Somatic Versus Germline: A Case Series of Three Children With ATM-Mutated Medulloblastoma.

Somatic versus Germline-A Case Series of Three Children with ATM- mutated Medulloblastoma.

Imaging of pediatric calvarial and skull base tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee/ASPNR White Paper.

A standardized imaging protocol for pediatric oncology patients is essential for accurate and efficient imaging, while simultaneously promoting collaborative understanding of pathologies and radiologic assessment of treatment response. The objective of this article is to provide standardized pediatric imaging guidelines and parameters for evaluation of tumors of the pediatric orbit, calvarium, skull base, and temporal bone. This article was drafted based on current scientific literature as well as consensus opinions of imaging experts in collaboration with the Children's Oncology Group Diagnostic Imaging Committee, Society of Pediatric Radiology Oncology Committee, and American Society of Pediatric Neuroradiology.

Changes to pediatric brain tumors in 2021 World Health Organization classification of tumors of the central nervous system.

New tumor types are continuously being described with advances in molecular testing and genomic analysis resulting in better prognostics, new targeted therapy options and improved patient outcomes. As a result of these advances, pathological classification of tumors is periodically updated with new editions of the World Health Organization (WHO) Classification of Tumors books. In 2021, WHO Classification of Tumors of the Central Nervous System, 5th edition (CNS5), was published with major changes in pediatric brain tumors officially recognized including pediatric gliomas being separated from adult gliomas, ependymomas being categorized based on anatomical compartment and many new tumor types, most of them seen in children. Additional general changes, such as tumor grading now being done within tumor types rather than across entities and changes in definition of glioblastoma, are also relevant to pediatric neuro-oncology practice. The purpose of this manuscript is to highlight the major changes in pediatric brain tumors in CNS5 most relevant to radiologists. Additionally, brief descriptions of newly recognized entities will be presented with a focus on imaging findings.

Intraventricular B7-H3 CAR T Cells for Diffuse Intrinsic Pontine Glioma: Preliminary First-in-Human Bioactivity and Safety.

Diffuse intrinsic pontine glioma (DIPG) remains a fatal brainstem tumor demanding innovative therapies. As B7-H3 (CD276) is expressed on central nervous system (CNS) tumors, we designed B7-H3-specific chimeric antigen receptor (CAR) T cells, confirmed their preclinical efficacy, and opened BrainChild-03 (NCT04185038), a first-in-human phase I trial administering repeated locoregional B7-H3 CAR T cells to children with recurrent/refractory CNS tumors and DIPG. Here, we report the results of the first three evaluable patients with DIPG (including two who enrolled after progression), who received 40 infusions with no dose-limiting toxicities. One patient had sustained clinical and radiographic improvement through 12 months on study. Patients exhibited correlative evidence of local immune activation and persistent cerebrospinal fluid (CSF) B7-H3 CAR T cells. Targeted mass spectrometry of CSF biospecimens revealed modulation of B7-H3 and critical immune analytes (CD14, CD163, CSF-1, CXCL13, and VCAM-1). Our data suggest the feasibility of repeated intracranial B7-H3 CAR T-cell dosing and that intracranial delivery may induce local immune activation. SIGNIFICANCE: This is the first report of repeatedly dosed intracranial B7-H3 CAR T cells for patients with DIPG and includes preliminary tolerability, the detection of CAR T cells in the CSF, CSF cytokine elevations supporting locoregional immune activation, and the feasibility of serial mass spectrometry from both serum and CSF. This article is highlighted in the In This Issue feature, p. 1.

Precision medicine in pediatric temporal epilepsy surgery: optimization of outcomes through functional MRI memory tasks and tailored surgeries.

OBJECTIVE: The goal of epilepsy surgery is both seizure cessation and maximal preservation of function. In temporal lobe (TL) cases, the lack of functional MRI (fMRI) tasks that effectively activate mesial temporal structures hampers preoperative memory risk assessment, especially in children. This study evaluated pediatric TL surgery outcome optimization associated with tailored resection informed by an fMRI memory task. METHODS: The authors identified focal onset TL epilepsy patients with 1) TL resections; 2) viable fMRI memory scans; and 3) pre- and postoperative neuropsychological (NP) evaluations. They retrospectively evaluated preoperative fMRI memory scans, available Wada tests, pre- and postoperative NP scores, postoperative MRI scans, and postoperative Engel class outcomes. To assess fMRI memory task outcome prediction, the authors 1) overlaid preoperative fMRI activation onto postoperative structural images; 2) classified patients as having "overlap" or "no overlap" of activation and resection cavities; and 3) compared these findings with memory improvement, stability, or decline, based on Reliable Change Index calculations. RESULTS: Twenty patients met the inclusion criteria. At a median of 2.1 postoperative years, 16 patients had Engel class IA outcomes and 1 each had Engel class IB, ID, IIA, and IID outcomes. Functional MRI activation was linked to NP memory outcome in 19 of 20 cases (95%). Otherwise, heterogeneity characterized the cohort. CONCLUSIONS: Functional MRI memory task activation effectively predicted individual NP outcomes in the context of tailored TL resections. Patients had excellent seizure and overall good NP outcomes. This small study adds to extant literature indicating that pediatric TL epilepsy does not represent a single clinical syndrome. Findings support individualized surgical intervention using fMRI memory activation to help guide this precision medicine approach.

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.

Profiling PI3K-AKT-MTOR variants in focal brain malformations reveals new insights for diagnostic care.

Focal malformations of cortical development including focal cortical dysplasia, hemimegalencephaly and megalencephaly, are a spectrum of neurodevelopmental disorders associated with brain overgrowth, cellular and architectural dysplasia, intractable epilepsy, autism and intellectual disability. Importantly, focal cortical dysplasia is the most common cause of focal intractable paediatric epilepsy. Gain and loss of function variants in the PI3K-AKT-MTOR pathway have been identified in this spectrum, with variable levels of mosaicism and tissue distribution. In this study, we performed deep molecular profiling of common PI3K-AKT-MTOR pathway variants in surgically resected tissues using droplet digital polymerase chain reaction (ddPCR), combined with analysis of key phenotype data. A total of 159 samples, including 124 brain tissue samples, were collected from 58 children with focal malformations of cortical development. We designed an ultra-sensitive and highly targeted molecular diagnostic panel using ddPCR for six mutational hotspots in three PI3K-AKT-MTOR pathway genes, namely PIK3CA (p.E542K, p.E545K, p.H1047R), AKT3 (p.E17K) and MTOR (p.S2215F, p.S2215Y). We quantified the level of mosaicism across all samples and correlated genotypes with key clinical, neuroimaging and histopathological data. Pathogenic variants were identified in 17 individuals, with an overall molecular solve rate of 29.31%. Variant allele fractions ranged from 0.14 to 22.67% across all mutation-positive samples. Our data show that pathogenic MTOR variants are mostly associated with focal cortical dysplasia, whereas pathogenic PIK3CA variants are more frequent in hemimegalencephaly. Further, the presence of one of these hotspot mutations correlated with earlier onset of epilepsy. However, levels of mosaicism did not correlate with the severity of the cortical malformation by neuroimaging or histopathology. Importantly, we could not identify these mutational hotspots in other types of surgically resected epileptic lesions (e.g. polymicrogyria or mesial temporal sclerosis) suggesting that PI3K-AKT-MTOR mutations are specifically causal in the focal cortical dysplasia-hemimegalencephaly spectrum. Finally, our data suggest that ultra-sensitive molecular profiling of the most common PI3K-AKT-MTOR mutations by targeted sequencing droplet digital polymerase chain reaction is an effective molecular approach for these disorders with a good diagnostic yield when paired with neuroimaging and histopathology.

Pearls of Temporal Bone Imaging in Children with Hearing Loss.

Hearing loss is one of the most common indications for temporal bone imaging in children. Hearing loss may be congenital or acquired, and it may be conductive, sensorineural, or mixed audiologically. Temporal bone imaging plays an important role in the assessment and management of this condition. An understanding of the embryology of ear structures better enables the radiologist to interpret abnormalities on imaging of the temporal bone. Here, we provide a general review of ear development and a description of known genetic defects that contribute to congenital ear anomalies associated with hearing loss. We provide appropriate imaging techniques for the temporal bone depending on the clinical presentation and a systematic approach to imaging for children with hearing loss. Diagnostic imaging for developmental anomalies of the ear and cholesteatoma will be discussed.

Non-inferiority of a non-gadolinium-enhanced magnetic resonance imaging follow-up protocol for isolated optic pathway gliomas.

BACKGROUND: Pediatric patients with optic pathway gliomas (OPGs) typically undergo a large number of follow-up MRI brain exams with gadolinium-based contrast media (GBCM), which have been associated with gadolinium tissue retention. Therefore, careful consideration of GBCM use in these children is warranted. OBJECTIVE: To investigate whether GBCM is necessary for OPG MR imaging response assessment using a blinded, non-inferiority, multi-reader study. MATERIALS AND METHODS: We identified children with OPG and either stable disease or change in tumor size on MRI using a regional cancer registry serving the U.S. Pacific Northwest. For each child, the two relevant, consecutive MRI studies were anonymized and standardized into two imaging sets excluding or including GBCM-enhanced images. Exam pairs were compiled from 42 children with isolated OPG (19 with neurofibromatosis type 1), from a population of 106 children with OPG. We included 28 exam pairs in which there was a change in size between exams. Seven pediatric radiologists measured tumor sizes during three blinded sessions, spaced by at least 1 week. The first measuring session excluded GBCM-enhanced sequences; the others did not. The primary endpoint was intra-reader agreement for ≥ 25% change in axial cross-product measurement, using a 12% non-inferiority threshold. RESULTS: Analysis demonstrated an overall 1.2% difference (95% confidence interval, -3.2% to 5.5%) for intra-reader agreement using a non-GBCM-enhanced protocol and background variability. CONCLUSION: A non-GBCM-enhanced protocol was non-inferior to a GBCM-enhanced protocol for assessing change in size of isolated OPGs on follow-up MRI exams.

Radiomic signatures of posterior fossa ependymoma: Molecular subgroups and risk profiles.

BACKGROUND: The risk profile for posterior fossa ependymoma (EP) depends on surgical and molecular status [Group A (PFA) versus Group B (PFB)]. While subtotal tumor resection is known to confer worse prognosis, MRI-based EP risk-profiling is unexplored. We aimed to apply machine learning strategies to link MRI-based biomarkers of high-risk EP and also to distinguish PFA from PFB. METHODS: We extracted 1800 quantitative features from presurgical T2-weighted (T2-MRI) and gadolinium-enhanced T1-weighted (T1-MRI) imaging of 157 EP patients. We implemented nested cross-validation to identify features for risk score calculations and apply a Cox model for survival analysis. We conducted additional feature selection for PFA versus PFB and examined performance across three candidate classifiers. RESULTS: For all EP patients with GTR, we identified four T2-MRI-based features and stratified patients into high- and low-risk groups, with 5-year overall survival rates of 62% and 100%, respectively (P < .0001). Among presumed PFA patients with GTR, four T1-MRI and five T2-MRI features predicted divergence of high- and low-risk groups, with 5-year overall survival rates of 62.7% and 96.7%, respectively (P = .002). T1-MRI-based features showed the best performance distinguishing PFA from PFB with an AUC of 0.86. CONCLUSIONS: We present machine learning strategies to identify MRI phenotypes that distinguish PFA from PFB, as well as high- and low-risk PFA. We also describe quantitative image predictors of aggressive EP tumors that might assist risk-profiling after surgery. Future studies could examine translating radiomics as an adjunct to EP risk assessment when considering therapy strategies or trial candidacy.

A clinically applicable functional MRI memory paradigm for use with pediatric patients.

OBJECTIVE: Clinically employable functional MRI (fMRI) memory paradigms are not yet established for pediatric patient epilepsy surgery workups. Seeking to establish such a paradigm, we evaluated the effectiveness of memory fMRI tasks we developed by quantifying individual activation in a clinical pediatric setting, analyzing patterns of activation relative to the side of temporal lobe (TL) pathology, and comparing fMRI and Wada test results. METHODS: We retrospectively identified 72 patients aged 6.7-20.9 years with pathology (seizure focus and/or tumor) limited to the TL who had attempted memory and language fMRI tasks over a 9-year period as part of presurgical workups. Memory fMRI tasks required visualization of autobiographical memories in a block design alternating with covert counting. Language fMRI protocols involved verb and sentence generation. Scans were both qualitatively interpreted and quantitatively assessed for blood oxygenation level dependent (BOLD) signal change using region of interest (ROI) masks. We calculated the percentage of successfully scanned individual cases, compared 2 memory task activation masks in cases with left versus right TL pathology, and compared fMRI with Wada tests when available. Patients who had viable fMRI and Wada tests had generally concordant results. RESULTS: Of the 72 cases, 60 (83%), aged 7.6-20.9 years, successfully performed the memory fMRI tasks and 12 (17%) failed. Eleven of 12 unsuccessful scans were due to motion and/or inability to perform the tasks, and the success of a twelfth was indeterminate due to orthodontic metal artifact. Seven of the successful 60 cases had distorted anatomy that precluded employing predetermined masks for quantitative analysis. Successful fMRI memory studies showed bilateral mesial temporal activation and quantitatively demonstrated: (1) left activation (L-ACT) less than right activation (R-ACT) in cases with left temporal lobe (L-TL) pathology, (2) nonsignificant R-ACT less than L-ACT in cases with right temporal lobe (R-TL) pathology, and (3) lower L-ACT plus R-ACT activation for cases with L-TL versus R-TL pathology. Patients who had viable fMRI and Wada tests had generally concordant results. SIGNIFICANCE: This study demonstrates evidence of an fMRI memory task paradigm that elicits reliable activation at the individual level and can generally be accomplished in clinically involved pediatric patients. This autobiographical memory paradigm showed activation in mesial TL structures, and cases with left compared to right TL pathology showed differences in activation consistent with extant literature in TL epilepsy. Further studies will be required to assess outcome prediction.

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.

Association between Term Equivalent Brain Magnetic Resonance Imaging and 2-Year Outcomes in Extremely Preterm Infants: A Report from the Preterm Erythropoietin Neuroprotection Trial Cohort.

OBJECTIVES: To compare the term equivalent brain magnetic resonance imaging (MRI) findings between erythropoietin (Epo) treated and placebo control groups in infants 240/7-276/7 weeks of gestational age and to assess the associations between MRI findings and neurodevelopmental outcomes at 2 years corrected age. STUDY DESIGN: The association between brain abnormality scores and Bayley Scales of Infant Development, Third Edition at 2 years corrected age was explored in a subset of infants enrolled in the Preterm Erythropoietin Neuroprotection Trial. Potential risk factors for neurodevelopmental outcomes such as treatment assignment, recruitment site, gestational age, inpatient complications, and treatments were examined using generalized estimating equation models. RESULTS: One hundred ten infants were assigned to Epo and 110 to placebo groups. 27% of MRI scans were rated as normal, and 60%, 10%, and 2% were rated as having mild, moderate, or severe abnormality. Brain abnormality scores did not significantly differ between the treatment groups. Factors that increased the risk of higher brain injury scores included intubation; bronchopulmonary dysplasia; retinopathy of prematurity; opioid, benzodiazepine, or antibiotic treatment >7 days; and periventricular leukomalacia or severe intraventricular hemorrhage diagnosed on cranial ultrasound. Increased global brain abnormality and white matter injury scores at term equivalent were associated with reductions in cognitive, motor, and language abilities at 2 years of corrected age. CONCLUSIONS: Evidence of brain injury on brain MRIs obtained at term equivalent correlated with adverse neurodevelopmental outcomes as assessed by the Bayley Scales of Infant and Toddler Development, Third Edition at 2 years corrected age. Early Epo treatment had no effect on the MRI brain injury scores compared with the placebo group.

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

BACKGROUND: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. METHODS: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. RESULTS: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). CONCLUSIONS: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance.

Multiple Abusive Fractures in an Infant With a Concurrent Parathyroid Hormone-Related Peptide-Secreting Renal Tumor: Abusive Fractures Accompanying a Parathyroid Hormone-Related Peptide-Secreting Tumor.

BACKGROUND: When evaluating an infant with unexplained fractures for child abuse, it is important to evaluate for possible causes of underlying bone fragility. CASE: A 7-month-old infant was found to have a parathyroid hormone (PTH)-related peptide-secreting mesoblastic nephroma. In spite of having an elevated serum calcium, depressed serum phosphate, and high levels of PTH-related peptide, he had no demineralization or other hyper parathyroid-related bone changes. Instead, he had multiple classic metaphyseal lesions, fractures of differing ages including a proximal clavicle fracture, and current and past bruising. No fractures typical of bone insufficiency were present. These findings are highly indicative of abuse in addition to his hormone-secreting tumor. CONCLUSIONS: In spite of this child's abuse findings, endogenous or tumor-related hyper PTH should be in the differential of underlying bone fragility. Children with disorders that could cause injury susceptibility can also be abused.

Focal Benign Disorders of the Pediatric Mandible With Radiologic-Histopathologic Correlation: Mandibular Development and Lucent Lesions.

OBJECTIVE: Lucent lesions of the pediatric mandible may present variably. Cysts, neoplasms, and developmental and inflammatory conditions have a host of possible causes. There is also substantial overlap in the imaging appearance of cysts and that of benign but locally aggressive tumors that need to undergo resection. CONCLUSION: The purpose of this article is to present common and uncommon lucent lesions of the mandible in children, with an emphasis on benign abnormalities. Discussions of imaging and histopathologic features are provided.