour volume was not indicative of malignant vs. benign tumour diagnosis. Conclusions: In this study, both small and large ROIs used to derive ADC DW MRI metrics demonstrated high accuracy to differentiate malignant from benign neuroblastic tumours, with the ADC AUROC for the averaged multiple small ROIs being slightly greater than that of large ROIs, but with overlapping 95% CIs. This should be taken into consideration for standardisation of ROI-related data analysis by international initiatives.

Unraveling the glycosphingolipid metabolism by leveraging transcriptome-weighted network analysis on neuroblastic tumors

BackgroundGlycosphingolipids (GSLs) are membrane lipids composed of a ceramide backbone linked to a glycan moiety. Ganglioside biosynthesis is a part of the GSL metabolism, which involves sequential reactions catalyzed by specific enzymes that in part have a poor substrate specificity. GSLs are deregulated in cancer, thus playing a role as potential biomarkers for personalized therapy or subtype classification. However, the analysis of GSL profiles is complex and requires dedicated technologies, that are currently not included in the commonly utilized high-throughput assays adopted in contexts such as molecular tumor boards.MethodsIn this study, we developed a method to discriminate the enzyme activity among the four series of the ganglioside metabolism pathway by incorporating transcriptome data and topological information of the metabolic network. We introduced three adjustment options for reaction activity scores (RAS) and demonstrated their application in both exploratory and comparative analyses by applying the method on neuroblastic tumors (NTs), encompassing neuroblastoma (NB), ganglioneuroblastoma (GNB), and ganglioneuroma (GN). Furthermore, we interpreted the results in the context of earlier published GSL measurements in the same tumors.ResultsBy adjusting RAS values using a weighting scheme based on network topology and transition probabilities (TPs), the individual series of ganglioside metabolism can be differentiated, enabling a refined analysis of the GSL profile in NT entities. Notably, the adjustment method we propose reveals the differential engagement of the ganglioside series between NB and GNB. Moreover, MYCN gene expression, a well-known prognostic marker in NTs, appears to correlate with the expression of therapeutically relevant gangliosides, such as GD2. Using unsupervised learning, we identified subclusters within NB based on altered GSL metabolism.ConclusionOur study demonstrates the utility of adjusting RAS values in discriminating ganglioside metabolism subtypes, highlighting the potential for identifying novel cancer subgroups based on sphingolipid profiles. These findings contribute to a better understanding of ganglioside dysregulation in NT and may have implications for stratification and targeted therapeutic strategies in these tumors and other tumor entities with a deregulated GSL metabolism.

Robotic Surgery in Paediatric Oncology: Expanding Boundaries and Defining Relevant Indications

This article reviews the establishment and progress of the Multidisciplinary Paediatric Robotic Program in a high-volume paediatric surgery department at Hôpital Necker-Enfants Malades, Paris, France. A major foundational principle of the program was to establish a safe and secure environment for patients and staff, both pre-operatively, intra-operatively and post-operatively. This founding principle when applied systematically has allowed increasing confidence across the program and service. The robotic platform allows for precision surgery when approaching tumours, with freedom of movement adapted to meticulous vascular and organ dissection. Surgical feasibility is based on tumour characteristics, pre-operative imaging, with a focus on vascular and organ involvement, considering goals of surgery and surgical experience. Case complexity has been gradually increased (where appropriate) through an iterative process. The future of surgery is robotic, and even more so image-guided surgery, and this synergy has been instrumental when approaching tumour surgery in children. The current principles that guide application of robot-assisted surgery in paediatric tumours are presented. With this blueprint, excellent oncological outcomes can be achieved while utilising a minimally invasive approach in children with selected endocrine, neuroblastic and renal tumours.

Approach to the paediatric patient with suspected pheochromocytoma or paraganglioma versus neuroblastoma.

Catecholamine producing tumours of childhood include neuroblastic tumours, phaeochromocytoma and paraganglioma (PPGL). PPGL and neuroblastic tumours can arise in similar anatomical locations and clinical presentations can overlap resulting in diagnostic challenges. Distinguishing between these tumour types is critical as management and long-term surveillance strategies differ depending on the diagnosis. Herein we describe two clinical cases and illustrate key considerations in the diagnostic work up of a neuroblastoma versus PPGL for patients presenting with adrenal, pelvic, and retroperitoneal masses in childhood.

Vasoactive Intestinal Peptide-Producing Neuroblastic Tumors: A Rare Cause of Refractory Diarrhea.

Neuroblastic tumors are the most common malignant extracranial solid tumors of childhood. A small subgroup presents chronic incoercible diarrhea due to the tumor's production of vasoactive intestinal peptide (VIP). The hypothesis of an occult tumor is not always considered, which delays and impairs treatment. We aim to identify these patients' characteristics and help alert health professionals to the hypothesis of a neuroblastic tumor in children with chronic diarrhea refractory to the usual approach. We carried out an epidemiological study on all retrievable reports of neuroblastic tumors between 1975 and 2021 described in the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica database (EMBASE), and Latin American & Caribbean Health Sciences Literature (LILACS) databases. Patient information was divided into categories, and we performed a descriptive analysis. We analyzed 96 cases; 83 (86.5%) cases had diarrhea prior to the diagnosis of the neoplasm, 49 (51%) were ganglioneuroblastomas, 69 (71.8%) were abdominal, and 59 of the 60 patients (98%) with reported acid-base disorders had hypokalemia. When serum VIP was reported, the majority of values varied between one and 20 times the upper reference limit. Seventy-two (75%) patients underwent complete tumor resection, and the overall survival rate was 70%. Serum VIP production by neuroblastic tumors is related to cell differentiation and better prognosis. Such children often require intensive hospital support to reverse the malnutrition and acid-base disorders related to this paraneoplastic syndrome. Its early diagnosis and treatment significantly change the prognosis and quality of life. We, therefore, suggest screening for neuroblastic tumors when health professionals encounter unmanageable chronic secretory diarrhea in children with no defined etiology in the usual investigations.

Clinical significance of sarcopenia in children with neuroblastic tumors

PurposeTo elucidate the clinical significance of sarcopenia in children with neuroblastic tumors (NTs).MethodsWe conducted a retrospective observational study and analyzed the z-scores for height, body weight, body mass index, and skeletal muscle index (HT-z, BW-z, BMI-z, and SMI-z) along with the clinical characteristics of 36 children with NTs. SMI-z was calculated from 138 computed tomography scans at diagnosis, during treatment, and at follow-up. The International Neuroblastoma Risk Group classification was used to identify high-risk groups. We analyzed the data at diagnosis for prognostic analysis and changes over time after diagnosis in the HT-z, BW-z, BMI-z, and SMI-z groups.ResultsAmong the four parameters at diagnosis, only SMI-z predicted overall survival (hazard ratio, 0.58; 95% confidence interval, 0.34–0.99). SMI-z, HT-z, and BW-z significantly decreased over time after diagnosis (P < 0.05), while BMI-z did not (P = 0.11). In surviving high-risk NT cases without disease, SMI-z, HT-z, and BW-z significantly decreased over time (P < 0.05), while BMI-z did not (P = 0.43).ConclusionIn children with NT, the SMI-z at diagnosis was a significant prognostic factor and decreased during treatment and follow-up along with HT-z and BW-z. Monitoring muscle mass is important because sarcopenia may be associated with growth impairment.

Robotics and 3D modeling for precision surgery in pediatric oncology

In an attempt to minimize surgical trauma in already vulnerable patients, pediatric surgeons are increasingly using minimally invasive surgery in surgical oncology, with similar outcomes as open surgery. In addition to its technical benefits, robotic surgery allows integration of technological enhancements, such as artificial-intelligence-based software or tri-dimensional (3D) modeling, into the operating room. In this article, we report our experience in robotic-assisted surgery for the resection of pediatric tumors and present current developments in 3D modeling applied to pelvic tumors. Since 2016, 149 oncology cases have been undertaken using the robotic approach. Neuroblastic tumors account for the most part, with a median hospital stay of two days [1–7 days] and very few intraoperative events. The use of robotics was mainly extended to renal tumors (predominantly Wilms tumors) and endocrine tumors, but was found of particular interest for pelvic tumors. Our experience led us to publish a first set of guidelines on robotic surgical oncology, focusing on its apparent contraindications. 3D models derived from preoperative magnetic resonance imaging have been developed for more than 150 patients with solid tumors, but the pelvic area was made a key focus because of its anatomical complexity. In addition to their educational benefits, some of these 3D models were integrated into the robotic console as a surgical aid and proved invaluable for difficult dissections or nerve plexus preservation. As evidenced by the development of robotics and 3D modeling, pediatric oncology is leaning toward ultra-precise surgical resection tailored to the patient and the tumor.

A head-to-head comparison of computed tomography- and magnetic resonance imaging-based radiomics in assessing pediatric peripheral neuroblastic tumor cell behavior.

To compare the performance of radiomics from contrast-enhanced computed tomography (CECT) and non-contrast magnetic resonance imaging (MRI) in assessing cellular behavior in pediatric peripheral neuroblastic tumors (PNTs). A retrospective analysis of 81 PNT patients who underwent venous phase CECT, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI) scans was conducted. The patients were classified into neuroblastoma and ganglioneuroblastoma/ganglioneuroma based on their pathological subtypes. Additionally, they were categorized into favorable histology and unfavorable histology according to the International Neuroblastoma Pathology Classification (INPC). Tumor regions of interest were segmented on CECT, axial T1WI, and axial T2WI images, and radiomics models were developed based on the selected radiomics features. Following five-fold cross-validation, the performance of the radiomics models derived from CECT and MRI was compared using the area under the receiver operating characteristic curve (AUC) and accuracy. For discriminating pathological subtypes, the AUC for CECT radiomics models ranged from 0.765 to 0.870, with an accuracy range of 0.728 to 0.815. In contrast, the AUC for MRI radiomics models ranged from 0.549 to 0.748, with an accuracy range of 0.531 to 0.778. Regarding the discrimination of INPC subgroups, the AUC for CECT radiomics models ranged from 0.503 to 0.759, with an accuracy range of 0.432 to 0.741. Meanwhile, the AUC for MRI radiomics models ranged from 0.512 to 0.739, with an accuracy range of 0.605 to 0.815. CECT radiomics outperforms non-contrast MRI radiomics in evaluating pathological subtypes. When assessing INPC subgroups, CECT radiomics demonstrates comparability with non-contrast MRI radiomics.

Expression of GD2 and GD3 in peripheral neuroblastic tumors.

The aim of this study was to explore the correlation between the expression of GD2 and GD3 and the histopathological types, risk groups, and chemotherapy in peripheral neuroblastic tumors (pNTs) and provide a theoretical basis for the selection of immunotargeted therapy for pNTs. The expression of GD2 and GD3 in samples of pNTs in all 87 cases, including 39 neuroblastomas (NB), 13 ganglion neuroblastomas nodular (GNBn), 19 ganglion neuroblastomas intermixed (GNBi), 16 ganglioneuroma (GN), and 16 paired NB after chemotherapy, were detected by immunohistochemistry (IHC). SPSS 20.0 statistical software was used for statistical analysis, and P < 0.05 was considered statistically significant. The expression of GD2 was higher than that of GD3 (P < 0.001) in all samples. In NB and GNBn, the expression of GD2 was higher than that of GD3 (P < 0.001 and P = 0.02, respectively). The expression of GD2 in NB was higher than that in GNBn (P = 0.015), and GNBn was higher than GNBi (P < 0.001). The expression of GD2 in the high-risk group was significantly higher than that in the medium-risk group and low-risk group (P = 0.019). The expression of GD2 before chemotherapy was higher than that after chemotherapy (P = 0.022). GD2 was expressed in different degrees in tumor-infiltrating lymphocytes. GD2 may be better than GD3 as a target of immunotherapy for pNTs, especially in the same pathological type. NB and GNBn may be more suitable for anti-GD2 immunotherapy. The expression of GD2 on tumor-infiltrating lymphocytes may be related to the side effects of anti-GD2 immunotherapy.

Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors.

Purpose To evaluate the reproducibility of radiomics features extracted from T2-weighted MR images in patients with neuroblastoma. Materials and Methods A retrospective study included 419 patients (mean age, 29 months ± 34 [SD]; 220 male, 199 female) with neuroblastic tumors diagnosed between 2002 and 2023, within the scope of the PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers (ie, PRIMAGE) project, involving 746 T2/T2*-weighted MRI sequences at diagnosis and/or after initial chemotherapy. Images underwent processing steps (denoising, inhomogeneity bias field correction, normalization, and resampling). Tumors were automatically segmented, and 107 shape, first-order, and second-order radiomics features were extracted, considered as the reference standard. Subsequently, the previous image processing settings were modified, and volumetric masks were applied. New radiomics features were extracted and compared with the reference standard. Reproducibility was assessed using the concordance correlation coefficient (CCC); intrasubject repeatability was measured using the coefficient of variation (CoV). Results When normalization was omitted, only 5% of the radiomics features demonstrated high reproducibility. Statistical analysis revealed significant changes in the normalization and resampling processes (P < .001). Inhomogeneities removal had the least impact on radiomics (83% of parameters remained stable). Shape features remained stable after mask modifications, with a CCC greater than 0.90. Mask modifications were the most favorable changes for achieving high CCC values, with a radiomics features stability of 70%. Only 7% of second-order radiomics features showed an excellent CoV of less than 0.10. Conclusion Modifications in the T2-weighted MRI preparation process in patients with neuroblastoma resulted in changes in radiomics features, with normalization identified as the most influential factor for reproducibility. Inhomogeneities removal had the least impact on radiomics features. Keywords: Pediatrics, MR Imaging, Oncology, Radiomics, Reproducibility, Repeatability, Neuroblastic Tumors Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Safdar and Galaria in this issue.

Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology.

A deep learning model using attention-based multiple instance learning (aMIL) and self-supervised learning (SSL) was developed to perform pathologic classification of neuroblastic tumors and assess MYCN-amplification status using H&E-stained whole slide digital images. The model demonstrated strong performance in identifying diagnostic category, grade, mitosis-karyorrhexis index (MKI), and MYCN-amplification on an external test dataset. This AI-based approach establishes a valuable tool for automating diagnosis and precise classification of neuroblastoma tumors.

Interpretable artificial intelligence-based analysis for morphologic classification of neuroblastic tumors.

10023 Background: Rapid and accurate identification of morphologic features of neuroblastic tumors (NTs) is critical for risk stratification and therapeutic decision making. The prognostic value of features like neuroblast differentiation, mitosis-karyorrhexis index (MKI), and Schwannian stromal presence is well established. Deep learning permits objective histopathological analysis, streamlining workflows for pathologists, notably in rare cancers. In rare cancers, our method minimizes bias and optimizes limited data using transfer and self-supervised learning (SSL) for feature extraction, with improved explainability. Here, we used an artificial intelligence-based model to morphologically classify NT tumors and MYCN-amplification. Methods: Annotated H&amp;E-stained slides of diagnostic NT tumor biopsies from the University of Chicago and the Children’s Oncology Group were digitalized. Pathologists defined three binarized measures including diagnostic category (ganglioneuroblastoma/neuroblastoma), grade (differentiating/poorly differentiating), and MKI (low and intermediate/high). MYCN status was abstracted from patient records (amplified/non-amplified). Using Slideflow, our open-source pipeline, we developed an attention-based multiple instance learning model with features extracted by CTransPath, a SSL model pretrained on pan-cancer images from The Cancer Genome Atlas. For each measure, model performance was evaluated using 5-fold cross validation by aggregating k-fold model predictions across multiple metrics. Patients were excluded from a model if the measure of interest was unknown. Feature significance was assessed visually using Class Activation Mapping (Grad-CAM). Results: The mean age of the study cohort (n = 172) was 3.66 years. Of patients with clinical information, 84 of 138 (60.2%) had metastatic disease and 94 of 133 (70.7%) were high-risk. Of the 148 tumors with a diagnostic category of neuroblastoma, 93.2% were poorly differentiated and 25% had high MKI. Of the 135 tumors with known MYCN status, 40 were amplified (29.6%). The final models excelled across all outcomes, performing best for diagnostic category, grade, and MYCN status (Table 1). Physician review of the attention-based heatmaps for all measures highlighted biologically relevant regions such as neuropil. Conclusions: We created a deep learning pipeline for auto-characterization of digitized H&amp;E-stained NT pathology slides. Our approach may also aid in identifying molecular features including MYCN-amplification. Review of heatmaps showed pertinent biological tissue, boosting model reliability.[Table: see text]

Adolescent- and adult-onset neuroblastic tumor: A retrospective multicenter observational study of patients diagnosed in France between 2000 and 2020.

Adult- and adolescent-onset neuroblastomas are rare, with no established therapy. In addition, rare pheochromocytomas may harbor neuroblastic components. This study was designed to collect epidemiological, diagnostic and therapeutic data in order to better define the characteristics of malignant peripheral neuroblastic tumors (MPNT) and composite pheochromocytomas (CP) with MPNT. Fifty-nine adults and adolescents (aged over 15years) diagnosed with a peripheral or composite neuroblastic tumor, who were treated in one of 17 institutions between 2000 and 2020, were retrospectively studied. Eighteen patients with neuroblastoma (NB) or ganglioneuroblastoma (GNB) had locoregional disease, and 28 patients had metastatic stage 4 NB. Among the 13 patients with CP, 12 had locoregional disease. Fifty-eight percent of the population were adolescents and young adults under 24years of age. The probability of 5-year event-free survival (EFS) was 40% (confidence interval: 27%-53%). Outcomes were better for patients with localized tumor than for patients with metastases. For patients with localized tumor, in terms of survival, surgical treatment was the best therapeutic option. Multimodal treatment with chemotherapy, surgery, radiotherapy, and immunotherapy-based maintenance allowed long-term survival for some patients. Adolescent- and adult-onset neuroblastoma appeared to have specific characteristics associated with poorer outcomes compared to pediatric neuroblastoma. Nevertheless, complete disease control improved survival. The presence of a neuroblastic component in pheochromocytoma should be considered when making therapeutic management decisions. The development of specific tools/resources (Tumor Referral Board, Registry, biology, and trials with new agents or strategies) may help to improve outcomes for patients.

A Preliminary Study on the Application of Contrast-Enhanced Ultrasonography in Children With Peripheral Neuroblastic Tumors

The purpose of this study was to retrospectively analyze the characteristics of contrast-enhanced ultrasound (CEUS) images and quantitative parameters of time-intensity curves (TICs) in children's peripheral neuroblastic tumors (pNTs). By comparing the imaging features and quantitative parameters of the TICs of neuroblastoma (NB) and ganglioneuroblastoma (GNB) patients, we attempted to identify the distinguishing points between NB and GNB. A total of 35 patients confirmed to have pNTs by pathologic examination were included in this study. Each child underwent CEUS with complete imaging data (including still images and at least 3 min of video files). Twenty-four patients were confirmed to have NB, and 11 were considered to have GNB according to differentiation. The CEUS image features and quantitative parameters of the TICs of all lesions were analyzed to determine whether there were CEUS-related differences between the two types of pNT. There was a significant difference in the enhancement patterns of the CEUS features (χ2 = 5.303, p < 0.05), with more “peripheral-central” enhancement in the NB group and more “central-peripheral” enhancement in the GNB group. In the TIC, the rise time and time to peak were significantly different (p < 0.05). The receiver operating characteristic curve showed that the probability of ganglion cell NB increased significantly after RT > 15.29, with a sensitivity of 0.636 and a specificity of 0.958. When the peak time was greater than 16.155, the probability of NB increased significantly, with a sensitivity of 0.636 and a specificity of 0.958. The CEUS features of NB and GNB patients are very similar, and it is difficult to distinguish them. Rise time and time to peak may be useful in identifying GNB and NB, but the sample size of this study was small, and the investigation was only preliminary; a larger sample size is needed to support these conclusions.

Robotic-assisted Pediatric Thoracic and Abdominal Tumor Resection: An Initial Multi-center Review

IntroductionRobotic-assisted minimally invasive surgery (RA-MIS) for tumor resection is an emerging technology in the pediatric population with significant promise but unproven safety and feasibility. MethodsA multi-center retrospective review of patients ≤18 years undergoing RA-MIS tumor resection from December 2015–March 2023 was performed. Patient demographics, perioperative variables, and complication rates were analyzed. ResultsThirty-nine procedures were performed on 38 patients (17 thoracic, 22 abdominal); 37% female and 68% non-Hispanic White. Median age at surgery was 8.3 years (IQR 5.7, 15.7); the youngest was 1.7 years-old. Thoracic operations included resections of neuroblastic tumors (n = 16) and a single paraganglioma. The most common abdominal operations included resections of neuroblastic tumors (n = 5), pheochromocytomas (n = 3), and angiomyolipomas (n = 3). Six patients underwent retroperitoneal lymph node dissection (RPLND) for paratesticular tumors. Median operating time for the cohort was 2:52 h (IQR 2:04, 4:31). Two thoracic cases required open conversion due to poor visualization and lack of working domain. All patients underwent complete tumor resection; one had tumor spillage from a positive margin (Wilms tumor). Median LOS was 1.5 days (IQR 1.1, 3.0). Postoperatively, one patient developed a chyle leak requiring interventional radiology drainage, but none required a return to the operating room. ConclusionsRobotic-assisted surgery is safe and feasible for tumor resection in carefully selected pediatric patients, achieving complete resection with minimal morbidity and short LOS. Resection should be performed by those with robotic expertise for optimal outcomes. Level of EvidenceIV. Type of StudyOriginal Clinical Research.

Current vaccination status and safety of children with peripheral neuroblastoma in the real-world.

peripheral neuroblastic tumors (pNT) have high incidence and mortality, and infants are prone to various infectious diseases. The purpose of this study is to understand the immunization status of children with pNT in the real-world and the incidence of adverse reactions after vaccination, and to evaluate the feasibility of vaccination and the influencing factors of vaccination. Children with pNT treated in the Children's Hospital Affiliated to Zhejiang University from January 1, 2011 to December 1, 2021 were included. By referring to medical records, the vaccination history of the national immunization program (NIP) vaccines and the occurrence of adverse events following immunization(AEFI), current status and safety of immunization in children with pNT in the real-world were analyzed. Among 784 children with pNT, 394 were able to obtain the history of vaccination. The overall vaccination rate of NIP vaccines was 71.49% before chemotherapy and 37.67% after chemotherapy, and the recovery time of vaccination after treatment was 16.00 (6.00,24.00) months. Age, time of tumor diagnosis and disease classification were significantly correlated with vaccination. AEFI reported an incidence of 0.23‰. The vaccination rate of children with pNT is generally low, especially the vaccination rate after chemotherapy. The vaccination safety is good, children should be encouraged to immunize.

Prediction of High-Risk Neuroblastoma Among Neuroblastic Tumors Using Radiomics Features Derived from Magnetic Resonance Imaging: A Pilot Study.

This study aimed to predict high-risk neuroblastoma among neuroblastic tumors using radiomics features extracted from MRI. Pediatric patients (age≤18 years) diagnosed with neuroblastic tumors who had pre-treatment MR images available were enrolled from institution A from January 2010 to November 2019 (training set) and institution B from January 2016 to January 2022 (test set). Segmentation was performed with regions of interest manually drawn along tumor margins on the slice with the widest tumor area by two radiologists. First-order and texture features were extracted and intraclass correlation coefficients (ICCs) were calculated. Multivariate logistic regression (MLR) and random forest (RF) models from 10-fold cross-validation were built using these features. The trained MLR and RF models were tested in an external test set. Thirty-two patients (M:F=23:9, 26.0±26.7 months) were in the training set and 14 patients (M:F=10:4, 33.4±20.4 months) were in the test set with radiomics features (n=930) being extracted. For 10 of the most relevant features selected, intra- and inter-observer variability was moderate to excellent (ICCs 0.633-0.911, 0.695-0.985, respectively). The area under the receiver operating characteristic curve (AUC) was 0.94 (sensitivity 67%, specificity 91%, and accuracy 84%) for the MLR model and the average AUC was 0.83 (sensitivity 44%, specificity 87%, and accuracy 75%) for the RF model from 10-fold cross-validation. In the test set, AUCs of the MLR and RF models were 0.94 and 0.91, respectively. An MRI-based radiomics model can help predict high-risk neuroblastoma among neuroblastic tumors.

Successful endoscopic approach for peripheral neuroblastic tumors in children.

Recently, reports of endoscopic approaches for neuroblastoma, ganglioneuroblastoma, and ganglioneuroma (peripheral neuroblastic tumor; PNTs) have been increasing. This study aimed to clarify the indications for endoscopic surgery for PNTs. Pediatric patients who underwent endoscopic surgery for PNTs at our institution were included in this study. Image-defined risk factors (IDRFs) were analyzed using preoperative computed tomography (CT). Twenty-four patients underwent endoscopic surgery for PNTs. The diagnoses included neuroblastoma (n = 11), ganglioneuroma (n = 10), and ganglioneuroblastoma (n = 3). Regarding the tumor site, there were 18 cases of adrenal tumors, five cases of mediastinal tumors, and one case of retroperitoneal tumors. Image-defined risk factors were positive in eight cases (contacted with a renal vessel, n = 6; compression of principal bronchi, n = 2). Complete resection was accomplished in 21 cases (14 of 16 IDRF-negative cases and seven of eight IDRF-positive cases). All patients survived without recurrence during the follow-up period. The CT findings of contact with renal vessels and compression of principal bronchi do not seem to be indicators of incomplete resection. An endoscopic approach to PNTs in pediatric patients is feasible with a good prognosis if patients are selected strictly.