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Featured Application: This study explores the potential of two popular open-source AI models, ChatGPT 4o (omni) and Gemini Pro, to analyze MRI video sequences depicting a pediatric brain tumor. We aimed to evaluate whether these AI models can accurately identify and analyze the content of MRI videos showing a medulloblastoma in sagittal and coronal planes. Our findings revealed that while Gemini Pro correctly identified the video as an MRI, it did not attempt a detailed analysis, deferring to medical specialists. Conversely, ChatGPT 4o performed some image analysis but failed to recognize the video content as MRI. Both models struggled with tumor identification, suggesting that further improvements and specialized training are needed for these AI models to effectively support medical diagnostics. Over the past year, there has been a significant rise in interest in the application of open-source artificial intelligence models (OSAIM) in the field of medicine. An increasing number of studies focus on evaluating the capabilities of these models in image analysis, including magnetic resonance imaging (MRI). This study aimed to investigate whether two of the most popular open-source AI models, namely ChatGPT 4o and Gemini Pro, can analyze MRI video sequences with single-phase contrast in sagittal and frontal projections, depicting a posterior fossa tumor corresponding to a medulloblastoma in a child. The study utilized video files from single-phase contrast-enhanced head MRI in two planes (frontal and sagittal) of a child diagnosed with a posterior fossa tumor, type medulloblastoma, confirmed by histopathological examination. Each model was separately provided with the video file, first in the sagittal plane, analyzing three different sets of commands from the most general to the most specific. The same procedure was applied to the video file in the frontal plane. The Gemini Pro model did not conduct a detailed analysis of the pathological change but correctly identified the content of the video file, indicating it was a brain MRI, and suggested that a specialist in the field should perform the evaluation. Conversely, ChatGPT 4o conducted image analysis but failed to recognize that the content was MRI. The attempts to detect the lesion were random and varied depending on the plane. These models could not accurately identify the video content or indicate the area of the neoplastic change, even after applying detailed queries. The results suggest that despite their widespread use in various fields, these models require further improvements and specialized training to effectively support medical diagnostics. [ABSTRACT FROM AUTHOR]

Purpose: Various surgical nuances of the telovelar approach have been suggested. The necessity of removing the posterior arch of C1 to accomplish optimal tumor exposure is still debated. Therefore, we report on our experience and technical details of the fourth ventricular tumor resection in a modified prone position without systematic removal of the posterior arch of C1. Methods: A retrospective analysis of all pediatric patients, who underwent a fourth ventricular tumor resection in the modified prone position between 2012 and 2021, was performed. Results: We identified 40 patients with a median age of 6 years and a M:F ratio of 25:15. A telovelar approach was performed in all cases. In 39/40 patients, the posterior arch of C1 was not removed. In the remaining patient, the reason for removing C1 was tumor extension below the level of C2 with ventral extension. Gross or near total resection could be achieved in 34/39 patients, and subtotal resection in 5/39 patients. In none of the patients, a limited exposure, sight of view, or range of motion caused by the posterior arch of C1 was encountered, necessitating an unplanned removal of the posterior arch of C1. Importantly, in none of the cases, the surgeon had the impression of a limited sight of view to the most rostral parts of the fourth ventricle, which necessitated a vermian incision. Conclusion: A telovelar approach without the removal of the posterior arch of C1 allows for an optimal exposure of the fourth ventricle provided that critical nuances in patient positioning are considered. [ABSTRACT FROM AUTHOR]

Objective: Survivors of pediatric brain tumors (SPBT) are at risk for social deficits, fewer friendships, and poor peer relations. SPBT also experience reduced brain connectivity via microstructural disruptions to white matter from neurological insults. Research with other populations implicates white matter connectivity as a key contributor to poor social functioning. This case-controlled diffusion-weighted imaging study evaluated structural connectivity in SPBT and typically developing controls (TDC) and associations between metrics of connectivity and social functioning. Methods: Diffusion weighted-imaging results from 19 SPBT and 19 TDC were analyzed using probabilistic white matter tractography. Survivors were at least 5 years post-diagnosis and 2 years off treatment. Graph theory statistics measured group differences across several connectivity metrics, including average strength, global efficiency, assortativity, clustering coefficient, modularity, and betweenness centrality. Analyses also evaluated the effects of neurological risk on connectivity among SPBT. Correlational analyses evaluated associations between connectivity and indices of social behavior. Results: SPBT demonstrated reduced global connectivity compared to TDC. Several medical factors (e.g., chemotherapy, recurrence, multimodal therapy) were related to decreased connectivity across metrics of integration (e.g., average strength, global efficiency) in SPBT. Connectivity metrics were related to peer relationship quality and social challenges in the SPBT group and to social challenges in the total sample. Conclusions: Microstructural white matter connectivity is diminished in SPBT and related to neurological risk and peer relationship quality. Additional neuroimaging research is needed to evaluate associations between brain connectivity metrics and social functioning in SPBT. [ABSTRACT FROM AUTHOR]

BACKGROUND: A major obstacle in translating the therapeutic potential of chimeric antigen receptor (CAR) T cells to children with central nervous system (CNS) tumors is the blood–brain barrier. To overcome this limitation, preclinical and clinical studies have supported the use of repeated, locoregional intracranial CAR T-cell delivery. However, there is limited literature available describing the process for the involvement of an investigational drug service (IDS) pharmacy, particularly in the setting of a children’s hospital with outpatient dosing for CNS tumors. OBJECTIVES: To describe Seattle Children’s Hospital’s experience in clinically producing CAR T cells and the implementation of IDS pharmacy practices used to deliver more than 300 intracranial CAR T-cell doses to children, as well as to share how we refined the processing techniques from CAR T-cell generation to the thawing of fractionated doses for intracranial delivery. METHODS: Autologous CD4+ and CD8+ T cells were collected and transduced to express HER2, EGFR, or B7-H3–specific CAR T cells. Cryopreserved CAR T cells were thawed by the IDS pharmacy before intracranial delivery to patients with recurrent/refractory CNS tumors or with diffuse intrinsic pontine glioma/diffuse midline glioma. RESULTS: The use of a thaw-and-dilute procedure for cryopreserved individual CAR T-cell doses provides reliable viability and is more efficient than typical thaw-and-wash protocols. Cell viability with the thaw-and-dilute protocol was approximately 75% and was always within 10% of the viability assessed at cryopreservation. Cell viability was preserved through 6 hours after thawing, which exceeded the 1-hour time frame from thawing to infusion. CONCLUSION: As the field of adoptive immunotherapy grows and continues to bring hope to patients with fatal CNS malignancies, it is critical to focus on improving the preparatory steps for CAR T-cell delivery. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the amide proton transfer (APT), tumor blood flow (TBF), and apparent diffusion coefficient (ADC) combined diagnostic value for differentiating intracranial malignant tumors (MTs) from benign tumors (BTs) in young patients, as defined by the 2021 World Health Organization classification of central nervous system tumors. Methods: Fifteen patients with intracranial MTs and 10 patients with BTs aged 0–30 years underwent MRI with APT, pseudocontinuous arterial spin labeling (pCASL), and diffusion-weighted imaging. All tumors were evaluated through the use of histogram analysis and the Mann–Whitney U test to compare 10 parameters for each sequence between the groups. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Results: The APT maximum, mean, 10th, 25th, 50th, 75th, and 90th percentiles were significantly higher in MTs than in BTs; the TBF minimum (min) was significantly lower in MTs than in BTs; TBF kurtosis was significantly higher in MTs than in BTs; the ADC min, 10th, and 25th percentiles were significantly lower in MTs than in BTs (all p < 0.05). The APT 50th percentile (0.900), TBF min (0.813), and ADC min (0.900) had the highest area under the curve (AUC) values of the parameters in each sequence. The AUC for the combination of these three parameters was 0.933. Conclusions: The combination of APT, TBF, and ADC evaluated through histogram analysis may be useful for differentiating intracranial MTs from BTs in young patients. [ABSTRACT FROM AUTHOR]

The purpose of this prospective pilot study was to evaluate the feasibility and effects of cognitive-motor intervention on the cognitive and motor abilities of pediatric survivors of posterior fossa tumors. The study involved patients aged 7 to 18 years with cognitive deficits who had completed primary treatment for posterior fossa tumors. 25 participants (Mage=11.3 ± 2.93, 64% male; 17 medulloblastoma, 1 ependymoma, 1 desmoplastic medulloblastoma, 6 piloid astrocytoma; 22 in remission (Mmonths =45), 3 in stabilization (Mmonths=49)) were recruited from the Research Institute for Brain Development and Peak Performance. The intervention consisted of two phases with a 3-month break for home training, and a total duration of 6 months. Each phase lasted 7 weeks and included two assessment procedures (pre- and post-intervention) and 10 training sessions over a period of 5 weeks (two 3-hour sessions per week). At baseline and pre- and post-intervention, all participants underwent a battery of cognitive and motor tests. Each training session included gross motor training (GMT), graphomotor training (GT), and cognitive-motor training (CMT). Statistical analysis was performed using the Friedman test for repeated measures and post-hoc Durbin-Conover test. The results indicated significant improvements in visuospatial working memory, visual attention, eye-hand coordination, semantic verbal fluency, auditory-motor synchronization, reaction time, and a decrease in the rate of ataxia. These improvements remained stable even in the absence of direct intervention. The findings demonstrate positive effects and feasibility of the intervention and suggest the need for further research in this area including randomized controlled feasibility studies with a larger sample. [ABSTRACT FROM AUTHOR]

Introduction: Brain tumors are a major source of disease burden in pediatric population, with the most common tumor types being pilocytic astrocytoma, ependymoma and medulloblastoma. In every tumor entity, surgery is the cornerstone of treatment, but the importance of gross-total resection and the corresponding patient prognosis is highly variant. However, real-time identification of pediatric CNS malignancies based on the histology of the frozen sections alone is especially troublesome. We propose a novel method based on differential mobility spectrometry (DMS) analysis for rapid identification of pediatric brain tumors. Methods: We prospectively obtained tumor samples from 15 pediatric patients (5 pilocytic astrocytomas, 5 ependymomas and 5 medulloblastomas). The samples were cut into 36 smaller specimens that were analyzed with the DMS. Results: With linear discriminant analysis algorithm, a classification accuracy (CA) of 70% was reached. Additionally, a 75% CA was achieved in a pooled analysis of medulloblastoma vs. gliomas. Discussion: Our results show that the DMS is able to differentiate most common pediatric brain tumor samples, thus making it a promising additional instrument for real-time brain tumor diagnostics. [ABSTRACT FROM AUTHOR]

BACKGROUND: Brain tumors are the most common solid tumors and the leading cause of cancer-related death among all childhood cancers. Tumor segmentation is essential in surgical and treatment planning, and response assessment and monitoring. However, manual segmentation is time-consuming and has high interoperator variability. We present a multi-institutional deep learning-based method for automated brain extraction and segmentation of pediatric brain tumors based on multi-parametric MRI scans. METHODS: Multi-parametric scans (T1w, T1w-CE, T2, and T2-FLAIR) of 244 pediatric patients ( n = 215 internal and n = 29 external cohorts) with de novo brain tumors, including a variety of tumor subtypes, were preprocessed and manually segmented to identify the brain tissue and tumor subregions into four tumor subregions, i.e., enhancing tumor (ET), non-enhancing tumor (NET), cystic components (CC), and peritumoral edema (ED). The internal cohort was split into training ( n = 151), validation ( n = 43), and withheld internal test ( n = 21) subsets. DeepMedic, a three-dimensional convolutional neural network, was trained and the model parameters were tuned. Finally, the network was evaluated on the withheld internal and external test cohorts. RESULTS: Dice similarity score (median ± SD) was 0.91 ± 0.10/0.88 ± 0.16 for the whole tumor, 0.73 ± 0.27/0.84 ± 0.29 for ET, 0.79 ± 19/0.74 ± 0.27 for union of all non-enhancing components (i.e., NET, CC, ED), and 0.98 ± 0.02 for brain tissue in both internal/external test sets. CONCLUSIONS: Our proposed automated brain extraction and tumor subregion segmentation models demonstrated accurate performance on segmentation of the brain tissue and whole tumor regions in pediatric brain tumors and can facilitate detection of abnormal regions for further clinical measurements.

Simple Summary: Reliable preoperative differentiation of pediatric brain tumors can be challenging. While deep learning models have made significant progress in radiology, their use in pediatric populations is limited, typically through limited data availability. In this proof-of-concept study, we investigated the potential of a deep learning classifier trained on a multicenter data set of 195 children to learn to differentiate between pilocytic astrocytoma and medulloblastoma, the two most common infratentorial pediatric brain tumors, which in general present with overlapping imaging features. Our model is validated against the assessment of five independent readers of varying expertise. The final models performed strongly (AUC 0.986) on the unseen test set, correctly predicting the tumor diagnosis in 62 of 64 patients (97%). Compared to human readers, the classifier performed significantly better than relatively inexperienced readers and was on par with pediatric neuroradiologists with specific expertise in pediatric neuro-oncology. Our work highlights the potential of deep learning even in this challenging population and warrants future studies, including different tumor types and diverse acquisition protocols. Medulloblastoma and pilocytic astrocytoma are the two most common pediatric brain tumors with overlapping imaging features. In this proof-of-concept study, we investigated using a deep learning classifier trained on a multicenter data set to differentiate these tumor types. We developed a patch-based 3D-DenseNet classifier, utilizing automated tumor segmentation. Given the heterogeneity of imaging data (and available sequences), we used all individually available preoperative imaging sequences to make the model robust to varying input. We compared the classifier to diagnostic assessments by five readers with varying experience in pediatric brain tumors. Overall, we included 195 preoperative MRIs from children with medulloblastoma (n = 69) or pilocytic astrocytoma (n = 126) across six university hospitals. In the 64-patient test set, the DenseNet classifier achieved a high AUC of 0.986, correctly predicting 62/64 (97%) diagnoses. It misclassified one case of each tumor type. Human reader accuracy ranged from 100% (expert neuroradiologist) to 80% (resident). The classifier performed significantly better than relatively inexperienced readers (p < 0.05) and was on par with pediatric neuro-oncology experts. Our proof-of-concept study demonstrates a deep learning model based on automated tumor segmentation that can reliably preoperatively differentiate between medulloblastoma and pilocytic astrocytoma, even in heterogeneous data. [ABSTRACT FROM AUTHOR]

Background: Intracranial teratoma represents a rare neoplasm, occurring predominantly during childhood. Characteristic symptoms depend on the location but are mainly hydrocephalus, visual disturbances, hypopituitarism, and diabetes insipidus. Initial diagnosis can be challenging due to similar radiological features in both teratomas and other lesions such as craniopharyngiomas. Gross total resection is recommended if feasible and associated with a good prognosis. Case description: A 10-year-old girl presented with newly diagnosed growth retardation, fatigue, cephalgia and bilateral hemianopia. Further laboratory analysis confirmed central hypothyroidism and hypercortisolism. Cranial magnetic resonance imaging showed a cystic space-occupying lesion in the sellar and suprasellar compartment with compression of the optic chiasm without hydrocephalus present, suspicious of craniopharyngioma. Subsequently, an endonasal endoscopic transsphenoidal near-total tumor resection with decompression of the optic chiasm was performed. During postoperative recovery the patient developed transient diabetes insipidus, the bilateral hemianopia remained unchanged. The patient could be discharged in a stable condition, while hormone replacement for multiple pituitary hormone deficiency was required. Surprisingly, histopathology revealed conspicuous areas of skin with formation of hairs and squamous epithelia, compatible with a mature teratoma. Conclusions: We present an extremely rare case of pediatric sellar teratoma originating from the pituitary gland and a review of literature focusing on the variation in presentation and treatment. Sellar teratomas are often mistaken for craniopharyngioma due to their similar radiographic appearances. However, the primary goal of treatment for both pathologies is to decompress eloquent surrounding structures such as the optic tract, and if applicable, resolution of hydrocephalus while avoiding damage to the pituitary stalk and especially the hypothalamic structures. If feasible, the aim of surgery should be gross total resection. [ABSTRACT FROM AUTHOR]

Background While exercise training (ET) programs show positive outcomes in cognition, motor function, and physical fitness in pediatric brain tumor (PBT) survivors, little is known about the optimal timing of intervention. The aim of this work was to explore the feasibility and benefits of ET based on its timing after radiotherapy. Methods This retrospective analysis (ClinicalTrials.gov , NCT01944761) analyzed data based on the timing of PBT survivors' participation in an ET program relative to their completion of radiotherapy: <2 years (n  = 9), 2–5 years (n  = 10), and > 5 years (n  = 13). We used repeated measures analysis of variance to compare feasibility and efficacy indicators among groups, as well as correlation analysis between ET program timing postradiotherapy and preliminary treatment effects on cognition, motor function and physical fitness outcomes. Results Two to five years postradiotherapy was the optimal time period in terms of adherence (88.5%), retention (100%), and satisfaction (more fun, more enjoyable and recommend it more to other children). However, the benefits of ET program on memory recognition (r  = −0.379, P  = .047) and accuracy (r  = −0.430, P  = .032) decreased with increased time postradiotherapy. Motor function improved in all groups, with greater improvements in bilateral coordination (P  = .043) earlier postradiotherapy, and in running (P  = .043) later postradiotherapy. The greatest improvement in pro-rated work rate occurred in the < 2-year group (P  = .008). Conclusion Participation in an ET program should be offered as part of routine postradiotherapy care in the first 1–2 years and strongly encouraged in the first 5 years. [ABSTRACT FROM AUTHOR]

Objective: The challenge of pediatric brain tumor surgery is given due to a relative low prevalence but high heterogeneity in age, localization, and pathology. Improvements of long-term overall survival rates were achieved during the past decades stressing the importance of a multidisciplinary decision process guided by a national treatment protocol. We reviewed the entire spectrum of pediatric brain tumor surgeries from the perspective of an interdisciplinary pediatric neuro-oncology center in Germany. Methods: Every patient who underwent brain tumor surgery from January 2010 to June 2017 in our Pediatric Neurosurgery department was retrospectively included and evaluated regarding the course of treatment. Perioperative data such as tumor localization, timing of surgery, extent of resection, neuropathological diagnosis, transfusion rates, oncologic and radiation therapy, and neurological follow-up including morbidity and mortality were evaluated. Results: Two hundred ninety-three pediatric brain tumor patients were applicable (age: 8.28 ± 5.62 years, 1.22:1.0 m:f). A total of 531 tumor surgical interventions was performed within these patients (457 tumor resections, 74 tumor biopsies; mean interventions per patient 1.8 ± 1.2). Due to a critical neurologic status, 32 operations (6%) were performed on the day of admission. In 65.2% of all cases, tumor were approached supratentorially. Most frequent diagnoses of the cases were glial tumors (47.8%) and embryonal tumors (17.6%). Preoperative planned extent of resection was achieved in 92.7%. Pre- and postoperative neurologic deficits resolved completely in 30.7%, whereas symptom regressed in 28.6% of surgical interventions. New postoperative neurologic deficit was observed in 10.7%, which resolved or improved in 80% of these cases during 30 days. The mortality rate was 1%. Conclusion: We outlined the center perspective of a specialized pediatric neuro-oncological center describing the heterogeneous distribution of cases regarding age-related prevalence, tumor localization, and biology, which requires a high multidisciplinary expertise. The study contributes to define challenges in treating pediatric brain tumors and to develop quality indicators for pediatric neuro-oncological surgery. We assume that an adequate volume load of patients within a interdisciplinary infrastructure is warranted to aim for effective treatment and decent quality of life for the majority of long-term surviving pediatric tumor patients. [ABSTRACT FROM AUTHOR]

Survivors of Pediatric Brain Tumors (PBTs) treated with cranial radiation therapy (CRT) often experience a decline in neurocognitive test scores. Less is known about the neurocognitive development of non-irradiated survivors of PBTs. The aim of this study was to statistically model neurocognitive development after PBT in both irradiated and non-irradiated survivors and to find clinical variables associated with the rate of decline in neurocognitive scores. A total of 151 survivors were included in the study. Inclusion criteria: Diagnosis of PBT between 2001 and 2013 or earlier diagnosis of PBT and turning 18 years of age between 2006 and 2013. Exclusion criteria: Death within a year from diagnosis, neurocutaneous syndromes, severe intellectual disability. Clinical neurocognitive data were collected retrospectively from medical records. Multilevel linear modeling was used to evaluate the rate of decline in neurocognitive measures and factors associated with the same. A decline was found in most measures for both irradiated and non-irradiated survivors. Ventriculo-peritoneal (VP) shunting and treatment with whole-brain radiation therapy (WBRT) were associated with a faster decline in neurocognitive scores. Male sex and supratentorial lateral tumor were associated with lower scores. Verbal learning measures were either stable or improving. Survivors of PBTs show a pattern of decline in neurocognitive scores irrespective of treatment received, which suggests the need for routine screening for neurocognitive rehabilitation. However, survivors treated with WBRT and/or a VP shunt declined at a faster rate and appear to be at the highest risk of negative neurocognitive outcomes and to have the greatest need for neurocognitive rehabilitation. [ABSTRACT FROM AUTHOR]

BackgroundPleomorphic xanthoastrocytoma (PXA) is a rare brain tumor that accounts for

PurposeTo highlight the clinical, neuroradiographic, neuropathologic, and molecular features of histologically identified neurocytoma in a pediatric cohort and highlight the evolving use methylation profiling in providing diagnostic clarity in difficult to diagnosis pediatric brain tumors.MethodsFive consecutive children (ages 9-13, 2 girls 3 boys) were histologically diagnosed with neurocytoma at Rady Children's Hospital San Diego from 2012 to 2018. Clinical and molecular features were analyzed with regards to treatment course and outcome.ResultsPresenting symptoms included seizures (n = 2), syncope (n = 1), headache (n = 2), visual disturbances (n = 2) and emesis (n = 2). Tumor location included intraventricular (n = 2), intraventricular with parenchymal spread (n = 1), and extraventricular (n = 2). Magnetic resonance imaging demonstrated reduced diffusivity (2/5), signal abnormality on susceptibility-weighted sequences (3/5), and varying degrees of contrast enhancement (4/5). All patients underwent surgical resection alone. Recurrence occurred in four children that were treated with surgery (4/4), adjuvant radiation (2/4), and chemoradiation (1/4). Neuropathologic features included positivity for GFAP (4/5), synaptophysin (4/5), NSE (2/2), NeuN (4/4), and variable Ki-67 (

Abstract Background Pediatric brain tumors (PBT) stand as the leading cause of cancer‐related deaths in children. Chemoradiation protocols have improved survival rates, even for non‐resectable tumors. Nonetheless, radiation therapy carries the risk of numerous adverse effects that can have long‐lasting, detrimental effects on the quality of life for survivors. The pursuit of chemotherapeutics that could obviate the need for radiotherapy remains ongoing. Several anti‐tumor agents, including sunitinib, valproic acid, carboplatin, and panobinostat, have shown effectiveness in various malignancies but have not proven effective in treating PBT. The presence of the blood–brain barrier (BBB) plays a pivotal role in maintaining suboptimal concentrations of anti‐cancer drugs in the central nervous system (CNS). Ongoing research aims to modulate the integrity of the BBB to attain clinically effective drug concentrations in the CNS. However, current findings on the interaction of exogenous chemical agents with the BBB remain limited and do not provide a comprehensive explanation for the ineffectiveness of established anti‐cancer drugs in PBT. Methods We conducted our search for chemotherapeutic agents associated with the blood–brain barrier (BBB) using the following keywords: Chemotherapy in Cancer, Chemotherapy in Brain Cancer, Chemotherapy in PBT, BBB Inhibition of Drugs into CNS, Suboptimal Concentration of CNS Drugs, PBT Drugs and BBB, and Potential PBT Drugs. We reviewed each relevant article before compiling the information in our manuscript. For the generation of figures, we utilized BioRender software. Focus We focused our article search on chemical agents for PBT and subsequently investigated the role of the BBB in this context. Our search criteria included clinical trials, both randomized and non‐randomized studies, preclinical research, review articles, and research papers. Finding Our research suggests that, despite the availability of potent chemotherapeutic agents for several types of cancer, the effectiveness of these chemical agents in treating PBT has not been comprehensively explored. Additionally, there is a scarcity of studies examining the role of the BBB in the suboptimal outcomes of PBT treatment, despite the effectiveness of these drugs for other types of tumors.

Over the past year, there has been a significant rise in interest in the application of open-source artificial intelligence models (OSAIM) in the field of medicine. An increasing number of studies focus on evaluating the capabilities of these models in image analysis, including magnetic resonance imaging (MRI). This study aimed to investigate whether two of the most popular open-source AI models, namely ChatGPT 4o and Gemini Pro, can analyze MRI video sequences with single-phase contrast in sagittal and frontal projections, depicting a posterior fossa tumor corresponding to a medulloblastoma in a child. The study utilized video files from single-phase contrast-enhanced head MRI in two planes (frontal and sagittal) of a child diagnosed with a posterior fossa tumor, type medulloblastoma, confirmed by histopathological examination. Each model was separately provided with the video file, first in the sagittal plane, analyzing three different sets of commands from the most general to the most specific. The same procedure was applied to the video file in the frontal plane. The Gemini Pro model did not conduct a detailed analysis of the pathological change but correctly identified the content of the video file, indicating it was a brain MRI, and suggested that a specialist in the field should perform the evaluation. Conversely, ChatGPT 4o conducted image analysis but failed to recognize that the content was MRI. The attempts to detect the lesion were random and varied depending on the plane. These models could not accurately identify the video content or indicate the area of the neoplastic change, even after applying detailed queries. The results suggest that despite their widespread use in various fields, these models require further improvements and specialized training to effectively support medical diagnostics.

Objective: It has been theorized that pediatric brain tumor survivors may have reduced insight into their executive functioning. Agreement between informants and survivors has been used to probe this theory, but findings have been inconsistent. This study sought to expand on prior work by examining the relationship between participant role and ratings on the Frontal Systems Behavior Scale (FrSBe) among 73 adult survivors and their informants. This study also sought to test whether agreement on scores varied as a function of tumor treatment. Method: Dyadic mixed effects models examined the relationship between participant ratings on FrSBe subscales and the role of a participant (survivor or informant). Intraclass correlations (ICC) were used to calculate reliable change indices to evaluate significant divergence in self and informant agreement. Results: Dyadic mixed effects models showed an insignificant relationship between participant role and ratings on the FrSBe apathy and executive dysfunction subscales. Participant role was related to ratings on the disinhibition subscale of the FrSBe. The ICC for apathy was ICC =.583, for disinhibition ICC =.420, and for executive dysfunction ICC =.373. Significant divergence in scores did not vary by history of chemoradiation. Conclusions: Results demonstrate an effect of role on one FrSBe subscale and weak to moderate agreement between survivor and informant scores, which suggests that agreement between informants and survivors varies by FrSBe domain. The strongest relationship between survivors and informants was seen on apathy, which suggests that apathy is a shared concern for survivors and their families. [ABSTRACT FROM AUTHOR]

Background Although the relationship between radiation and neurocognition has been extensively studied in the pediatric brain tumor population, it is increasingly recognized that neurocognitive impairment is multifactorial. Therefore, we quantified the effect of socioeconomic status (SES) and chemotherapy on neurocognitive impairment and decline post-treatment. Methods Eligible patients included those diagnosed with a brain tumor at < 22 years of age with ≥1 neurocognitive assessment. Neurocognitive impairment was defined as performance 1.5 standard deviations below the normative mean using age-standardized measures of intellectual function. Neurocognitive decline was defined as a negative slope. Neurocognitive outcomes included Wechsler indices of Full-Scale Intelligence Quotient (IQ). Logistic regression identified variables associated with neurocognitive impairment. Longitudinal data was analyzed using linear mixed models. Results Eligible patients (n  = 152, median age at diagnosis = 9.6 years) had a mean neurocognitive follow-up of 50.2 months. After accounting for age and receipt of craniospinal irradiation, patients with public insurance had 8-fold increased odds of impaired IQ compared to private insurance (odds ratio [OR]: 7.59, P  < .001). After accounting for age, change in IQ was associated with chemotherapy use (slope: −0.45 points/year with chemotherapy vs. 0.71 points/year without chemotherapy, P  = .012). Conclusions Public insurance, an indicator of low SES, was associated with post-treatment impairment in IQ, highlighting the need to incorporate SES measures into prospective studies. Chemotherapy was associated with change in IQ. Further work is needed to determine whether impairment associated with low SES is secondary to baseline differences in IQ prior to brain tumor diagnosis, brain tumor/therapy itself, or some combination thereof. [ABSTRACT FROM AUTHOR]

Background: Pediatric brain tumors (PBT) stand as the leading cause of cancer‐related deaths in children. Chemoradiation protocols have improved survival rates, even for non‐resectable tumors. Nonetheless, radiation therapy carries the risk of numerous adverse effects that can have long‐lasting, detrimental effects on the quality of life for survivors. The pursuit of chemotherapeutics that could obviate the need for radiotherapy remains ongoing. Several anti‐tumor agents, including sunitinib, valproic acid, carboplatin, and panobinostat, have shown effectiveness in various malignancies but have not proven effective in treating PBT. The presence of the blood–brain barrier (BBB) plays a pivotal role in maintaining suboptimal concentrations of anti‐cancer drugs in the central nervous system (CNS). Ongoing research aims to modulate the integrity of the BBB to attain clinically effective drug concentrations in the CNS. However, current findings on the interaction of exogenous chemical agents with the BBB remain limited and do not provide a comprehensive explanation for the ineffectiveness of established anti‐cancer drugs in PBT. Methods: We conducted our search for chemotherapeutic agents associated with the blood–brain barrier (BBB) using the following keywords: Chemotherapy in Cancer, Chemotherapy in Brain Cancer, Chemotherapy in PBT, BBB Inhibition of Drugs into CNS, Suboptimal Concentration of CNS Drugs, PBT Drugs and BBB, and Potential PBT Drugs. We reviewed each relevant article before compiling the information in our manuscript. For the generation of figures, we utilized BioRender software. Focus: We focused our article search on chemical agents for PBT and subsequently investigated the role of the BBB in this context. Our search criteria included clinical trials, both randomized and non‐randomized studies, preclinical research, review articles, and research papers. Finding: Our research suggests that, despite the availability of potent chemotherapeutic agents for several types of cancer, the effectiveness of these chemical agents in treating PBT has not been comprehensively explored. Additionally, there is a scarcity of studies examining the role of the BBB in the suboptimal outcomes of PBT treatment, despite the effectiveness of these drugs for other types of tumors. [ABSTRACT FROM AUTHOR]

Survivors of pediatric brain tumors experience significant cognitive deficits from their diagnosis and treatment. The exact mechanisms of cognitive injury are poorly understood, and validated predictors of long-term cognitive outcome are lacking. Resting state functional magnetic resonance imaging allows for the study of the spontaneous fluctuations in bulk neural activity, providing insight into brain organization and function. Here, we evaluated cognitive performance and functional network architecture in pediatric brain tumor patients. Forty-nine patients (7–18 years old) with a primary brain tumor diagnosis underwent resting state imaging during regularly scheduled clinical visits. All patients were tested with a battery of cognitive assessments. Extant data from 139 typically developing children were used as controls. We found that obtaining high-quality imaging data during routine clinical scanning was feasible. Functional network organization was significantly altered in patients, with the largest disruptions observed in patients who received propofol sedation. Awake patients demonstrated significant decreases in association network segregation compared to controls. Interestingly, there was no difference in the segregation of sensorimotor networks. With a median follow-up of 3.1 years, patients demonstrated cognitive deficits in multiple domains of executive function. Finally, there was a weak correlation between decreased default mode network segregation and poor picture vocabulary score. Future work with longer follow-up, longitudinal analyses, and a larger cohort will provide further insight into this potential predictor. [ABSTRACT FROM AUTHOR]

The increasing number of long-term survivors of pediatric brain tumors requires us to incorporate the most recent knowledge derived from cognitive neuroscience into their oncological treatment. As the lesion itself, as well as each treatment, can cause specific neural damage, the long-term neurocognitive outcomes are highly complex and challenging to assess. The number of neurocognitive studies in this population grows exponentially worldwide, motivating modern neuroscience to provide guidance in follow-up before, during and after treatment. In this review, we provide an overview of structural and functional brain connectomes and their role in the neuropsychological outcomes of specific brain tumor types. Based on this information, we propose a theoretical neuroscientific framework to apply appropriate neuropsychological and imaging follow-up for future clinical care and rehabilitation trials. [ABSTRACT FROM AUTHOR]

Background: Children with brain tumors are at high risk of neurocognitive decline after radiotherapy (RT). However, there is a lack of studies on how RT doses to organs at risk (OARs) impacts neurocognition. The aim of this study was to examine dose-risk relationships for mean RT dose to different brain structures important for neurocognitive networks. We explored previously established OARs and potentially new OARs. Methods: A sample of 44 pediatric brain tumor survivors who had received proton and/or photon RT were included. Correlations between mean RT doses to OARs and IQ were analyzed. Previously established OARs were cochleae, optic chiasm, optic nerve, pituitary gland, hypothalamus, hippocampus and pons. Potential new OARs for RT-induced neurocognitive decline were cerebellum, vermis and thalamus. Results: Mean RT dose to different OARs correlated with several IQ subtests. Higher mean RT dose to cochleae, optic nerve, cerebellum, vermis and pons was correlated with lower performance on particularly full-scale IQ (FIQ), Perceptual Reasoning (PRI), Working Memory (WMI) and Processing Speed Index (PSI). Higher mean RT dose to hippocampus correlated with lower performance on processing speed and working memory. For those receiving whole brain RT (WBRT), higher mean RT dose to the pituitary gland correlated with lower performance on working memory. Conclusion: A high dose-risk correlation was found between IQ subtests and mean RT dose in established and potential new OARs. Thus, in the lack of validated dose constraints for vulnerable brain structures, a parsimonious approach in RT planning should be considered to preserve neurocognitive networks. [ABSTRACT FROM AUTHOR]

IntroductionBrain tumors are a major source of disease burden in pediatric population, with the most common tumor types being pilocytic astrocytoma, ependymoma and medulloblastoma. In every tumor entity, surgery is the cornerstone of treatment, but the importance of gross-total resection and the corresponding patient prognosis is highly variant. However, real-time identification of pediatric CNS malignancies based on the histology of the frozen sections alone is especially troublesome. We propose a novel method based on differential mobility spectrometry (DMS) analysis for rapid identification of pediatric brain tumors.MethodsWe prospectively obtained tumor samples from 15 pediatric patients (5 pilocytic astrocytomas, 5 ependymomas and 5 medulloblastomas). The samples were cut into 36 smaller specimens that were analyzed with the DMS.ResultsWith linear discriminant analysis algorithm, a classification accuracy (CA) of 70% was reached. Additionally, a 75% CA was achieved in a pooled analysis of medulloblastoma vs. gliomas.DiscussionOur results show that the DMS is able to differentiate most common pediatric brain tumor samples, thus making it a promising additional instrument for real-time brain tumor diagnostics.

Abstract Diffuse gliomas are a heterogeneous category of primary central nervous system tumors. Due to their infiltrative growth precluding complete surgical resection, most diffuse high-grade gliomas are treated with adjuvant chemotherapy and radiation. Recurrent/progressive diffuse gliomas may show genetic differences when compared to the primary tumors, giving insight into their molecular evolution and mechanisms of treatment resistance. In adult-type diffuse gliomas with or without isocitrate dehydrogenase gene mutations, tumor recurrence/progression can be associated with mutations in genes encoding DNA mismatch repair proteins, leading to a dramatic increase in tumor mutation burden. This phenomenon is closely linked to treatment with the DNA alkylating agent temozolomide, a mainstay of adult diffuse glioma chemotherapeutic management. Post-treatment mismatch repair deficiency and acquired high tumor mutation burden is relatively unexplored in pediatric patients who have recurrent high-grade gliomas. Here, we report a molecular and histological analysis of an institutional cohort of eleven pediatric patients with paired initial and recurrent high-grade astrocytoma samples with intervening temozolomide treatment. We identified three cases with evidence for increased tumor mutation burden at recurrence, including two cases of diffuse hemispheric glioma H3 G34-mutant (one previously reported). We also show that molecular analysis by next-generation DNA sequencing and DNA methylation-based profiling enabled an integrated diagnosis per 2021 World Health Organization criteria in 10 of 11 cases (91%). Our findings indicate that increased tumor mutation burden at post-treatment recurrence is relevant in pediatric-type diffuse high-grade gliomas. Diffuse hemispheric glioma H3 G34-mutant may be particularly susceptible to this phenomenon.

Diffuse midline glioma (DMG) is a childhood brain tumor with an extremely poor prognosis. Chimeric antigen receptor (CAR) T cell therapy has recently demonstrated some success in DMG, but there may a need to target multiple tumor-specific targets to avoid antigen escape. We developed a second-generation CAR targeting an HLA-A∗02:01 restricted histone 3K27M epitope in DMG, the target of previous peptide vaccination and T cell receptor-mimics. These CAR T cells demonstrated specific, titratable, binding to cells pulsed with the H3.3K27M peptide. However, we were unable to observe scFv binding, CAR T cell activation, or cytotoxic function against H3.3K27M+ patient-derived models. Despite using sensitive immunopeptidomics, we could not detect the H3.3K27M26–35-HLA-A∗02:01 peptide on these patient-derived models. Interestingly, other non-mutated peptides from DMG were detected bound to HLA-A∗02:01 and other class I molecules, including a novel HLA-A3-restricted peptide encompassing the K27M mutation and overlapping with the H3 K27M26–35-HLA-A∗02:01 peptide. These results suggest that targeting the H3 K27M26–35 mutation in context of HLA-A∗02:01 may not be a feasible immunotherapy strategy because of its lack of presentation. These findings should inform future investigations and clinical trials in DMG.

Abstract Background Children with brain tumors are at high risk of neurocognitive decline after radiotherapy (RT). However, there is a lack of studies on how RT doses to organs at risk (OARs) impacts neurocognition. The aim of this study was to examine dose-risk relationships for mean RT dose to different brain structures important for neurocognitive networks. We explored previously established OARs and potentially new OARs. Methods A sample of 44 pediatric brain tumor survivors who had received proton and/or photon RT were included. Correlations between mean RT doses to OARs and IQ were analyzed. Previously established OARs were cochleae, optic chiasm, optic nerve, pituitary gland, hypothalamus, hippocampus and pons. Potential new OARs for RT-induced neurocognitive decline were cerebellum, vermis and thalamus. Results Mean RT dose to different OARs correlated with several IQ subtests. Higher mean RT dose to cochleae, optic nerve, cerebellum, vermis and pons was correlated with lower performance on particularly full-scale IQ (FIQ), Perceptual Reasoning (PRI), Working Memory (WMI) and Processing Speed Index (PSI). Higher mean RT dose to hippocampus correlated with lower performance on processing speed and working memory. For those receiving whole brain RT (WBRT), higher mean RT dose to the pituitary gland correlated with lower performance on working memory. Conclusion A high dose-risk correlation was found between IQ subtests and mean RT dose in established and potential new OARs. Thus, in the lack of validated dose constraints for vulnerable brain structures, a parsimonious approach in RT planning should be considered to preserve neurocognitive networks.

PURPOSE: To evaluate for predictive neuroimaging features of pediatric brain tumor development and quantify tumor growth characteristics in patients who had neuroimaging performed prior to a diagnosis of a brain tumor. METHODS: Retrospective review of 1098 consecutive pediatric patients at a single institution with newly diagnosed brain tumors from January 2009 to October 2021 was performed to identify patients with neuroimaging prior to the diagnosis of a brain tumor. Pre-diagnostic and diagnostic neuroimaging features (e.g., tumor size, apparent diffusion coefficient (ADC) values), clinical presentations, and neuropathology were recorded in those patients who had neuroimaging performed prior to a brain tumor diagnosis. High- and low-grade tumor sizes were fit to linear and exponential growth regression models. RESULTS: Fourteen of 1098 patients (1%) had neuroimaging prior to diagnosis of a brain tumor (8 females, mean age at definitive diagnosis 8.1 years, imaging interval 0.2-8.7 years). Tumor types included low-grade glioma (n = 4), embryonal tumors (n = 2), pineal tumors (n=2), ependymoma (n = 3), and others (n = 3). Pre-diagnostic imaging of corresponding tumor growth sites were abnormal in four cases (28%) and demonstrated higher ADC values in the region of high-grade tumor growth (p = 0.05). Growth regression analyses demonstrated R2-values of 0.92 and 0.91 using a linear model and 0.64 and 0.89 using an exponential model for high- and low-grade tumors, respectively; estimated minimum velocity of diameter expansion was 2.4 cm/year for high-grade and 0.4 cm/year for low-grade tumors. High-grade tumors demonstrated faster growth rate of diameter and solid tumor volume compared to low-grade tumors (p = 0.02, p = 0.03, respectively). CONCLUSIONS: This is the first study to test feasibility in utilizing pre-diagnostic neuroimaging to demonstrate that linear and exponential growth rate models can be used to estimate pediatric brain tumor growth velocity and should be validated in a larger multi-institutional cohort.

PurposeDiffuse intrinsic pontine gliomas (DIPG) are highly aggressive tumors with no currently available curative therapy. This study evaluated whether measurements of in vivo cell metabolites using magnetic resonance spectroscopy (MRS) may serve as biomarkers of response to therapy, including progression.MethodsSingle-voxel MR spectra were serially acquired in two cohorts of patients with DIPG treated with radiation therapy (RT) with or without concurrent chemotherapy and prior to progression: 14 participants were enrolled in a clinical trial of adjuvant glioma-associated antigen peptide vaccines and 32 patients were enrolled who did not receive adjuvant vaccine therapy. Spearman correlations measured overall survival associations with absolute metabolite concentrations of myo-inositol (mI), creatine (Cr), and n-acetyl-aspartate (NAA) and their ratios relative to choline (Cho) during three specified time periods following completion of RT. Linear mixed-effects regression models evaluated the longitudinal associations between metabolite ratios and time from death (terminal decline).ResultsOverall survival was not associated with metabolite ratios obtained shortly after RT (1.9-3.8 months post-diagnosis) in either cohort. In the vaccine cohort, an elevated mI/Cho ratio after 2-3 doses (3.9-5.2 months post-diagnosis) was associated with longer survival (rho = 0.92, 95% CI 0.67-0.98). Scans performed up to 6 months before death showed a terminal decline in the mI/Cho ratio, with an average of 0.37 ratio/month in vaccine patients (95% CI 0.11-0.63) and 0.26 (0.04-0.48) in the non-vaccine cohort.ConclusionHigher mI/Cho ratios following RT, consistent with less proliferate tumors and decreased cell turnover, were associated with longer survival, suggesting that this ratio can serve as a biomarker of prognosis following RT. This finding was seen in both cohorts, although the association with OS was detected earlier in the vaccine cohort. Increased mI/Cho (possibly reflecting immune-effector cell influx into the tumor as a mechanism of tumor response) requires further study.

Purpose: To evaluate the amide proton transfer (APT), tumor blood flow (TBF), and apparent diffusion coefficient (ADC) combined diagnostic value for differentiating intracranial malignant tumors (MTs) from benign tumors (BTs) in young patients, as defined by the 2021 World Health Organization classification of central nervous system tumors. Methods: Fifteen patients with intracranial MTs and 10 patients with BTs aged 0–30 years underwent MRI with APT, pseudocontinuous arterial spin labeling (pCASL), and diffusion-weighted imaging. All tumors were evaluated through the use of histogram analysis and the Mann–Whitney U test to compare 10 parameters for each sequence between the groups. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Results: The APT maximum, mean, 10th, 25th, 50th, 75th, and 90th percentiles were significantly higher in MTs than in BTs; the TBF minimum (min) was significantly lower in MTs than in BTs; TBF kurtosis was significantly higher in MTs than in BTs; the ADC min, 10th, and 25th percentiles were significantly lower in MTs than in BTs (all p < 0.05). The APT 50th percentile (0.900), TBF min (0.813), and ADC min (0.900) had the highest area under the curve (AUC) values of the parameters in each sequence. The AUC for the combination of these three parameters was 0.933. Conclusions: The combination of APT, TBF, and ADC evaluated through histogram analysis may be useful for differentiating intracranial MTs from BTs in young patients.