Imaging of pediatric glioneuronal and neuronal tumors.

Glioneuronal tumors (GNTs) are an expanding group of primary CNS neoplasms, commonly affecting children, adolescents and young adults. Most GNTs are relatively indolent, low-grade, WHO grade I lesions. In the pediatric age group, GNTs have their epicenter in the cerebral cortex and present with seizures. Alterations in the mitogen-activated protein kinase (MAPK) pathway, which regulates cell growth, are implicated in tumorigenesis. Imaging not only plays a key role in the characterization and pre-surgical evaluation of GNTs but is also crucial role in follow-up, especially with the increasing use of targeted inhibitors and immunotherapies. In this chapter, we review the clinical and imaging perspectives of common pediatric GNTs.

Multimodal imaging with magnetization transfer and diffusion tensor imaging reveals evidence of myelin damage in children and youth treated for a brain tumor.

Background: The microstructural damage underlying compromise of white matter following treatment for pediatric brain tumors is unclear. We use multimodal imaging employing advanced diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI) MRI methods to examine chronic microstructural damage to white matter in children and adolescents treated for pediatric brain tumor. Notably, MTI may be more sensitive to macromolecular content, including myelin, than DTI. Methods: Fifty patients treated for brain tumors (18 treated with surgery ± chemotherapy and 32 treated with surgery followed by cranial-spinal radiation; time from diagnosis to scan ~6 years) and 45 matched healthy children completed both MTI and DTI scans. Voxelwise and region-of-interest approaches were employed to compare white matter microstructure metrics (magnetization transfer ratio (MTR); DTI- fractional anisotropy [FA], radial diffusivity [RD], axial diffusivity [AD], mean diffusivity [MD]) between patients and healthy controls. Results: MTR was decreased across multiple white matter tracts in patients when compared to healthy children, P < .001. These differences were observed for both patients treated with radiation and those treated with only surgery, P < .001. We also found that children and adolescents treated for brain tumors exhibit decreased FA and increased RD/AD/MD compared to their healthy counterparts in several white matter regions, Ps < .02. Finally, we observed that MTR and DTI metrics were related to multiple white matter tracts in patients, Ps < .01, but not healthy control children. Conclusions: Our findings provide evidence that the white matter damage observed in patients years after treatment of pediatric posterior fossa tumors, likely reflects myelin disruption.

Brain Tumor Imaging in Adolescents and Young Adults: 2021 WHO Updates for Molecular-based Tumor Types.

Published in 2021, the fifth edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) introduced new molecular criteria for tumor types that commonly occur in either pediatric or adult age groups. Adolescents and young adults (AYAs) are at the intersection of adult and pediatric care, and both pediatric-type and adult-type CNS tumors occur at that age. Mortality rates for AYAs with CNS tumors have increased by 0.6% per year for males and 1% per year for females from 2007 to 2016. To best serve patients, it is crucial that both pediatric and adult radiologists who interpret neuroimages are familiar with the various pediatric- and adult-type brain tumors and their typical imaging morphologic characteristics. Gliomas account for approximately 80% of all malignant CNS tumors in the AYA age group, with the most common types observed being diffuse astrocytic and glioneuronal tumors. Ependymomas and medulloblastomas also occur in the AYA population but are seen less frequently. Importantly, biologic behavior and progression of distinct molecular subgroups of brain tumors differ across ages. This review discusses newly added or revised gliomas in the fifth edition of the CNS WHO classification, as well as other CNS tumor types common in the AYA population.

Network connectivity underlying episodic memory in children: Application of a pediatric brain tumor survivor injury model.

Episodic memory involves personal experiences paired with their context. The Medial Temporal, Posterior Medial, Anterior Temporal, and Medial Prefrontal networks have been found to support the hippocampus in episodic memory in adults. However, there lacks a model that captures how the structural and functional connections of these networks interact to support episodic memory processing in children. Using diffusion-weighted imaging, magnetoencephalography, and memory tests, we quantified differences in white matter microstructure, neural communication, and episodic memory performance, respectively, of healthy children (n = 23) and children with reduced memory performance. Pediatric brain tumor survivors (PBTS; n = 24) were used as a model, as they exhibit reduced episodic memory and perturbations in white matter and neural communication. We observed that PBTS, compared to healthy controls, showed significantly (p < 0.05) (1) disrupted white matter microstructure between these episodic memory networks through lower fractional anisotropy and higher mean and axial diffusivity, (2) perturbed theta band (4-7 Hz) oscillatory synchronization in these same networks through higher weighted phase lag indices (wPLI), and (3) lower episodic memory performance in the Transverse Patterning and Children's Memory Scale (CMS) tasks. Using partial-least squares path modeling, we found that brain tumor treatment predicted network white matter damage, which predicted inter-network theta hypersynchrony and lower verbal learning (directly) and lower verbal recall (indirectly via theta hypersynchrony). Novel to the literature, our findings suggest that white matter modulates episodic memory through effect on oscillatory synchronization within relevant brain networks. RESEARCH HIGHLIGHTS: Investigates the relationship between structural and functional connectivity of episodic memory networks in healthy children and pediatric brain tumor survivors Pediatric brain tumor survivors demonstrate disrupted episodic memory, white matter microstructure and theta oscillatory synchronization compared to healthy children Findings suggest white matter microstructure modulates episodic memory through effects on oscillatory synchronization within relevant episodic memory networks.

Postoperative cerebellar mutism syndrome is an acquired Autism-like network disturbance.

BACKGROUND: Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumour surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates. METHODS: In this study, we analyzed post-operative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and paediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n=427). RESULTS: Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the paediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviours. CONCLUSIONS: Our findings indicate that CMS-associated lesions result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Radiomic Features Based on MRI Predict Progression-Free Survival in Pediatric Diffuse Midline Glioma/Diffuse Intrinsic Pontine Glioma.

Purpose: Biopsy-based assessment of H3 K27 M status helps in predicting survival, but biopsy is usually limited to unusual presentations and clinical trials. We aimed to evaluate whether radiomics can serve as prognostic marker to stratify diffuse intrinsic pontine glioma (DIPG) subsets. Methods: In this retrospective study, diagnostic brain MRIs of children with DIPG were analyzed. Radiomic features were extracted from tumor segmentations and data were split into training/testing sets (80:20). A conditional survival forest model was applied to predict progression-free survival (PFS) using training data. The trained model was validated on the test data, and concordances were calculated for PFS. Experiments were repeated 100 times using randomized versions of the respective percentage of the training/test data. Results: A total of 89 patients were identified (48 females, 53.9%). Median age at time of diagnosis was 6.64 years (range: 1-16.9 years) and median PFS was 8 months (range: 1-84 months). Molecular data were available for 26 patients (29.2%) (1 wild type, 3 K27M-H3.1, 22 K27M-H3.3). Radiomic features of FLAIR and nonenhanced T1-weighted sequences were predictive of PFS. The best FLAIR radiomics model yielded a concordance of .87 [95% CI: .86-.88] at 4 months PFS. The best T1-weighted radiomics model yielded a concordance of .82 [95% CI: .8-.84] at 4 months PFS. The best combined FLAIR + T1-weighted radiomics model yielded a concordance of .74 [95% CI: .71-.77] at 3 months PFS. The predominant predictive radiomic feature matrix was gray-level size-zone. Conclusion: MRI-based radiomics may predict progression-free survival in pediatric diffuse midline glioma/diffuse intrinsic pontine glioma.

Imaging of pediatric brain tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee/ASPNR White Paper.

Tumors of the central nervous system are the most common solid malignancies in children and the most common cause of pediatric cancer-related mortality. Imaging plays a central role in diagnosis, staging, treatment planning, and response assessment of pediatric brain tumors. However, the substantial variability in brain tumor imaging protocols across institutions leads to variability in patient risk stratification and treatment decisions, and complicates comparisons of clinical trial results. This White Paper provides consensus-based imaging recommendations for evaluating pediatric patients with primary brain tumors. The proposed brain magnetic resonance imaging protocol recommendations balance advancements in imaging techniques with the practicality of deployment across most imaging centers.

Neural and cognitive function in a pediatric brain injury model: The impact of task complexity.

Acquired brain injury (ABI) in childhood/adolescence results in dysfunctional neural and attentional resources during minimal and higher task load. Impact of injury on these resources during increasing load, when task design (e.g., stimuli, timing) is held constant, is not yet well understood. We examined neural communication, processing speed and controlled attention in pediatric brain tumor survivors (PBTS; Mtime since treatment = 6.78 years) and typically developing children (TDC; n = 57). Participants performed simple-go and choice reaction time (RxnT) tasks during magnetoencephalography. The weighted phase lag index estimated seed-based and whole-brain functional connectivity. Group differences were assessed using tmax and network based statistics. Mean RxnT and response accuracy measured performance. Linear models assessed group differences. Tasks were analyzed individually to account for a difference in trial numbers. During both tasks, PBTS demonstrated decreased seed-based connectivity in the high gamma frequency (60-100 Hz; p < .01) relative to TDC. During the choice task alone, PBTS also demonstrated decreased theta (4-7 Hz) and alpha (8-12 Hz) seed-based connectivity (p < .01), and increased RxnT in adolescence (p < .05). ABI in childhood/adolescence may predominantly disrupt recruitment of neural and attentional resources necessary for higher load tasks. These findings advance understanding of the impact of task load on brain function and cognition during development, and effects of injury.

Abnormalities of structural brain connectivity in pediatric brain tumor survivors.

Background: Pediatric brain tumor survivors are at an increased risk for white matter (WM) injury. However, damage to whole-brain structural connectivity is unelucidated. The impact of treatment on WM connectivity was investigated. Methods: Whole-brain WM networks were derived from diffusion tensor imaging data acquired for 28 irradiated patients (radiotherapy, RT) (mean age = 13.74 ± 3.32 years), 13 patients not irradiated (No RT) (mean age = 12.57 ± 2.87), and 41 typically developing children (TDC) (mean age = 13.32 ± 2.92 years). Differences in network properties were analyzed using robust regressions. Results: Participation coefficient was lower in both patient groups (RT: adj. P = .015; No RT: adj. P = .042). Compared to TDC, RT had greater clustering (adj. P = .015), local efficiency (adj. P = .003), and modularity (adj. P = .000003). WM traced from hubs was damaged in patients: left hemisphere pericallosal sulcus (FA [F = 4.97; q < 0.01]; MD [F = 11.02; q < 0.0001]; AD [F = 10.00; q < 0.0001]; RD [F = 8.53; q < 0.0001]), right hemisphere pericallosal sulcus (FA [F = 8.87; q < 0.0001]; RD [F = 8.27; q < 0.001]), and right hemisphere parietooccipital sulcus (MD [F = 5.78; q < 0.05]; RD [F = 5.12; q < 0.05]). Conclusions: Findings indicate greater segregation of WM networks after RT. Intermodular connectivity was lower after treatment with and without RT. No significant network differences were observed between patient groups. Our results are discussed in the context of a network approach that emphasizes interactions between brain regions.

Structural connectivity and intelligence in brain-injured children.

In children, higher general intelligence corresponds with better processing speed ability. However, the relationship between structural brain connectivity and processing speed in the context of intelligence is unclear. Furthermore, the impact of brain injury on this relationship is also unknown. Structural networks were constructed for 36 brain tumor patients (mean age: 13.45 ± 2.73, 58% males) and 35 typically developing children (13.30 ± 2.86, 51% males). Processing speed and general intelligence scores were acquired using standard batteries. The relationship between network properties, processing speed, and intelligence was assessed using a partial least squares analysis. Results indicated that structural networks in brain-injured children were less integrated (ß = -.38, p = 0.001) and more segregated (ß = 0.4, p = 0.0005) compared to typically developing children. There was an indirect effect of network segregation on general intelligence via processing speed, where greater network segregation predicted slower processing speed which in turn predicted worse general intelligence (GoF = 0.37). These findings provide the first evidence of relations between structural connectivity, processing speed, and intelligence in children. Injury-related disruption to the structural network may result in worse intelligence through impacts on information processing. Our findings are discussed in the context of a network approach to understanding brain-behavior relationships.

MRI Radiogenomics of Pediatric Medulloblastoma: A Multicenter Study.

Background Radiogenomics of pediatric medulloblastoma (MB) offers an opportunity for MB risk stratification, which may aid therapeutic decision making, family counseling, and selection of patient groups suitable for targeted genetic analysis. Purpose To develop machine learning strategies that identify the four clinically significant MB molecular subgroups. Materials and Methods In this retrospective study, consecutive pediatric patients with newly diagnosed MB at MRI at 12 international pediatric sites between July 1997 and May 2020 were identified. There were 1800 features extracted from T2- and contrast-enhanced T1-weighted preoperative MRI scans. A two-stage sequential classifier was designed-one that first identifies non-wingless (WNT) and non-sonic hedgehog (SHH) MB and then differentiates therapeutically relevant WNT from SHH. Further, a classifier that distinguishes high-risk group 3 from group 4 MB was developed. An independent, binary subgroup analysis was conducted to uncover radiomics features unique to infantile versus childhood SHH subgroups. The best-performing models from six candidate classifiers were selected, and performance was measured on holdout test sets. CIs were obtained by bootstrapping the test sets for 2000 random samples. Model accuracy score was compared with the no-information rate using the Wald test. Results The study cohort comprised 263 patients (mean age ± SD at diagnosis, 87 months ± 60; 166 boys). A two-stage classifier outperformed a single-stage multiclass classifier. The combined, sequential classifier achieved a microaveraged F1 score of 88% and a binary F1 score of 95% specifically for WNT. A group 3 versus group 4 classifier achieved an area under the receiver operating characteristic curve of 98%. Of the Image Biomarker Standardization Initiative features, texture and first-order intensity features were most contributory across the molecular subgroups. Conclusion An MRI-based machine learning decision path allowed identification of the four clinically relevant molecular pediatric medulloblastoma subgroups. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Chaudhary and Bapuraj in this issue.

Machine Assist for Pediatric Posterior Fossa Tumor Diagnosis: A Multinational Study.

BACKGROUND: Clinicians and machine classifiers reliably diagnose pilocytic astrocytoma (PA) on magnetic resonance imaging (MRI) but less accurately distinguish medulloblastoma (MB) from ependymoma (EP). One strategy is to first rule out the most identifiable diagnosis. OBJECTIVE: To hypothesize a sequential machine-learning classifier could improve diagnostic performance by mimicking a clinician's strategy of excluding PA before distinguishing MB from EP. METHODS: We extracted 1800 total Image Biomarker Standardization Initiative (IBSI)-based features from T2- and gadolinium-enhanced T1-weighted images in a multinational cohort of 274 MB, 156 PA, and 97 EP. We designed a 2-step sequential classifier - first ruling out PA, and next distinguishing MB from EP. For each step, we selected the best performing model from 6-candidate classifier using a reduced feature set, and measured performance on a holdout test set with the microaveraged F1 score. RESULTS: Optimal diagnostic performance was achieved using 2 decision steps, each with its own distinct imaging features and classifier method. A 3-way logistic regression classifier first distinguished PA from non-PA, with T2 uniformity and T1 contrast as the most relevant IBSI features (F1 score 0.8809). A 2-way neural net classifier next distinguished MB from EP, with T2 sphericity and T1 flatness as most relevant (F1 score 0.9189). The combined, sequential classifier was with F1 score 0.9179. CONCLUSION: An MRI-based sequential machine-learning classifiers offer high-performance prediction of pediatric posterior fossa tumors across a large, multinational cohort. Optimization of this model with demographic, clinical, imaging, and molecular predictors could provide significant advantages for family counseling and surgical planning.

Magnetic Resonance Imaging Findings Are Associated with Long-Term Global Neurological Function or Death after Traumatic Brain Injury in Critically Ill Children.

The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.

Bevacizumab for pediatric radiation necrosis.

BACKGROUND: Radiation necrosis is a frequent complication occurring after the treatment of pediatric brain tumors; however, treatment options remain a challenge. Bevacizumab is an anti-VEGF monoclonal antibody that has been shown in small adult cohorts to confer a benefit, specifically a reduction in steroid usage, but its use in children has not been well described. METHODS: We describe our experience with bevacizumab use for symptomatic radiation necrosis at 5 institutions including patients treated after both initial irradiation and reirradiation. RESULTS: We identified 26 patients treated with bevacizumab for symptomatic radiation necrosis, with a wide range of underlying diagnoses. The average age at diagnosis of radiation necrosis was 10.7 years, with a median time between the last dose of radiation and the presentation of radiation necrosis of 3.8 months (range, 0.6-110 months). Overall, we observed that 13 of 26 patients (50%) had an objective clinical improvement, with only 1 patient suffering from significant hypertension. Radiological improvement, defined as reduced T2/fluid-attenuated inversion recovery signal and mass effect, was observed in 50% of patients; however, this did not completely overlap with clinical response. Both early and late radiation necrosis responded equally well to bevacizumab therapy. Overall, bevacizumab was very well tolerated, permitting a reduction of corticosteroid dose and/or duration in the majority of patients. CONCLUSIONS: Bevacizumab appears to be effective and well-tolerated in children as treatment for symptomatic radiation necrosis and warrants more robust study in the context of controlled clinical trials.

Assessment of cognitive and neural recovery in survivors of pediatric brain tumors in a pilot clinical trial using metformin.

We asked whether pharmacological stimulation of endogenous neural precursor cells (NPCs) may promote cognitive recovery and brain repair, focusing on the drug metformin, in parallel rodent and human studies of radiation injury. In the rodent cranial radiation model, we found that metformin enhanced the recovery of NPCs in the dentate gyrus, with sex-dependent effects on neurogenesis and cognition. A pilot double-blind, placebo-controlled crossover trial was conducted (ClinicalTrials.gov, NCT02040376) in survivors of pediatric brain tumors who had been treated with cranial radiation. Safety, feasibility, cognitive tests and MRI measures of white matter and the hippocampus were evaluated as endpoints. Twenty-four participants consented and were randomly assigned to complete 12-week cycles of metformin (A) and placebo (B) in either an AB or BA sequence with a 10-week washout period at crossover. Blood draws were conducted to monitor safety. Feasibility was assessed as recruitment rate, medication adherence and procedural adherence. Linear mixed modeling was used to examine cognitive and MRI outcomes as a function of cycle, sequence and treatment. We found no clinically relevant safety concerns and no serious adverse events associated with metformin. Sequence effects were observed for all cognitive outcomes in our linear mixed models. For the subset of participants with complete data in cycle 1, metformin was associated with better performance than placebo on tests of declarative and working memory. We present evidence that a clinical trial examining the effects of metformin on cognition and brain structure is feasible in long-term survivors of pediatric brain tumors and that metformin is safe to use and tolerable in this population. This pilot trial was not intended to test the efficacy of metformin for cognitive recovery and brain growth, but the preliminary results are encouraging and warrant further investigation in a large multicenter phase 3 trial.

Response assessment in diffuse intrinsic pontine glioma: recommendations from the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group.

Optimising the conduct of clinical trials for diffuse intrinsic pontine glioma involves use of consistent, objective disease assessments and standardised response criteria. The Response Assessment in Pediatric Neuro-Oncology working group, consisting of an international panel of paediatric and adult neuro-oncologists, clinicians, radiologists, radiation oncologists, and neurosurgeons, was established to address issues and unique challenges in assessing response in children with CNS tumours. A working group was formed specifically to address response assessment in children and young adults with diffuse intrinsic pontine glioma and to develop a consensus on recommendations for response assessment. Response should be assessed using MRI of brain and spine, neurological examination, and anti-inflammatory or antiangiogenic drugs. Clinical imaging standards are defined. As with previous consensus recommendations, these recommendations will need to be validated in prospective clinical trials.

Eye Movements and White Matter are Associated with Emotional Control in Children Treated for Brain Tumors.

OBJECTIVE: Children treated for brain tumors often experience social and emotional difficulties, including challenges with emotion regulation; our goal was to investigate the attention-related component processes of emotion regulation, using a novel eye-tracking measure, and to evaluate its relations with emotional functioning and white matter (WM) organization. METHOD: Fifty-four children participated in this study; 36 children treated for posterior fossa tumors, and 18 typically developing children. Participants completed two versions of an emotion regulation eye-tracking task, designed to differentiate between implicit (i.e., automatic) and explicit (i.e., voluntary) subprocesses. The Emotional Control scale from the Behavior Rating Inventory of Executive Function was used to evaluate emotional control in daily life, and WM organization was assessed with diffusion tensor imaging. RESULTS: We found that emotional faces captured attention across all groups (F(1,51) = 32.18, p < .001, η2p = .39). However, unlike typically developing children, patients were unable to override the attentional capture of emotional faces when instructed to (emotional face-by-group interaction: F(2,51) = 5.58, p = .006, η2p = .18). Across all children, our eye-tracking measure of emotion regulation was modestly associated with the parent-report emotional control score (r = .29, p = .045), and in patients it was associated with WM microstructure in the body and splenium of the corpus callosum (all t > 3.03, all p < .05). CONCLUSIONS: Our findings suggest that an attention-related component process of emotion regulation is disrupted in children treated for brain tumors, and that it may relate to their emotional difficulties and WM organization. This work provides a foundation for future theoretical and mechanistic investigations of emotional difficulties in brain tumor survivors.