Solitary Tumefactive Demyelinating Lesions in Children: Clinical and Magnetic Resonance Imaging Features, Pathologic Characteristics, and Outcomes.

BACKGROUND: Isolated tumefactive demyelinating lesions (≥2 cm) may be difficult to distinguish from contrast-enhancing brain tumors, central nervous system infections, and (rarely) tissue dysgenesis, which may all occur with increased signal on T2-weighted images. Establishing an accurate diagnosis is essential for management, and we delineate our single-center experience. METHODS: We performed a retrospective review of medical records, imaging, and biopsy specimens for patients under 18 years presenting with isolated tumefactive demyelination over a 10-year period. RESULTS: Ten children (eight female) met inclusion criteria, with a median age of 14.1 years. Lesions were most likely to involve the thalamus (six of 10), brainstem (five of 10), basal ganglia (four of 10), or corpus callosum (four of 10). Eighty percent had perilesional edema at presentation, and 60% had midline shift. Biopsies demonstrated demyelination with perivascular lymphocytic infiltration and axonal damage ranging from mild to severe. All patients were initially treated with high-dose corticosteroids, and eight of 10 required additional medical therapies such as intravenous immunoglobulin, plasmapheresis, cyclophosphamide, or rituximab. Increased intracranial pressure was managed aggressively with two of 10 patients requiring decompressive craniectomies. Clinical outcomes varied. CONCLUSIONS: Solitary tumefactive demyelinating lesions are rare, and aggressive management of inflammation and increased intracranial pressure is essential. Biopsy is helpful to evaluate for other diagnoses on the differential and maximize therapies. Treatment beyond initial therapy with corticosteroids is often required. Isolated tumefactive demyelinating lesions are uncommon; multicenter natural history studies are needed to better delineate differential diagnoses and optimal therapies.

Diffusion Analysis of Intracranial and Head and Neck Epidermoid and Temporal Bone Cholesteatoma.

BACKGROUND AND PURPOSE: Intracranial epidermoid tumors (IET), temporal bone cholesteatomas (TBC), and head and neck epidermoid cysts (ECs) are typically slow-growing, benign conditions arising from ectodermal tissue. They exhibit increased signal on diffusion-weighted imaging (DWI). While much of the imaging literature describes these lesions as showing diffusion restriction, we aimed to investigate these qualitative signal intensities and interpretations of restricted diffusion with respect to normal brain structures. This study aims to quantitatively evaluate the apparent diffusion coefficient (ADC) values and histogram features of these lesions. MATERIALS AND METHODS: This retrospective study included children with histologically confirmed IET, TBC, or EC diagnoses. Lesions were segmented, and voxel-wise calculation of ADC values was performed along with histogram analysis. ADC calculations were validated with a second analysis software to ensure accuracy. Normal brain regions of interest-including the cerebellum, white matter, and thalamus-served as normal comparators. Correlational analysis and Bland-Altman plots assessed agreement between software for ADC calculations. Differences in the distribution of values between the lesions and normal brain tissues were assessed using Wilcoxon rank sum and Kruskal-Wallis tests. RESULTS: Forty-eight pathology-proven cases were included in this study. Among them, 13(27.1%) patients had IET, 14(29.2%) had EC, and 21(43.7%) had TBC. The mean age was 8.67±5.30, and 27(52.9%) were female. The intraclass correlation for absolute agreement for lesional ADC between the two software was 0.997(95%CI=0.995-0.998). The IET, EC, and TBC median ADC values were not significantly different (973.7vs.875.7vs.933.2 x10-6 mm2/s, p=0.265). However, the ADCs of the three types of lesions were higher than those of three normal brain tissue types (933vs.766, x10-6 mm2/s, p<0.0001). CONCLUSIONS: The ADC values of IET, TBC, and EC are higher than those of normal brain regions. It is not accurate to simply classify these lesions as exhibiting restricted diffusion or reduced diffusivity without considering the tissue used for comparison. The observed hyperintensity on DWI compared to the brain is likely attributable a relative higher contribution of T2 shine-through effect. ABBREVIATIONS: TBC= Temporal Bone Cholesteatomas; IE= Intracranial Epidermoid; EC= Head and Neck Epidermal Inclusion cysts; DWI= Diffusion-Weighted Imaging; ADC= Apparent Diffusion Coefficient.

Brainstem Chipmunk Sign: A Diagnostic Imaging Clue across All Subtypes of Alexander Disease.

BACKGROUND AND PURPOSE: While classic brain MR imaging features of Alexander disease have been well-documented, lesional patterns can overlap with other leukodystrophies, especially in the early stages of the disease or in milder phenotypes. We aimed to assess the utility of a new neuroimaging sign to help increase the diagnostic specificity of Alexander disease. MATERIALS AND METHODS: A peculiar bilateral symmetric hyperintense signal on T2-weighted images affecting the medulla oblongata was identified in an index patient with type I Alexander disease. Subsequently, 5 observers performed a systematic MR imaging review for this pattern by examining 55 subjects with Alexander disease and 74 subjects with other leukodystrophies. Interobserver agreement was assessed by the κ index. Sensitivity, specificity, and receiver operating characteristic curves were determined. RESULTS: The identified pattern was present in 87% of subjects with Alexander disease and 14% of those without Alexander disease leukodystrophy (P < .001), 3 with vanishing white matter, 4 with adult polyglucosan body disease, and 3 others. It was found equally in both type I and type II Alexander disease (28/32, 88% versus 18/21, 86%; P = .851) and in subjects with unusual disease features (2/2). Sensitivity (87.3%; 95% CI, 76.0%-93.7%), specificity (86.5%; 95% CI, 76.9%-92.5%), and interobserver agreement (κ index = 0.82) were high. CONCLUSIONS: The identified pattern in the medulla oblongata, called the chipmunk sign due to its resemblance to the face of this rodent, is extremely common in subjects with Alexander disease and represents a diagnostic tool that can aid in early diagnosis, especially in subjects with otherwise atypical MR imaging findings and/or clinical features.

Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors.

BACKGROUND AND PURPOSE: Tumor segmentation is essential in surgical and treatment planning and response assessment and monitoring in pediatric brain tumors, the leading cause of cancer-related death among children. However, manual segmentation is time-consuming and has high interoperator variability, underscoring the need for more efficient methods. After training, we compared 2 deep-learning-based 3D segmentation models, DeepMedic and nnU-Net, with pediatric-specific multi-institutional brain tumor data based on multiparametric MR images. MATERIALS AND METHODS: Multiparametric preoperative MR imaging scans of 339 pediatric patients (n = 293 internal and n = 46 external cohorts) with a variety of tumor subtypes were preprocessed and manually segmented into 4 tumor subregions, ie, enhancing tumor, nonenhancing tumor, cystic components, and peritumoral edema. After training, performances of the 2 models on internal and external test sets were evaluated with reference to ground truth manual segmentations. Additionally, concordance was assessed by comparing the volume of the subregions as a percentage of the whole tumor between model predictions and ground truth segmentations using the Pearson or Spearman correlation coefficients and the Bland-Altman method. RESULTS: The mean Dice score for nnU-Net internal test set was 0.9 (SD, 0.07) (median, 0.94) for whole tumor; 0.77 (SD, 0.29) for enhancing tumor; 0.66 (SD, 0.32) for nonenhancing tumor; 0.71 (SD, 0.33) for cystic components, and 0.71 (SD, 0.40) for peritumoral edema, respectively. For DeepMedic, the mean Dice scores were 0.82 (SD, 0.16) for whole tumor; 0.66 (SD, 0.32) for enhancing tumor; 0.48 (SD, 0.27) for nonenhancing tumor; 0.48 (SD, 0.36) for cystic components, and 0.19 (SD, 0.33) for peritumoral edema, respectively. Dice scores were significantly higher for nnU-Net (P ≤ .01). Correlation coefficients for tumor subregion percentage volumes were higher (0.98 versus 0.91 for enhancing tumor, 0.97 versus 0.75 for nonenhancing tumor, 0.98 versus 0.80 for cystic components, 0.95 versus 0.33 for peritumoral edema in the internal test set). Bland-Altman plots were better for nnU-Net compared with DeepMedic. External validation of the trained nnU-Net model on the multi-institutional Brain Tumor Segmentation Challenge in Pediatrics (BraTS-PEDs) 2023 data set revealed high generalization capability in the segmentation of whole tumor, tumor core (a combination of enhancing tumor, nonenhancing tumor, and cystic components), and enhancing tumor with mean Dice scores of 0.87 (SD, 0.13) (median, 0.91), 0.83 (SD, 0.18) (median, 0.89), and 0.48 (SD, 0.38) (median, 0.58), respectively. CONCLUSIONS: The pediatric-specific data-trained nnU-Net model is superior to DeepMedic for whole tumor and subregion segmentation of pediatric brain tumors.

Towards Consistency in Pediatric Brain Tumor Measurements: Challenges, Solutions, and the Role of AI-Based Segmentation.

MR imaging is central to the assessment of tumor burden and changes over time in neuro-oncology. Several response assessment guidelines have been set forth by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working groups in different tumor histologies; however, the visual delineation of tumor components using MRIs is not always straightforward, and complexities not currently addressed by these criteria can introduce inter- and intra-observer variability in manual assessments. Differentiation of non-enhancing tumor from peritumoral edema, mild enhancement from absence of enhancement, and various cystic components can be challenging; particularly given a lack of sufficient and uniform imaging protocols in clinical practice. Automated tumor segmentation with artificial intelligence (AI) may be able to provide more objective delineations, but rely on accurate and consistent training data created manually (ground truth). Herein, this paper reviews existing challenges and potential solutions to identifying and defining subregions of pediatric brain tumors (PBTs) that are not explicitly addressed by current guidelines. The goal is to assert the importance of defining and adopting criteria for addressing these challenges, as it will be critical to achieving standardized tumor measurements and reproducible response assessment in PBTs, ultimately leading to more precise outcome metrics and accurate comparisons among clinical studies.

A Comparative Review of Imaging Journal Policies for Use of AI in Manuscript Generation.

RATIONALE AND OBJECTIVES: Artificial intelligence (AI) technologies are rapidly evolving and offering new advances almost on a day-by-day basis, including various tools for manuscript generation and modification. On the other hand, these potentially time- and effort-saving solutions come with potential bias, factual error, and plagiarism risks. Some journals have started to update their author guidelines in reference to AI-generated or AI-assisted manuscripts. The purpose of this paper is to evaluate author guidelines for including AI use policies in radiology journals and compare scientometric data between journals with and without explicit AI use policies. MATERIALS AND METHODS: This cross-sectional study included 112 MEDLINE-indexed imaging journals and evaluated their author guidelines between 13 October 2023 and 16 October 2023. Journals were identified based on subject matter and association with a radiological society. The authors' guidelines and editorial policies were evaluated for the use of AI in manuscript preparation and specific AI-generated image policies. We assessed the existence of an AI usage policy among subspecialty imaging journals. The scientometric scores of journals with and without AI use policies were compared using the Wilcoxon signed-rank test. RESULTS: Among 112 MEDLINE-indexed radiology journals, 80 journals were affiliated with an imaging society, and 32 were not. 69 (61.6%) of 112 imaging journals had an AI usage policy, and 40 (57.9%) of 69 mentioned a specific policy about AI-generated figures. CiteScore (4.9 vs 4, p = 0.023), Source Normalized Impact per Paper (1.12 vs 0.83, p = 0.06), Scientific Journal Ranking (0.75 vs 0.54, p = 0.010) and Journal Citation Indicator (0.77 vs 0.62, p = 0.038) were significantly higher in journals with an AI policy. CONCLUSION: The majority of imaging journals provide guidelines for AI-generated content, but still, a substantial number of journals do not have AI usage policies or do not require disclosure for non-human-created manuscripts. Journals with an established AI policy had higher citation and impact scores.

Progesterone for Neurodevelopment in Fetuses With Congenital Heart Defects: A Randomized Clinical Trial.

Importance: Neurodevelopmental outcomes for children with congenital heart defects (CHD) have improved minimally over the past 20 years. Objectives: To assess the feasibility and tolerability of maternal progesterone therapy as well as the magnitude of the effect on neurodevelopment for fetuses with CHD. Design, Setting, and Participants: This double-blinded individually randomized parallel-group clinical trial of vaginal natural progesterone therapy vs placebo in participants carrying fetuses with CHD was conducted between July 2014 and November 2021 at a quaternary care children's hospital. Participants included maternal-fetal dyads where the fetus had CHD identified before 28 weeks' gestational age and was likely to need surgery with cardiopulmonary bypass in the neonatal period. Exclusion criteria included a major genetic or extracardiac anomaly other than 22q11 deletion syndrome and known contraindication to progesterone. Statistical analysis was performed June 2022 to April 2024. Intervention: Participants were 1:1 block-randomized to vaginal progesterone or placebo by diagnosis: hypoplastic left heart syndrome (HLHS), transposition of the great arteries (TGA), and other CHD diagnoses. Treatment was administered twice daily between 28 and up to 39 weeks' gestational age. Main Outcomes and Measures: The primary outcome was the motor score of the Bayley Scales of Infant and Toddler Development-III; secondary outcomes included language and cognitive scales. Exploratory prespecified subgroups included cardiac diagnosis, fetal sex, genetic profile, and maternal fetal environment. Results: The 102 enrolled fetuses primarily had HLHS (n = 52 [50.9%]) and TGA (n = 38 [37.3%]), were more frequently male (n = 67 [65.7%]), and without genetic anomalies (n = 61 [59.8%]). The mean motor score differed by 2.5 units (90% CI, -1.9 to 6.9 units; P = .34) for progesterone compared with placebo, a value not statistically different from 0. Exploratory subgroup analyses suggested treatment heterogeneity for the motor score for cardiac diagnosis (P for interaction = .03) and fetal sex (P for interaction = .04), but not genetic profile (P for interaction = .16) or maternal-fetal environment (P for interaction = .70). Conclusions and Relevance: In this randomized clinical trial of maternal progesterone therapy, the overall effect was not statistically different from 0. Subgroup analyses suggest heterogeneity of the response to progesterone among CHD diagnosis and fetal sex. Trial Registration: ClinicalTrials.gov Identifier: NCT02133573.

Imaging of supratentorial intraventricular masses in children:a pictorial review- part 1.

PURPOSE: This article is the first in a two-part series designed to provide a comprehensive overview of the range of supratentorial intraventricular masses observed in children. Our primary objective is to discuss the diverse types of intraventricular masses that originate not only from cells within the choroid plexus but also from other sources. METHODS: In this article, we review relevant epidemiological data, the current genetics/molecular classification as outlined in the fifth edition of the World Health Organization's Classification of tumours of the Central Nervous System and noteworthy imaging findings. We conduct an exhaustive analysis of primary choroid plexus tumours as well as other conditions such as choroid plexus hyperplasia, choroid plexus cyst, choroid plexus xanthogranuloma, atypical teratoid rhabdoid tumour, meningioma, arteriovenous malformation and metastasis. RESULTS: We comprehensively evaluated each supratentorial intraventricular mass, providing an in-depth analysis of their unique clinical and histological characteristics. The fifth edition of the World Health Organization Classification of Tumours of the Central Nervous System introduces major modifications. These important changes could potentially have a profound impact on the management strategies and subsequent outcomes of these tumours. CONCLUSION: Intraventricular masses in children can arise from various sources. Surgical intervention is key for certain supratentorial intraventricular masses in paediatric patients, with preoperative neuroimaging essential to decide the best treatment approach, surgical or otherwise, as some cases may not require surgery.

Brain AVM compactness score in children with hereditary hemorrhagic telangiectasia.

OBJECTIVE: The brain arteriovenous malformation (BAVM) nidus compactness score (CS), determined on angiography, predicts BAVM recurrence after surgical resection among children with sporadic BAVMs. We measured the angiographic CS for BAVMs among children with hereditary hemorrhagic telangiectasia (HHT) to determine CS characteristics in this population. METHODS: A pediatric interventional neuroradiologist reviewed angiograms to determine the CS of BAVMs in children with HHT recruited to the BVMC. CS is based on overall nidus and perinidal anomalous vessel compactness. CS categories included 1 = diffuse nidus, 2 = intermediate nidus, and 3 = compact nidus. RESULTS: Forty-eight of 78 children (61.5%) with HHT and brain vascular malformations had a conventional angiogram; 47 (97.9%) angiograms were available. Fifty-four BAVMs were identified in 40 of these 47 children (85.1%). Of 54 BAVMs in children with HHT, CS was 1 in 7 (13%), 2 in 29 (53.7%), and 3 in 18 BAVMs (33.3%) compared with CS of 1 in six (26.1%), 2 in 15 (65.2%), and 3 in 2 BAVMs (8.7%) among 23 previously reported children with sporadic BAVMs, p = 0.045 (Fisher's exact). Seven children with HHT had intracranial hemorrhage: 4 had CS = 3, 1 had CS = 2, and 2 had CS = 1. CONCLUSIONS: A range of CSs exists across HHT BAVMs, suggesting it may be an angiographic measure of interest for future studies of BAVM recurrence and hemorrhage risk. Children with HHT may have more compact niduses compared to children with sporadic BAVMs. Additional research should determine whether CS affects hemorrhage risk or post-surgical recurrence risk in HHT-associated BAVMs, which could be used to direct BAVM treatment.

Association of EEG Background With Diffusion-Weighted Magnetic Resonance Neuroimaging and Short-Term Outcomes After Pediatric Cardiac Arrest.

BACKGROUND AND OBJECTIVES: EEG and MRI features are independently associated with pediatric cardiac arrest (CA) outcomes, but it is unclear whether their combination improves outcome prediction. We aimed to assess the association of early EEG background category with MRI ischemia after pediatric CA and determine whether addition of MRI ischemia to EEG background features and clinical variables improves short-term outcome prediction. METHODS: This was a single-center retrospective cohort study of pediatric CA with EEG initiated ≤24 hours and MRI obtained ≤7 days of return of spontaneous circulation. Initial EEG background was categorized as normal, slow/disorganized, discontinuous/burst-suppression, or attenuated-featureless. MRI ischemia was defined as percentage of brain tissue with apparent diffusion coefficient (ADC) <650 × 10-6 mm2/s and categorized as high (≥10%) or low (<10%). Outcomes were mortality and unfavorable neurologic outcome (Pediatric Cerebral Performance Category increase ≥1 from baseline resulting in ICU discharge score ≥3). The Kruskal-Wallis test evaluated the association of EEG with MRI. Area under the receiver operating characteristic (AUROC) curve evaluated predictive accuracy. Logistic regression and likelihood ratio tests assessed multivariable outcome prediction. RESULTS: We evaluated 90 individuals. EEG background was normal in 16 (18%), slow/disorganized in 42 (47%), discontinuous/burst-suppressed in 12 (13%), and attenuated-featureless in 20 (22%) individuals. The median percentage of MRI ischemia was 5% (interquartile range 1-18); 32 (36%) individuals had high MRI ischemia burden. Twenty-eight (31%) individuals died, and 58 (64%) had unfavorable neurologic outcome. Worse EEG background category was associated with more MRI ischemia (p < 0.001). The combination of EEG background and MRI ischemia burden had higher predictive accuracy than EEG alone (AUROC: mortality: 0.92 vs 0.87, p = 0.03) or MRI alone (AUROC: mortality: 0.92 vs 0.84, p = 0.02; unfavorable: 0.83 vs 0.73, p < 0.01). Addition of percentage of MRI ischemia to clinical variables and EEG background category improved prediction for mortality (χ2 = 19.1, p < 0.001) and unfavorable neurologic outcome (χ2 = 4.8, p = 0.03) and achieved high predictive accuracy (AUROC: mortality: 0.97; unfavorable: 0.92). DISCUSSION: Early EEG background category was associated with MRI ischemia after pediatric CA. Combining EEG and MRI data yielded higher outcome predictive accuracy than either modality alone. The addition of MRI ischemia to clinical variables and EEG background improved short-term outcome prediction.

Expanding the Imaging Spectrum of Polymorphous Low-Grade Neuroepithelial Tumor of the Young in Children.

Polymorphous low-grade neuroepithelial tumors of the young (PLNTY) are rare brain tumors first described in 2017 and recently included in the 2021 5th World Health Organization Classification of Tumors of the Central Nervous System. They typically affect children and young adults. Few pediatric cases have been reported in the literature. The most common imaging features described, include location within the temporal lobe, involvement of the cortical/subcortical region, coarse calcifications, and well-defined margins with solid and cystic morphology, with slight-or-no enhancement. However, there is limited information on imaging features in children. We present the imaging spectrum of neuroimaging features in a series of pediatric patients with a histologically and molecularly proved PLNTY diagnosis. Coarse calcifications are uncommon in children compared with the adult literature, and they may develop with time. The transmantle-like sign can be observed, and adjacent cortical dysplasia may be seen. Seizure recurrence may occur despite gross total resection of the tumor.

Association between ASL MRI-derived cerebral blood flow and outcomes after pediatric cardiac arrest.

AIM: Cerebral blood flow (CBF) is dysregulated after cardiac arrest. It is unknown if post-arrest CBF is associated with outcome. We aimed to determine the association of CBF derived from arterial spin labelling (ASL) MRI with outcome after pediatric cardiac arrest. METHODS: Retrospective observational study of patients ≤18 years who had a clinically obtained brain MRI within 7 days of cardiac arrest between June 2005 and December 2019. Primary outcome was unfavorable neurologic status: change in Pediatric Cerebral Performance Category (PCPC) ≥1 from pre-arrest that resulted in hospital discharge PCPC 3-6. We measured CBF in whole brain and regions of interest (ROIs) including frontal, parietal, and temporal cortex, caudate, putamen, thalamus, and brainstem using pulsed ASL. We compared CBF between outcome groups using Wilcoxon Rank-Sum and performed logistic regression to associate each region's CBF with outcome, accounting for age, sex, and time between arrest and MRI. RESULTS: Forty-eight patients were analyzed (median age 2.8 [IQR 0.95, 8.8] years, 65% male). Sixty-nine percent had unfavorable outcome. Time from arrest to MRI was 4 [3,5] days and similar between outcome groups (p = 0.39). Whole brain median CBF was greater for unfavorable compared to favorable groups (28.3 [20.9,33.0] vs. 19.6 [15.3,23.1] ml/100 g/min, p = 0.007), as was CBF in individual ROIs. Greater CBF in the whole brain and individual ROIs was associated with higher odds of unfavorable outcome after controlling for age, sex, and days from arrest to MRI (aOR for whole brain 19.08 [95% CI 1.94, 187.41]). CONCLUSION: CBF measured 3-5 days after pediatric cardiac arrest by ASL MRI was independently associated with unfavorable outcome.

Predictors of the inability to achieve full oral feeding in postoperative infants with CHD.

OBJECTIVES: Poor oral feeding is a known contributor to growth challenges in neonates with complex CHD who require early surgery. Almost 60% of these infants do not achieve full oral feeding by hospital discharge. This study's objective was to identify predictors of the inability to achieve full oral feeding by discharge in neonates with complex CHD following surgical intervention with cardiopulmonary bypass. STUDY DESIGN: A retrospective analysis of a prospective study of 192 full-term neonates with complex CHD was performed. A stepwise selection logistic regression model was developed to predict oral feeding status at hospital discharge. Univariate subgroup analysis was performed with groups determined based on a CHD classification system. RESULTS: 58% of neonates (112/192) failed to achieve full oral feeding by hospital discharge. A logistic regression model identified duration of deep hypothermic circulatory arrest and reintubation as predictors of the inability to achieve full oral feeding. Among neonates who achieved full oral feeding by discharge (42%), only 7.5% did so after postoperative day 10. Brain maturation, brain injury, and preoperative oral feeding were not predictors of full postoperative oral feeding. CONCLUSIONS: Many infants with CHD fail to achieve full oral feeding by time of hospital discharge. Longer duration of deep hypothermic circulatory arrest and increased number of intubations were predictive of poor feeding after surgery. Prolonging hospitalisation solely to achieve full oral feeding after postoperative day ten is of limited utility; earlier discharge should be promoted to avoid negative impacts on neonatal neurodevelopment as unintended consequences of lengthy hospitalisations.

Imaging of supratentorial intraventricular masses in children: a pictorial review-part 2.

PURPOSE: This article is the second in a two-part series aimed at exploring the spectrum of supratentorial intraventricular masses in children. In particular, this part delves into masses originating from cells of the ventricular lining, those within the septum pellucidum, and brain parenchyma cells extending into the ventricles. The aim of this series is to offer a comprehensive understanding of these supratentorial intraventricular masses, encompassing their primary clinical findings and histological definitions. METHODS: We conducted a review and analysis of relevant epidemiological data, the current genetics/molecular classifications as per the fifth edition of the World Health Organization (WHO) Classification of Tumors of the Central Nervous System (WHO CNS5), and imaging findings. Each supratentorial intraventricular mass was individually evaluated, with a detailed discussion on its clinical and histological features. RESULTS: This article covers a range of supratentorial intraventricular masses observed in children. These include colloid cysts, subependymal giant cell astrocytomas, ependymomas, gangliogliomas, myxoid glioneuronal tumors, central neurocytomas, high-grade gliomas, pilocytic astrocytomas, cavernous malformations, and other embryonal tumors. Each mass type is characterized both clinically and histologically, offering an in-depth review of their individual imaging characteristics. CONCLUSION: The WHO CNS5 introduces notable changes, emphasizing the vital importance of molecular diagnostics in classifying pediatric central nervous system tumors. These foundational shifts have significant potential to impact management strategies and, as a result, the outcomes of intraventricular masses in children.

Cerebral microhemorrhages in children with congenital heart disease: Prevalence, risk factors, and impact on neurodevelopmental outcomes.

Background: Infants with complex congenital heart disease (CHD) require life-saving corrective/palliative heart surgery in the first weeks of life. These infants are at risk for brain injury and poor neurodevelopmental outcomes. Cerebral microhemorrhages (CMH) are frequently seen after neonatal bypass heart surgery, but it remains unknown if CMH are a benign finding or constitute injury. Herein, we investigate the risk factors for developing CMH and their clinical significance. Methods: 192 infants with CHD undergoing corrective cardiac surgery with cardiopulmonary bypass (CPB) at a single institution were prospectively evaluated with pre-(n = 183) and/or postoperative (n = 162) brain magnetic resonance imaging (MRI). CMH severity was scored based on total number of microhemorrhages. Antenatal, perioperative, and postoperative candidate risk factors for CMH and neurodevelopmental (ND) outcomes were analyzed. Eighteen-month neurodevelopmental outcomes were assessed using the Bayley-III Scales of Infants and Toddler Development in a subset of patients (n = 82). Linear regression was used to analyze associations between risk factors or ND outcomes and presence/number of CMH. Results: The most common CHD subtypes were hypoplastic left heart syndrome (HLHS) (37%) and transposition of the great arteries (TGA) (33%). Forty-two infants (23%) had CMH present on MRI before surgery and 137 infants (85%) post-surgery. No parameters evaluated were significant risk factors for preoperative CMH. In multivariate analysis, cardiopulmonary bypass (CPB) duration (p < 0.0001), use of extracorporeal membrane oxygenation (ECMO) support (p < 0.0005), postoperative seizure(s) (p < 0.03), and lower birth weight (p < 0.03) were associated with new or worsened CMH postoperatively. Higher CMH number was associated with lower scores on motor (p < 0.03) testing at 18 months. Conclusion: CMH is a common imaging finding in infants with CHD with increased prevalence and severity after CPB and adverse impact on neurodevelopmental outcomes starting at a young age. Longer duration of CPB and need for postoperative ECMO were the most significant risk factors for developing CMH. However, presence of CMH on preoperative scans indicates non-surgical risk factors that are yet to be identified. Neuroprotective strategies to mitigate risk factors for CMH may improve neurodevelopmental outcomes in this vulnerable population.

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.

Pediatric brain and spinal cancers remain the leading cause of cancer-related death in children. Advancements in clinical decision-support in pediatric neuro-oncology utilizing the wealth of radiology imaging data collected through standard care, however, has significantly lagged other domains. Such data is ripe for use with predictive analytics such as artificial intelligence (AI) methods, which require large datasets. To address this unmet need, we provide a multi-institutional, large-scale pediatric dataset of 23,101 multi-parametric MRI exams acquired through routine care for 1,526 brain tumor patients, as part of the Children's Brain Tumor Network. This includes longitudinal MRIs across various cancer diagnoses, with associated patient-level clinical information, digital pathology slides, as well as tissue genotype and omics data. To facilitate downstream analysis, treatment-naïve images for 370 subjects were processed and released through the NCI Childhood Cancer Data Initiative via the Cancer Data Service. Through ongoing efforts to continuously build these imaging repositories, our aim is to accelerate discovery and translational AI models with real-world data, to ultimately empower precision medicine for children.

Watershed infarction in COVID-19: The necessity of neuroimaging in patients with subtle neurological symptoms.

Background: Cerebrovascular diseases comprise a significant portion of neurological disorders related to coronavirus disease 2019 (COVID-19). We evaluated the clinical and imaging characteristics of a cohort of COVID-19 patients with stroke and also identified patients with watershed infarcts. Methods: In this cross-sectional study, seventy-three COVID-19 patients with ischemic stroke were included between October 2020 and January 2021. Patients were evaluated based on the following clinical and imaging features: severity of COVID-19 (critical/ non-critical), stroke type, presence/absence of clinical suspicion of stroke, medical risk factors, Fazekas scale, atherothrombosis, small vessel disease, cardiac pathology, other causes, and dissection (ASCOD) criteria classification, and presence or absence of watershed infarction. Clinical outcomes were assessed based on Modified Rankin Scale (MRS) and mortality. Results: Most cases of ischemic stroke were due to undetermined etiology (52.1%) and cardioembolism (32.9%). In terms of imaging pattern, 17 (23.0%) patients had watershed infarction. Watershed infarction was associated with the clinically non-suspicious category [odds ratio (OR) = 4.67, P = 0.007] and death after discharge (OR = 7.1, P = 0.003). Patients with watershed infarction had a higher odds of having high Fazekas score (OR = 5.17, P = 0.007) which was also shown by the logistic regression model (adjusted OR = 6.87, P = 0.030). Thirty-one (42%) patients were clinically non-suspected for ischemic stroke. Critical COVID-19 was more common among patients with watershed infarct and clinically non-suspicious patients (P = 0.020 and P = 0.005, respectively). Patients with chronic kidney disease (CKD) were more prone to having stroke with watershed pattern (P = 0.020). Conclusion: Watershed infarct is one of the most common patterns of ischemic stroke in patients with COVID-19, for which clinicians should maintain a high index of suspicion in patients with critical COVID-19 without obvious clinical symptoms of stroke.

Brain Growth Charts for Quantitative Analysis of Pediatric Clinical Brain MRI Scans with Limited Imaging Pathology.

Background Clinically acquired brain MRI scans represent a valuable but underused resource for investigating neurodevelopment due to their technical heterogeneity and lack of appropriate controls. These barriers have curtailed retrospective studies of clinical brain MRI scans compared with more costly prospectively acquired research-quality brain MRI scans. Purpose To provide a benchmark for neuroanatomic variability in clinically acquired brain MRI scans with limited imaging pathology (SLIPs) and to evaluate if growth charts from curated clinical MRI scans differed from research-quality MRI scans or were influenced by clinical indication for the scan. Materials and Methods In this secondary analysis of preexisting data, clinical brain MRI SLIPs from an urban pediatric health care system (individuals aged ≤22 years) were scanned across nine 3.0-T MRI scanners. The curation process included manual review of signed radiology reports and automated and manual quality review of images without gross pathology. Global and regional volumetric imaging phenotypes were measured using two image segmentation pipelines, and clinical brain growth charts were quantitatively compared with charts derived from a large set of research controls in the same age range by means of Pearson correlation and age at peak volume. Results The curated clinical data set included 532 patients (277 male; median age, 10 years [IQR, 5-14 years]; age range, 28 days after birth to 22 years) scanned between 2005 and 2020. Clinical brain growth charts were highly correlated with growth charts derived from research data sets (22 studies, 8346 individuals [4947 male]; age range, 152 days after birth to 22 years) in terms of normative developmental trajectories predicted by the models (median r = 0.979). Conclusion The clinical indication of the scans did not significantly bias the output of clinical brain charts. Brain growth charts derived from clinical controls with limited imaging pathology were highly correlated with brain charts from research controls, suggesting the potential of curated clinical MRI scans to supplement research data sets. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Ertl-Wagner and Pai in this issue.

Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges.

With medical software platforms moving to cloud environments with scalable storage and computing, the translation of predictive artificial intelligence (AI) models to aid in clinical decision-making and facilitate personalized medicine for cancer patients is becoming a reality. Medical imaging, namely radiologic and histologic images, has immense analytical potential in neuro-oncology, and models utilizing integrated radiomic and pathomic data may yield a synergistic effect and provide a new modality for precision medicine. At the same time, the ability to harness multi-modal data is met with challenges in aggregating data across medical departments and institutions, as well as significant complexity in modeling the phenotypic and genotypic heterogeneity of pediatric brain tumors. In this paper, we review recent pathomic and integrated pathomic, radiomic, and genomic studies with clinical applications. We discuss current challenges limiting translational research on pediatric brain tumors and outline technical and analytical solutions. Overall, we propose that to empower the potential residing in radio-pathomics, systemic changes in cross-discipline data management and end-to-end software platforms to handle multi-modal data sets are needed, in addition to embracing modern AI-powered approaches. These changes can improve the performance of predictive models, and ultimately the ability to advance brain cancer treatments and patient outcomes through the development of such models.