Kristen Yeom, MD

Abstract

Cerebral blood flow (CBF) is an important hemodynamic parameter to evaluate brain health. It can be obtained quantitatively using medical imaging modalities such as magnetic resonance imaging and positron emission tomography (PET). Although CBF in adults has been widely studied and linked with cerebrovascular and neurodegenerative diseases, CBF data in healthy children are sparse due to the challenges in pediatric neuroimaging. An understanding of the factors affecting pediatric CBF and its normal range is crucial to determine the optimal CBF measuring techniques in pediatric neuroradiology. This review focuses on pediatric CBF studies using neuroimaging techniques in 32 articles including 2668 normal subjects ranging from birth to 18years old. A systematic literature search was conducted in PubMed, Embase, and Scopus and reported following the preferred reporting items for systematic reviews and meta-analyses (PRISMA). We identified factors (such as age, gender, mood, sedation, and fitness) that have significant effects on pediatric CBF quantification. We also investigated factors influencing the CBF measurements in infants. Based on this review, we recommend best practices to improve CBF measurements in pediatric neuroimaging. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

View details for DOI 10.1002/jmri.28758

View details for PubMedID 37170640

Abstract

OBJECTIVES: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a model that takes as input digital subtraction angiography (DSA) videos and classifies the video according to (1) the presence of large vessel occlusion (LVO), (2) the location of the occlusion, and (3) the efficacy of reperfusion.METHODS: All patients who underwent DSA for anterior circulation acute ischaemic stroke between 2012 and 2019 were included. Consecutive normal studies were included to balance classes. An external validation (EV) dataset was collected from another institution. The trained model was also used on DSA videos post mechanical thrombectomy to assess thrombectomy efficacy.RESULTS: In total, 1024 videos comprising 287 patients were included (44 for EV). Occlusion identification was achieved with 100% sensitivity and 91.67% specificity (EV 91.30% and 81.82%). Accuracy of location classification was 71% for ICA, 84% for M1, and 78% for M2 occlusions (EV 73, 25, and 50%). For post-thrombectomy DSA (n=194), the model identified successful reperfusion with 100%, 88%, and 35% for ICA, M1, and M2 occlusion (EV 89, 88, and 60%). The model could also perform classification of post-intervention videos as mTICI<3 with an AUC of 0.71.CONCLUSIONS: Our model can successfully identify normal DSA studies from those with LVO and classify thrombectomy outcome and solve a clinical radiology problem with two temporal elements (dynamic video and pre and post intervention).KEY POINTS: DEEP MOVEMENT represents a novel application of a model applied to acute stroke imaging to handle two types of temporal complexity, dynamic video and pre and post intervention. The model takes as an input digital subtraction angiograms of the anterior cerebral circulation and classifies according to (1) the presence or absence of large vessel occlusion, (2) the location of the occlusion, and (3) the efficacy of thrombectomy. Potential clinical utility lies in providing decision support via rapid interpretation (pre thrombectomy) and automated objective gradation of thrombectomy outcomes (post thrombectomy).

View details for DOI 10.1007/s00330-023-09478-3

View details for PubMedID 36847835

Abstract

The objective of this study is to determine whether machine learning may be used for objective assessment of aesthetic outcomes of auricular reconstructive surgery.Images of normal and reconstructed auricles were obtained from internet image search engines. Convolutional neural networks were constructed to identify auricles in 2D images in an auto-segmentation task and to evaluate whether an ear was normal versus reconstructed in a binary classification task. Images were then assigned a percent score for "normal" ear appearance based on confidence of the classification.Images of 1115 ears (600 normal and 515 reconstructed) were obtained. The auto-segmentation task identified auricles with 95.30% accuracy compared to manually segmented auricles. The binary classification task achieved 89.22% accuracy in identifying reconstructed ears. When the confidence of the classification was used to assign percent scores to "normal" appearance, the reconstructed ears were classified to a range of 2% (least like normal ears) to 98% (most like normal ears).Image-based analysis using machine learning can offer objective assessment without the bias of the patient or the surgeon. This methodology could be adapted to be used by surgeons to assess quality of operative outcome in clinical and research settings.4 Laryngoscope, 2022.

View details for DOI 10.1002/lary.30499

View details for PubMedID 36444914

Abstract

Ferumoxytol is an ultrasmall iron oxide nanoparticle, originally approved in 2009 by the FDA for IV treatment of iron deficiency in adults with chronic kidney disease. Subsequently, its off-label use as an MRI contrast agent has increased in clinical practice, particularly in pediatric patients in North America. Unlike conventional MRI contrast agents that are based on the rare earth metal gadolinium [gadolinium-based contrast agents (GBCAs)], ferumoxytol is biodegradable and carries no potential risk of nephrogenic systemic fibrosis. At FDA-approved doses, ferumoxytol demonstrates no long-term tissue retention in patients with intact iron metabolism. Ferumoxytol provides unique MRI properties including long-lasting vascular retention (facilitating high-quality vascular imaging) and retention in reticuloendothelial system tissues, thereby supporting a variety of applications beyond those possible with GBCAs. This Clinical Perspective describes clinical and early translational applications of ferumoxytol-enhanced MRI in children and young adults through off-label use for a variety of settings, including vascular, cardiac, and cancer imaging, drawing on the authors' institutional experience. In addition, we describe current preclinical and clinical research advances using ferumoxytol with regard to cellular and molecular imaging, and also as a novel potential cancer therapeutic agent.

View details for DOI 10.2214/AJR.22.28453

View details for PubMedID 36197052

Abstract

Distribution of intracranial hemorrhage in term and late-preterm neonates is relatively unexplored. This descriptive study examines the MR imaging-detectable spectrum of intracranial hemorrhage in this population and potential risk factors.Prevalence and distribution of intracranial hemorrhage in consecutive term/late-preterm neonates who underwent brain MR imaging between January 2011 to August 2018 were assessed. MRIs were analyzed to determine intracranial hemorrhage distribution (intraventricular, subarachnoid, subdural, intraparenchymal, and subpial/leptomeningeal), and chart review was performed for potential clinical risk factors.Of 725 term/late-preterm neonates who underwent brain MR imaging, intracranial hemorrhage occurred in 63 (9%). Fifty-two (83%) had multicompartment intracranial hemorrhage. Intraventricular and subdural were the most common hemorrhage locations, found in 41 (65%) and 39 (62%) neonates, respectively. Intraparenchymal hemorrhage occurred in 33 (52%); subpial, in 19 (30%); subarachnoid, in 12 (19%); and epidural, in 2 (3%) neonates. Twenty infants (32%) were delivered via cesarean delivery, and 5 (8%), via instrumented delivery. Cortical vein thromboses were present in 34 (54%); periventricular or medullary vein thromboses, in 37 (59%); and cerebral venous sinus thrombosis, in 5 (8%). Thirty-seven (59%) had elevated markers of coagulopathy (international normalized ratio> 1.2, fibrinogenlevel < 234), 9 (14%) had a clinically meaningful elevation in the international normalized ratio (>1.4), and 3 (5%) had a clinically meaningful decrease in the fibrinogen level (<150). Three (5%) neonates had thrombocytopenia (platelet count < 100 103/L).While relatively infrequent, there was a wide distribution of intracranial hemorrhage in term and late-preterm infants; intraventricular and subdural hemorrhages were the most common types. We report a high prevalence of venous congestion or thromboses accompanying neonatal intracranial hemorrhage.

View details for DOI 10.3174/ajnr.A7642

View details for Web of Science ID 000861202300001

View details for PubMedID 36137666

Abstract

BACKGROUND: Moya Moya disease (MMD) and Moya Moya syndrome (MMS) are cerebrovascular disorders, which affect the internal carotid arteries (ICAs). Diagnosis and surveillance of MMD/MMS in children mostly rely on qualitative evaluation of vascular imaging, especially MR angiography (MRA).OBJECTIVE: To quantitatively characterize arterial differences in pediatric patients with MMD/MMS compared with normal controls.METHODS: MRA data sets from 17 presurgery MMD/MMS (10M/7F, mean age = 10.0 years) patients were retrospectively collected and compared with MRA data sets of 98 children with normal vessel morphology (49 male patients; mean age = 10.6 years). Using a level set segmentation method with anisotropic energy weights, the cerebral arteries were automatically extracted and used to compute the radius of the ICA, middle cerebral artery (MCA), anterior cerebral artery (ACA), posterior cerebral artery (PCA), and basilar artery (BA). Moreover, the density and the average radius of all arteries in the MCA, ACA, and PCA flow territories were quantified.RESULTS: Statistical analysis revealed significant differences comparing children with MMD/MMS and those with normal vasculature (P < .001), whereas post hoc analyses identified significantly smaller radii of the ICA, MCA-M1, MCA-M2, and ACA (P < .001) in the MMD/MMS group. No significant differences were found for the radii of the PCA and BA or any artery density and average artery radius measurement in the flow territories (P > .05).CONCLUSION: His study describes the results of an automatic approach for quantitative characterization of the cerebrovascular system in patients with MMD/MMS with promising preliminary results for quantitative surveillance in pediatric MMD/MMS management.

View details for DOI 10.1227/neu.0000000000002099

View details for PubMedID 36084178

View details for Web of Science ID 000892509500153

Abstract

Automatic segmentation of lung nodules on computed tomography (CT) images is challenging owing to the variability of morphology, location, and intensity. In addition, few segmentation methods can capture intra-nodular heterogeneity to assist lung nodule diagnosis. In this study, we propose an end-to-end architecture to perform fully automated segmentation of multiple types of lung nodules and generate intra-nodular heterogeneity images for clinical use. To this end, a hybrid loss is considered by introducing a Faster R-CNN model based on generalized intersection over union loss in generative adversarial network. The Lung Image Database Consortium image collection dataset, comprising 2,635 lung nodules, was combined with 3,200 lung nodules from five hospitals for this study. Compared with manual segmentation by radiologists, the proposed model obtained an average dice coefficient (DC) of 82.05% on the test dataset. Compared with U-net, NoduleNet, nnU-net, and other three models, the proposed method achieved comparable performance on lung nodule segmentation and generated more vivid and valid intra-nodular heterogeneity images, which are beneficial in radiological diagnosis. In an external test of 91 patients from another hospital, the proposed model achieved an average DC of 81.61%. The proposed method effectively addresses the challenges of inevitable human interaction and additional pre-processing procedures in the existing solutions for lung nodule segmentation. In addition, the results show that the intra-nodular heterogeneity images generated by the proposed model are suitable to facilitate lung nodule diagnosis in radiology.

View details for DOI 10.1109/JBHI.2021.3135647

View details for PubMedID 34910645

Abstract

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 Verschakelen in this issue.

View details for DOI 10.1148/radiol.212137

View details for PubMedID 35438562

Abstract

OBJECTIVE: There has been a large amount of research in the field of artificial intelligence (AI) as applied to clinical radiology. However, these studies vary in design and quality and systematic reviews of the entire field are lacking.This systematic review aimed to identify all papers that used deep learning in radiology to survey the literature and to evaluate their methods. We aimed to identify the key questions being addressed in the literature and to identify the most effective methods employed.METHODS: We followed the PRISMA guidelines and performed a systematic review of studies of AI in radiology published from 2015 to 2019. Our published protocol was prospectively registered.RESULTS: Our search yielded 11,083 results. Seven hundred sixty-seven full texts were reviewed, and 535 articles were included. Ninety-eight percent were retrospective cohort studies. The median number of patients included was 460. Most studies involved MRI (37%). Neuroradiology was the most common subspecialty. Eighty-eight percent used supervised learning. The majority of studies undertook a segmentation task (39%). Performance comparison was with a state-of-the-art model in 37%. The most used established architecture was UNet (14%). The median performance for the most utilised evaluation metrics was Dice of 0.89 (range .49-.99), AUC of 0.903 (range 1.00-0.61) and Accuracy of 89.4 (range 70.2-100). Of the 77 studies that externally validated their results and allowed for direct comparison, performance on average decreased by 6% at external validation (range increase of 4% to decrease 44%).CONCLUSION: This systematic review has surveyed the major advances in AI as applied to clinical radiology.KEY POINTS: While there are many papers reporting expert-level results by using deep learning in radiology, most apply only a narrow range of techniques to a narrow selection of use cases. The literature is dominated by retrospective cohort studies with limited external validation with high potential for bias. The recent advent of AI extensions to systematic reporting guidelines and prospective trial registration along with a focus on external validation and explanations show potential for translation of the hype surrounding AI from code to clinic.

View details for DOI 10.1007/s00330-022-08784-6

View details for PubMedID 35420305

Abstract

Primary brain tumors are the most common solid neoplasms in children and a leading cause of mortality in this population. MRI plays a central role in the diagnosis, characterization, treatment planning, and disease surveillance of intracranial tumors. The purpose of this review is to provide an overview of imaging methodology, including conventional and advanced MRI techniques, and illustrate the MRI appearances of common pediatric brain tumors.

View details for DOI 10.3390/diagnostics12040961

View details for PubMedID 35454009

Abstract

Cerebellar mutism syndrome, characterised by mutism, emotional lability and cerebellar motor signs, occurs in up to 39% of children following resection of medulloblastoma, the most common malignant posterior fossa tumour of childhood. Its pathophysiology remains unclear, but prior studies have implicated damage to the superior cerebellar peduncles. In this study, the objective was to conduct high-resolution spatial profilometry of the cerebellar peduncles and identify anatomic biomarkers of cerebellar mutism syndrome. In this retrospective study, twenty-eight children with medulloblastoma (mean age 8.83.8years) underwent diffusion MRI at four timepoints over one year. Forty-nine healthy children (9.04.2years), scanned at a single timepoint, served as age- and sex-matched controls. Automated Fibre Quantification was used to segment cerebellar peduncles and compute fractional anisotropy (FA) at 30 nodes along each tract. Thirteen patients developed cerebellar mutism syndrome. FA was significantly lower in the distal third of the left superior cerebellar peduncle pre-operatively in all patients compared to controls (FA in proximal third 0.228, middle and distal thirds 0.270, p=0.01, Cohen's d=0.927). Pre-operative differences in FA did not predict cerebellar mutism syndrome. However, post-operative reductions in FA were highly specific to the distal left superior cerebellar peduncle, and were most pronounced in children with cerebellar mutism syndrome compared to those without at the 1-4month follow up (0.325 vs 0.512, p=0.042, d=1.36) and at the 1-year follow up (0.342, vs 0.484, p=0.038, d=1.12). High spatial resolution cerebellar profilometry indicated a site-specific alteration of the distal segment of the superior cerebellar peduncle seen in cerebellar mutism syndrome which may have important surgical implications in the treatment of these devastating tumours of childhood.

View details for DOI 10.1016/j.nicl.2022.103000

View details for PubMedID 35370121

Abstract

Diffuse intrinsic pontine glioma (DIPG) and other H3K27M-mutated diffuse midline gliomas (DMG) are universally lethal paediatric central nervous system tumours1. We previously discovered that the disialoganglioside GD2 is highly expressed on H3K27M-mutant glioma cells and demonstrated promising preclinical efficacy of GD2-directed chimeric antigen receptor (CAR) T cells2, providing the rationale for a first-in-human Phase 1 clinical trial (NCT04196413). Because CAR T-cell-induced brainstem inflammation can result in obstructive hydrocephalus, increased intracranial pressure, and dangerous tissue shifts, neurocritical care precautions were incorporated. Here we present the clinical experience from the first four patients with H3K27M-mutant DIPG/DMG treated with GD2-CAR T cells (GD2-CART) at dose level 1 (1e6 GD2-CAR T cells/kg administered intravenously). Patients who exhibited clinical benefit were eligible for subsequent GD2-CAR T infusions administered intracerebroventricularly3. Toxicity was largely related to tumor location and reversible with intensive supportive care. On-target, off-tumor toxicity was not observed. Three of four patients exhibited clinical and radiographic improvement. Proinflammatory cytokines were increased in plasma and cerebrospinal fluid (CSF). Transcriptomic analyses of 65,598 single cells from CAR T cell products and CSF elucidate heterogeneity in response between subjects and administration routes. These early results underscore the promise of this approach for H3K27M+ DIPG/DMG therapy.

View details for DOI 10.1038/s41586-022-04489-4

View details for PubMedID 35130560

Abstract

Magnetic resonance imaging offers unrivaled visualization of the fetal brain, forming the basis for establishing age-specific morphologic milestones. However, gauging age-appropriate neural development remains a difficult task due to the constantly changing appearance of the fetal brain, variable image quality, and frequent motion artifacts. Here we present an end-to-end, attention-guided deep learning model that predicts gestational age with R2 score of 0.945, mean absolute error of 6.7days, and concordance correlation coefficient of 0.970. The convolutional neural network was trained on a heterogeneous dataset of 741 developmentally normal fetal brain images ranging from 19 to 39weeks in gestational age. We also demonstrate model performance and generalizability using independent datasets from four academic institutions across the U.S. and Turkey with R2 scores of 0.81-0.90 after minimal fine-tuning. The proposed regression algorithm provides an automated machine-enabled tool with the potential to better characterize in utero neurodevelopment and guide real-time gestational age estimation after the first trimester.

View details for DOI 10.1038/s41598-022-05468-5

View details for PubMedID 35082346

Abstract

Background: Postoperative pediatric cerebellar mutism syndrome (pCMS) is a common but severe complication that may arise following the resection of posterior fossa tumors in children. Two previous studies have aimed to preoperatively predict pCMS, with varying results. In this work, we examine the generalization of these models and determine if pCMS can be predicted more accurately using an artificial neural network (ANN).Methods: An overview of reviews was performed to identify risk factors for pCMS, and a retrospective dataset was collected as per these defined risk factors from children undergoing resection of primary posterior fossa tumors. The ANN was trained on this dataset and its performance was evaluated in comparison to logistic regression and other predictive indices via analysis of receiver operator characteristic curves. The area under the curve (AUC) and accuracy were calculated and compared using a Wilcoxon signed-rank test, with P<.05 considered statistically significant.Results: Two hundred and four children were included, of whom 80 developed pCMS. The performance of the ANN (AUC 0.949; accuracy 90.9%) exceeded that of logistic regression (P<.05) and both external models (P<.001).Conclusion: Using an ANN, we show improved prediction of pCMS in comparison to previous models and conventional methods.

View details for DOI 10.1093/noajnl/vdac003

View details for PubMedID 35233531

View details for DOI 10.1016/j.eclinm.2022.101541

Abstract

Objective: This study sought to determine if individuals with medically refractory migraine headache have volume or diffusion abnormalities on neuroimaging compared to neurotypical individuals.Background: Neuroimaging biomarkers in headache medicine continue to be limited. Early prediction of medically refractory headache and migraine disorders could result in earlier administration of high efficacy therapeutics.Methods: A single-center, retrospective, case control study was performed. All patients were evaluated clinically between 2014 and 2018. Individuals with medically refractory migraine headache (defined by ICDH-3 criteria) without any other chronic medical diseases were enrolled. Patients had to have failed more than two therapeutics and aura was not exclusionary. The initial MRI study for each patient was reviewed. Multiple brain regions were analyzed for volume and apparent diffusion coefficient values. These were compared to 81 neurotypical control patients.Results: A total of 79 patients with medically refractory migraine headache were included and compared to 74 neurotypical controls without headache disorders. Time between clinical diagnosis and neuroimaging was a median of 24 months (IQR: 12.0-37.0). Comparison of individuals with medically refractory migraine headache to controls revealed statistically significant differences in median apparent diffusion coefficient (ADC) in multiple brain subregions (p < 0.001). Post-hoc pair-wise analysis comparing individuals with medically refractory migraine headache to control patients revealed significantly decreased median ADC values for the thalamus, caudate, putamen, pallidum, amygdala, brainstem, and cerebral white matter. No volumetric differences were observed between groups.Conclusions: In individuals with medically refractory MH, ADC changes are measurable in multiple brain structures at an early age, prior to the failure of multiple pharmacologic interventions and the diagnosis of medically refractory MH. This data supports the hypothesis that structural connectivity issues may predispose some patients toward more medically refractory pain disorders such as MH.

View details for DOI 10.3389/fneur.2022.898219

View details for PubMedID 35775057

Abstract

OBJECTIVE: To assess diffusion and perfusion changes of the auditory pathway in pediatric medulloblastoma patients exposed to ototoxic therapies.STUDY DESIGN: Retrospective cohort study.SETTING: A single academic tertiary children's hospital.PATIENTS: Twenty pediatric medulloblastoma patients (13 men; mean age 12.04.8yr) treated with platinum-based chemotherapy with or without radiation and 18 age-and-sex matched controls were included. Ototoxicity scores were determined using Chang Ototoxicity Grading Scale.INTERVENTIONS: Three Tesla magnetic resonance was used for diffusion tensor and arterial spin labeling perfusion imaging.MAIN OUTCOME MEASURES: Quantitative diffusion tensor metrics were extracted from the Heschl's gyrus, auditory radiation, and inferior colliculus. Arterial spin labeling perfusion of the Heschl's gyrus was also examined.RESULTS: Nine patients had clinically significant hearing loss, or Chang grades more than or equal to 2a; 11 patients had mild/no hearing loss, or Chang grades less than 2a. The clinically significant hearing loss group showed reduced mean diffusivity in the Heschl's gyrus (p=0.018) and auditory radiation (p=0.037), and decreased perfusion in the Heschl's gyrus (p=0.001). Mild/no hearing loss group showed reduced mean diffusivity (p=0.036) in Heschl's gyrus only, with a decrease in perfusion (p=0.008). There were no differences between groups in the inferior colliculus. There was no difference in fractional anisotropy between patients exposed to ototoxic therapies and controls.CONCLUSIONS: Patients exposed to ototoxic therapies demonstrated microstructural and physiological alteration of the auditory pathway. The present study shows proof-of-concept use of diffusion tensor imaging to gauge ototoxicity along the auditory pathway. Future larger cohort studies are needed to assess significance of changes in diffusion tensor imaging longitudinally, and the relationship between these changes and hearing loss severity and longitudinal changes of the developing auditory white matter.

View details for DOI 10.1097/MAO.0000000000003336

View details for PubMedID 34739428

Abstract

Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, particularly in medical imaging. The number of applications of AI in neuroradiology has also grown. This article illustrates some of these applications. This article reviews machine learning challenges related to neuroradiology. The first approval of reimbursement for an AI algorithm by the Centers for Medicare and Medicaid Services, covering a stroke software for early detection of large vessel occlusion, is also discussed.

View details for DOI 10.1016/j.rcl.2021.07.002

View details for PubMedID 34689869

Abstract

BACKGROUND: Non-invasive differentiation between schwannomas and neurofibromas is important for appropriate management, preoperative counseling, and surgical planning, but has proven difficult using conventional imaging. The objective of this study was to develop and evaluate machine learning approaches for differentiating peripheral schwannomas from neurofibromas.METHODS: We assembled a cohort of schwannomas and neurofibromas from 3 independent institutions and extracted high-dimensional radiomic features from gadolinium-enhanced, T1-weighted MRI using the PyRadiomics package on Quantitative Imaging Feature Pipeline. Age, sex, neurogenetic syndrome, spontaneous pain, and motor deficit were recorded. We evaluated the performance of 6 radiomics-based classifier models with and without clinical features and compared model performance against human expert evaluators.RESULTS: 107 schwannomas and 59 neurofibroma were included. The primary models included both clinical and imaging data. The accuracy of the human evaluators (0.765) did not significantly exceed the no-information rate (NIR), whereas the Support Vector Machine (0.929), Logistic Regression (0.929), and Random Forest (0.905) classifiers exceeded the NIR. Using the method of DeLong, the AUC for the Logistic Regression (AUC=0.923) and K Nearest Neighbor (AUC=0.923) classifiers was significantly greater than the human evaluators (AUC=0.766; p = 0.041).CONCLUSIONS: The radiomics-based classifiers developed here proved to be more accurate and had a higher AUC on the ROC curve than expert human evaluators. This demonstrates that radiomics using routine MRI sequences and clinical features can aid in differentiation of peripheral schwannomas and neurofibromas.

View details for DOI 10.1093/neuonc/noab211

View details for PubMedID 34487172

Abstract

PURPOSE: Evaluation of intracranial artery morphology plays an important role in diagnosing avariety of neurovascular diseases. In addition to clinical symptoms, diagnosis currently relies on qualitative rather than quantitative evaluation of vascular imaging sequences, such as magnetic resonance angiography (MRA). However, there is a paucity of literature on normal arterial morphology in the pediatric population across brain development. We aimed to quantitatively assess normal, age-related changes in artery morphology in children.METHODS: We performed retrospective analysis of pediatric MRA data obtained from atertiary referral center. An MRA dataset from 98children (49boys/49girls) aged 0.6-20years (median=11.5years) with normal intracranial vasculature was retrospectively collected between 2011 and 2018. All arteries were automatically segmented to determine the vessel radius. Using an atlas-based approach, the average radius and density of arteries were measured in the three main cerebral vascular territories and the radius of five major arteries was determined at corresponding locations.RESULTS: The radii of the major arteries as well as the average artery radius and density in the different vascular territories in the brain remained constant throughout childhood and adolescence (|r|<0.369 in all cases).CONCLUSION: This study presents the first automated evaluation of intracranial vessel morphology on MRA across childhood. Our results can serve as aframework for quantitative evaluation of cerebral vessel morphology in the setting of pediatric neurovascular diseases.

View details for DOI 10.1007/s00062-021-01071-9

View details for PubMedID 34427700

Abstract

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 274MB, 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.

View details for DOI 10.1093/neuros/nyab311

View details for PubMedID 34392363

Abstract

BACKGROUND AND PURPOSE: Atypical teratoid/rhabdoid tumors and medulloblastomas have similar imaging and histologic features but distinctly different outcomes. We hypothesized that they could be distinguished by MR imaging-based radiomic phenotypes.MATERIALS AND METHODS: We retrospectively assembled T2-weighted and gadolinium-enhanced T1-weighted images of 48 posterior fossa atypical teratoid/rhabdoid tumors and 96 match-paired medulloblastomas from 7 institutions. Using a holdout test set, we measured the performance of 6 candidate classifier models using 6 imaging features derived by sparse regression of 900 T2WI and 900 T1WI Imaging Biomarker Standardization Initiative-based radiomics features.RESULTS: From the originally extracted 1800 total Imaging Biomarker Standardization Initiative-based features, sparse regression consistently reduced the feature set to 1 from T1WI and 5 from T2WI. Among classifier models, logistic regression performed with the highest AUC of 0.86, with sensitivity, specificity, accuracy, and F1 scores of 0.80, 0.82, 0.81, and 0.85, respectively. The top 3 important Imaging Biomarker Standardization Initiative features, by decreasing order of relative contribution, included voxel intensity at the 90th percentile, inverse difference moment normalized, and kurtosis-all from T2WI.CONCLUSIONS: Six quantitative signatures of image intensity, texture, and morphology distinguish atypical teratoid/rhabdoid tumors from medulloblastomas with high prediction performance across different machine learning strategies. Use of this technique for preoperative diagnosis of atypical teratoid/rhabdoid tumors could significantly inform therapeutic strategies and patient care discussions.

View details for DOI 10.3174/ajnr.A7200

View details for PubMedID 34266866

Abstract

BACKGROUND: Infants born very preterm (<32weeks gestational age (GA)) are at risk for developmental language delays. Poor language outcomes in children born preterm have been linked to neurobiological factors, including impaired development of the brain's structural connectivity (white matter), and environmental factors, including decreased exposure to maternal speech in the neonatal intensive care unit (NICU). Interventions that enhance preterm infants' exposure to maternal speech show promise as potential strategies for improving short-term health outcomes. Intervention studies have yet to establish whether increased exposure to maternal speech in the NICU offers benefits beyond the newborn period for brain and language outcomes.METHODS: This randomized controlled trial assesses the long-term effects of increased maternal speech exposure on structural connectivity at 12months of age (age adjusted for prematurity (AA)) and language outcomes between 12 and 18months of age AA. Study participants (N=42) will include infants born very preterm (24-31weeks 6/7days GA). Newborns are randomly assigned to the treatment (n=21) or standard medical care (n=21) group. Treatment consists of increased maternal speech exposure, accomplished by playing audio recordings of each baby's own mother reading a children's book via an iPod placed in their crib/incubator. Infants in the control group have the identical iPod setup but are not played recordings. The primary outcome will be measures of expressive and receptive language skills, obtained from a parent questionnaire collected at 12-18months AA. The secondary outcome will be measures of white matter development, including the mean diffusivity and fractional anisotropy derived from diffusion magnetic resonance imaging scans performed at around 36weeks postmenstrual age during the infants' routine brain imaging session before hospital discharge and 12months AA.DISCUSSION: The proposed study is expected to establish the potential impact of increased maternal speech exposure on long-term language outcomes and white matter development in infants born very preterm. If successful, the findings of this study may help to guide NICU clinical practice for promoting language and brain development. This clinical trial has the potential to advance theoretical understanding of how early language exposure directly changes brain structure for later language learning.TRIAL REGISTRATION: NIH Clinical Trials (ClinicalTrials.gov) NCT04193579 . Retrospectively registered on 10 December 2019.

View details for DOI 10.1186/s13063-021-05385-4

View details for PubMedID 34256820

Abstract

BACKGROUND: Clinicoradiologic differentiation between benign and malignant peripheral nerve sheath tumors (PNSTs) has important management implications.OBJECTIVE: To develop and evaluate machine-learning approaches to differentiate benign from malignant PNSTs.METHODS: We identified PNSTs treated at 3 institutions and extracted high-dimensional radiomics features from gadolinium-enhanced, T1-weighted magnetic resonance imaging (MRI) sequences. Training and test sets were selected randomly in a 70:30 ratio. A total of 900 image features were automatically extracted using the PyRadiomics package from Quantitative Imaging Feature Pipeline. Clinical data including age, sex, neurogenetic syndrome presence, spontaneous pain, and motor deficit were also incorporated. Features were selected using sparse regression analysis and retained features were further refined by gradient boost modeling to optimize the area under the curve (AUC) for diagnosis. We evaluated the performance of radiomics-based classifiers with and without clinical features and compared performance against human readers.RESULTS: A total of 95 malignant and 171 benign PNSTs were included. The final classifier model included 21 imaging and clinical features. Sensitivity, specificity, and AUC of 0.676, 0.882, and 0.845, respectively, were achieved on the test set. Using imaging and clinical features, human experts collectively achieved sensitivity, specificity, and AUC of 0.786, 0.431, and 0.624, respectively. The AUC of the classifier was statistically better than expert humans (P=.002). Expert humans were not statistically better than the no-information rate, whereas the classifier was (P=.001).CONCLUSION: Radiomics-based machine learning using routine MRI sequences and clinical features can aid in evaluation of PNSTs. Further improvement may be achieved by incorporating additional imaging sequences and clinical variables into future models.

View details for DOI 10.1093/neuros/nyab212

View details for PubMedID 34131749

Abstract

INTRODUCTION: MRI and MR spectroscopy (MRS) provide early biomarkers of brain injury and treatment response in neonates with hypoxic-ischaemic encephalopathy). Still, there are challenges to incorporating neuroimaging biomarkers into multisite randomised controlled trials. In this paper, we provide the rationale for incorporating MRI and MRS biomarkers into the multisite, phase III high-dose erythropoietin for asphyxia and encephalopathy (HEAL) Trial, the MRI/S protocol and describe the strategies used for harmonisation across multiple MRI platforms.METHODS AND ANALYSIS: Neonates with moderate or severe encephalopathy enrolled in the multisite HEAL trial undergo MRI and MRS between 96 and 144 hours of age using standardised neuroimaging protocols. MRI and MRS data are processed centrally and used to determine a brain injury score and quantitative measures of lactate and n-acetylaspartate. Harmonisation is achieved through standardisation-thereby reducing intrasite and intersite variance, real-time quality assurance monitoring and phantom scans.ETHICS AND DISSEMINATION: IRB approval was obtained at each participating site and written consent obtained from parents prior to participation in HEAL. Additional oversight is provided by an National Institutes of Health-appointed data safety monitoring board and medical monitor.TRIAL REGISTRATION NUMBER: NCT02811263; Pre-result.

View details for DOI 10.1136/bmjopen-2020-043852

View details for PubMedID 33888528

Abstract

To investigate the efficacy of radiomics in diagnosing patients with coronavirus disease (COVID-19) and other types of viral pneumonia with clinical symptoms and CT signs similar to those of COVID-19.Between 18 January 2020 and 20 May 2020, 110 SARS-CoV-2 positive and 108 SARS-CoV-2 negative patients were retrospectively recruited from three hospitals based on the inclusion criteria. Manual segmentation of pneumonia lesions on CT scans was performed by four radiologists. The latest version of Pyradiomics was used for feature extraction. Four classifiers (linear classifier, k-nearest neighbour, least absolute shrinkage and selection operator [LASSO], and random forest) were used to differentiate SARS-CoV-2 positive and SARS-CoV-2 negative patients. Comparison of the performance of the classifiers and radiologists was evaluated by ROC curve and Kappa score.We manually segmented 16,053 CT slices, comprising 32,625 pneumonia lesions, from the CT scans of all patients. Using Pyradiomics, 120 radiomic features were extracted from each image. The key radiomic features screened by different classifiers varied and lead to significant differences in classification accuracy. The LASSO achieved the best performance (sensitivity: 72.2%, specificity: 75.1%, and AUC: 0.81) on the external validation dataset and attained excellent agreement (Kappa score: 0.89) with radiologists (average sensitivity: 75.6%, specificity: 78.2%, and AUC: 0.81). All classifiers indicated that "Original_Firstorder_RootMeanSquared" and "Original_Firstorder_Uniformity" were significant features for this task.We identified radiomic features that were significantly associated with the classification of COVID-19 pneumonia using multiple classifiers. The quantifiable interpretation of the differences in features between the two groups extends our understanding of CT imaging characteristics of COVID-19 pneumonia.

View details for DOI 10.1016/j.ejrad.2021.109552

View details for PubMedID 33497881

View details for DOI 10.1109/ISBI48211.2021.9434126

View details for Web of Science ID 000786144100406

View details for DOI 10.1161/STROKEAHA.121.036616

Abstract

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.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.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 < 0.0001). 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 = 0.002). T1-MRI-based features showed the best performance distinguishing PFA from PFB with an AUC of 0.86.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.

View details for DOI 10.1093/neuonc/noab272

View details for PubMedID 34850171

Abstract

Children with neurofibromatosis type 1 (NF1) often report cognitive challenges, though the etiology of such remains an area of active investigation. With the advent of treatments that may affect white matter microstructure, understanding the effects of age on white matter aberrancies in NF1 becomes crucial in determining the timing of such therapeutic interventions. A cross-sectional study was performed with diffusion tensor imaging from 18 NF1 children and 26 age-matched controls. Fractional anisotropy was determined by region of interest analyses for both groups over the corpus callosum, cingulate, and bilateral frontal and temporal white matter regions. Two-way analyses of variance were done with both ages combined and age-stratified into early childhood, middle childhood, and adolescence. Significant differences in fractional anisotropy between NF1 and controls were seen in the corpus callosum and frontal white matter regions when ages were combined. When stratified by age, we found that this difference was largely driven by the early childhood (1-5.9 years) and middle childhood (6-11.9 years) age groups, whereas no significant differences were appreciable in the adolescence age group (12-18 years). This study demonstrates age-related effects on white matter microstructure disorganization in NF1, suggesting that the appropriate timing of therapeutic intervention may be in early childhood.

View details for DOI 10.1177/08830738211008736

View details for PubMedID 34048307

Abstract

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-naive 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.

View details for DOI 10.1093/noajnl/vdab042

View details for PubMedID 33977272

Abstract

The Coronavirus disease 2019 (COVID-19) presents open questions in how we clinically diagnose and assess disease course. Recently, chest computed tomography (CT) has shown utility for COVID-19 diagnosis. In this study, we developed Deep COVID DeteCT (DCD), a deep learning convolutional neural network (CNN) that uses the entire chest CT volume to automatically predict COVID-19 (COVID+) from non-COVID-19 (COVID-) pneumonia and normal controls. We discuss training strategies and differences in performance across 13 international institutions and 8 countries. The inclusion of non-China sites in training significantly improved classification performance with area under the curve (AUCs) and accuracies above 0.8 on most test sites. Furthermore, using available follow-up scans, we investigate methods to track patient disease course and predict prognosis.

View details for DOI 10.1038/s41746-020-00369-1

View details for PubMedID 33514852

Abstract

INTRODUCTION: There has been a recent explosion of research into the field of artificial intelligence as applied to clinical radiology with the advent of highly accurate computer vision technology. These studies, however, vary significantly in design and quality. While recent guidelines have been established to advise on ethics, data management and the potential directions of future research, systematic reviews of the entire field are lacking. We aim to investigate the use of artificial intelligence as applied to radiology, to identify the clinical questions being asked, which methodological approaches are applied to these questions and trends in use over time.METHODS AND ANALYSIS: We will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and by the Cochrane Collaboration Handbook. We will perform a literature search through MEDLINE (Pubmed), and EMBASE, a detailed data extraction of trial characteristics and a narrative synthesis of the data. There will be no language restrictions. We will take a task-centred approach rather than focusing on modality or clinical subspecialty. Sub-group analysis will be performed by segmentation tasks, identification tasks, classification tasks, pegression/prediction tasks as well as a sub-analysis for paediatric patients.ETHICS AND DISSEMINATION: Ethical approval will not be required for this study, as data will be obtained from publicly available clinical trials. We will disseminate our results in a peer-reviewed publication. Registration number PROSPERO: CRD42020154790.

View details for DOI 10.1186/s13244-020-00929-9

View details for PubMedID 33296033

Abstract

Purpose: To summarize the data of previously reported medical imaging features on human malignancies to provide a scientific basis for more credible imaging feature selection for future studies.Materials and Methods: A search was performed in PubMed from database inception through March 23, 2018, for studies clearly stating the decoding of medical imaging features for malignancy-related objectives and/or hypotheses. The Newcastle-Ottawa scale was used for quality assessment of the included studies. Unsupervised hierarchical clustering was performed on the manually extracted features from each included study to identify the application rules of medical imaging features across human malignancies. CT images of 1000 retrospective patients with non-small cell lung cancer were used to reveal a pattern for the value distribution of complex texture features.Results: A total of 5026 imaging features of malignancies affecting 20 parts of the human body from 930 original articles were collated and assessed in this study. A meta-feature construct was proposed to facilitate the investigation of details of any high-dimensional complex imaging features of malignancy. A correlation atlas was constructed to clarify the general rules of applying medical imaging features to the analysis of human malignancy. Assessment of this data revealed a pattern of value distributions of the most commonly reported texture features across human malignancies. Furthermore, the significant expression of the gene mutational signature 1B across human cancer was highly consistent with the presence of the run length imaging feature across different human malignancy types.Conclusion: The results of this study may facilitate more credible imaging feature selection in all oncology tasks across a wide spectrum of human malignancies and help to reduce bias and redundancies in future medical imaging studies.Keywords: Computer Aided Diagnosis (CAD), Computer Applications-General (Informatics), Evidence Based Medicine, Informatics, Research Design, Statistics, Technology AssessmentSupplemental material is available for this article.Published under a CC BY 4.0 license.

View details for DOI 10.1148/rycan.2020190079

View details for PubMedID 33778732

Abstract

PURPOSE: In the absence of a virus nucleic acid real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test and experienced radiologists, clinical diagnosis is challenging for viral pneumonia with clinical symptoms and CT signs similar to that of coronavirus disease 2019 (COVID-19). We developed an end-to-end automatic differentiation method based on CT images to identify COVID-19 pneumonia patients in real time.METHODS: From January 18 to February 23, 2020, we conducted a retrospective study and enrolled 201 patients from two hospitals in Chinawho underwent chest CT and RT-PCR tests, of which 98 patients tested positive for COVID-19 (118 males and 83 females, with an average age of 42years). Patient CT images from one hospital were divided among training, validation and test datasets with an 80%:10%:10% ratio. An end-to-end representation learning method using a large-scale bi-directional generative adversarial network (BigBiGAN) architecture was designed to extract semantic features from the CT images. The semantic feature matrix was input for linear classifier construction. Patients from the other hospital were used for external validation. Differentiation accuracy was evaluated using a receiver operating characteristic curve.RESULTS: Based on the 120-dimensional semantic features extracted by BigBiGAN from each image, the linear classifier results indicated that the area under the curve (AUC) in the training, validation and test datasets were 0.979, 0.968 and 0.972, respectively, with an average sensitivity of 92% and specificity of 91%. The AUC for external validation was 0.850, with a sensitivity of 80% and specificity of 75%. Publicly available architecture and computing resources were used throughout the study to ensure reproducibility.CONCLUSION: This study provides an efficient recognition method for coronavirus disease 2019 pneumonia, using an end-to-end design to implement targeted and effective isolation for the containment of this communicable disease.

View details for DOI 10.1007/s00259-020-04929-1

View details for PubMedID 32567006

Abstract

BACKGROUND: Very-low-birth-weight preterm infants have a higher rate of language impairments compared with children born full term. Early identification of preterm infants at risk for language delay is essential to guide early intervention at the time of optimal neuroplasticity. This study examined near-term structural brain magnetic resonance imaging (MRI) and white matter microstructure assessed on diffusion tensor imaging (DTI) in relation to early language development in children born very preterm.METHODS: A total of 102 very-low-birth-weight neonates (birthweight1500g, gestational age 32-weeks) were recruited to participate from 2010 to 2011. Near-term structural MRI was evaluated for white matter and cerebellar abnormalities. DTI fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were assessed. Language development was assessed with Bayley Scales of Infant-Toddler Development-III at 18 to 22months adjusted age. Multivariate models with leave-one-out cross-validation and exhaustive feature selection identified three brain regions most predictive of language function. Distinct logistic regression models predicted high-risk infants, defined by language scores >1 S.D. below average.RESULTS: Of 102 children, 92 returned for neurodevelopmental testing. Composite language score meanS.D. was 89.016.0; 31 of 92 children scored <85, including 15 of 92 scoring<70, suggesting moderate-to-severe delay. Children with cerebellar asymmetry had lower receptive language subscores (P=0.016). Infants at high risk for language impairments were predicted based on regional white matter microstructure on DTI with high accuracy (sensitivity, specificity) for composite (89%, 86%), expressive (100%, 90%), and receptive language (100%, 90%).CONCLUSIONS: Multivariate models of near-term structural MRI and white matter microstructure on DTI may assist in identification of preterm infants at risk for language impairment, guiding early intervention.

View details for DOI 10.1016/j.pediatrneurol.2020.02.007

View details for PubMedID 32279900

Abstract

Stereoelectroencephalography (SEEG) is a powerful intracranial diagnostic tool that requires accurate imaging for proper electrode trajectory planning to ensure efficacy and maximize patient safety. Computed tomography (CT) angiography and digital subtraction angiography are commonly used, but recent developments in magnetic resonance angiography allow for high-resolution vascular visualization without added risks of radiation. We report on the accuracy of electrode placement under robotic assistance planning utilizing a novel high-resolution magnetic resonance imaging (MRI)-based imaging modality.Sixteen pediatric patients between February 2014 and October 2017 underwent SEEG exploration for epileptogenic zone localization. A gadolinium-enhanced 3D T1-weighted spoiled gradient recalled echo sequence with minimum echo time and repetition time was applied for background parenchymal suppression and vascular enhancement. Electrode placement accuracy was determined by analyzing postoperative CT scans laid over preoperative virtual electrode trajectory paths. Entry point, target point, and closest vessel intersection were measured.For any intersection along the trajectory path, 57 intersected vessels were measured. The mean diameter of an intersected vessel was 1.0343 0.1721 mm, and 21.05% of intersections involved superficial vessels. There were 157 overall intersection + near-miss events. The mean diameter for an involved vessel was 1.0236 0.0928 mm, and superficial vessels were involved in 20.13%. Looking only at final electrode target, 3 intersection events were observed. The mean diameter of an intersected vessel was 1.0125 0.2227 mm. For intersection + near-miss events, 24 were measured. An involved vessel's mean diameter was 1.1028 0.2634 mm. For non-entry point intersections, 45 intersected vessels were measured. The mean diameter for intersected vessels was 0.9526 0.0689 mm. For non-entry point intersections + near misses, 126 events were observed. The mean diameter for involved vessels was 0.9826 0.1008 mm.We believe this novel sequence allows better identification of superficial and deeper subcortical vessels compared to conventional T1-weighted gadolinium-enhanced MRI.

View details for DOI 10.1159/000503693

View details for PubMedID 32062664

View details for DOI 10.1016/j.nicl.2020.102328

View details for DOI 10.1001/jamanetworkopen.2020.4063

Abstract

An end-to-end efficacy evaluation approach for identifying progression risk after epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) therapy in patients with stage IV EGFR variant-positive non-small cell lung cancer (NSCLC) is lacking.To propose a clinically applicable large-scale bidirectional generative adversarial network for predicting the efficacy of EGFR-TKI therapy in patients with NSCLC.This diagnostic/prognostic study enrolled 465 patients from January 1, 2010, to August 1, 2017, with follow-up from February 1, 2010, to June 1, 2020. A deep learning (DL) semantic signature to predict progression-free survival (PFS) was constructed in the training cohort, validated in 2 external validation and 2 control cohorts, and compared with the radiomics signature.An end-to-end bidirectional generative adversarial network framework was designed to predict the progression risk in patients with NSCLC.The primary end point was PFS, considering the time from the initiation of therapy to the date of recurrence, confirmed disease progression, or death.A total of 342 patients with stage IV EGFR variant-positive NSCLC receiving EGFR-TKI therapy met the inclusion criteria. Of these, 145 patients from 2 of the hospitals (n=117 and 28) formed a training cohort (mean [SD] age, 61 [11] years; 87 [60.0%] female), and the patients from 2 other hospitals comprised 2 external validation cohorts (validation cohort 1: n=101; mean [SD] age, 57 [12] years; 60 [59.4%] female; and validation cohort 2: n=96, mean [SD] age, 58 [9] years; 55 [57.3%] female). Fifty-six patients with advanced-stage EGFR variant-positive NSCLC (mean [SD] age, 52 [11] years; 26 [46.4%] female) and 67 patients with advanced-stage EGFR wild-type NSCLC (mean [SD] age, 54 [10] years; 10 [15.0%] female) who received first-line chemotherapy were included. A total of 90 (26%) receiving EGFR-TKI therapy with a high risk of rapid disease progression were identified (median [range] PFS, 7.3 [1.4-32.0] months in the training cohort, 5.0 [0.6-34.6] months in validation cohort 1, and 6.4 [1.8-20.1] months, in validation cohort 2) using the DL semantic signature.The PFS decreased by 36% (hazard ratio, 2.13; 95% CI, 1.30-3.49; P<.001) compared with that in other patients (median [range] PFS, 11.5 [1.5-64.2] months in the training cohort, 10.9 [1.1-50.5] in validation cohort 1, and 8.9 [0.8-40.6] months in validation cohort 2. No significant differences were observed when comparing the PFS of high-risk patients receiving EGFR-TKI therapy with the chemotherapy cohorts (median PFS, 6.9 vs 4.4 months; P=.08). In terms of predicting the tumor progression risk after EGFR-TKI therapy, clinical decisions based on the DL semantic signature led to better survival outcomes than those based on radiomics signature across all risk probabilities by the decision curve analysis.This diagnostic/prognostic study provides a clinically applicable approach for identifying patients with stage IV EGFR variant-positive NSCLC who are not likely to benefit from EGFR-TKI therapy. The end-to-end DL-derived semantic features eliminated all manual interventions required while using previous radiomics methods and have a better prognostic performance.

View details for DOI 10.1001/jamanetworkopen.2020.30442

View details for PubMedID 33331920

Abstract

Imaging evaluation of the cerebral ventricles is important for clinical decision-making in pediatric hydrocephalus. Although quantitative measurements of ventricular size, over time, can facilitate objective comparison, automated tools for calculating ventricular volume are not structured for clinical use. The authors aimed to develop a fully automated deep learning (DL) model for pediatric cerebral ventricle segmentation and volume calculation for widespread clinical implementation across multiple hospitals.The study cohort consisted of 200 children with obstructive hydrocephalus from four pediatric hospitals, along with 199 controls. Manual ventricle segmentation and volume calculation values served as "ground truth" data. An encoder-decoder convolutional neural network architecture, in which T2-weighted MR images were used as input, automatically delineated the ventricles and output volumetric measurements. On a held-out test set, segmentation accuracy was assessed using the Dice similarity coefficient (0 to 1) and volume calculation was assessed using linear regression. Model generalizability was evaluated on an external MRI data set from a fifth hospital. The DL model performance was compared against FreeSurfer research segmentation software.Model segmentation performed with an overall Dice score of 0.901 (0.946 in hydrocephalus, 0.856 in controls). The model generalized to external MR images from a fifth pediatric hospital with a Dice score of 0.926. The model was more accurate than FreeSurfer, with faster operating times (1.48 seconds per scan).The authors present a DL model for automatic ventricle segmentation and volume calculation that is more accurate and rapid than currently available methods. With near-immediate volumetric output and reliable performance across institutional scanner types, this model can be adapted to the real-time clinical evaluation of hydrocephalus and improve clinician workflow.

View details for DOI 10.3171/2020.6.PEDS20251

View details for PubMedID 33260138

View details for DOI 10.3389/fsurg.2020.517375

Abstract

White matter undergoes rapid development in the neonatal period. Its structure during and after development is influenced by neuronal activity. Pathological neuronal activity, as in seizures, might alter white matter, which in turn may contribute to network dysfunction. Neonatal epilepsy presents an opportunity to investigate seizures and early white matter development. Our objective was to determine whether neonatal seizures in the absence of brain injury or congenital anomalies are associated with altered white matter microstructure. In this retrospective case-control study of term neonates, cases had confirmed or suspected genetic epilepsy and normal brain magnetic resonance imaging (MRI) and no other conditions independently impacting white matter. Controls were healthy neonates with normal MRI results. White matter microstructure was assessed via quantitative mean diffusivity (MD). In 22 cases, MD was significantly lower in the genu of the corpus callosum, compared to 22 controls, controlling for gestational age and postmenstrual age at MRI. This finding suggests convergent abnormal corpus callosum microstructure in neonatal epilepsies with diverse suspected genetic causes. Further study is needed to determine the specific nature, causes, and functional impact of seizure-associated abnormal white matter in neonates, a potential pathogenic mechanism.

View details for DOI 10.1111/epi.16735

View details for PubMedID 33098118

Abstract

High-dimensional image features that underlie COVID-19 pneumonia remain opaque. We aim to compare feature engineering and deep learning methods to gain insights into the image features that drive CT-based for COVID-19 pneumonia prediction, and uncover CT image features significant for COVID-19 pneumonia from deep learning and radiomics framework.A total of 266 patients with COVID-19 and other viral pneumonia with clinical symptoms and CT signs similar to that of COVID-19 during the outbreak were retrospectively collected from three hospitals in China and the USA. All the pneumonia lesions on CT images were manually delineated by four radiologists. One hundred eighty-four patients (n=93 COVID-19 positive; n=91 COVID-19 negative; 24,216 pneumonia lesions from 12,001 CT image slices) from two hospitals from China served as discovery cohort for model development. Thirty-two patients (17 COVID-19 positive, 15 COVID-19 negative; 7883 pneumonia lesions from 3799 CT image slices) from a US hospital served as external validation cohort. A bi-directional adversarial network-based framework and PyRadiomics package were used to extract deep learning and radiomics features, respectively. Linear and Lasso classifiers were used to develop models predictive of COVID-19 versus non-COVID-19 viral pneumonia.120-dimensional deep learning image features and 120-dimensional radiomics features were extracted. Linear and Lasso classifiers identified 32 high-dimensional deep learning image features and 4 radiomics features associated with COVID-19 pneumonia diagnosis (P<0.0001). Both models achieved sensitivity >73% and specificity >75% on external validation cohort with slight superior performance for radiomics Lasso classifier. Human expert diagnostic performance improved (increase by 16.5% and 11.6% in sensitivity and specificity, respectively) when using a combined deep learning-radiomics model.We uncover specific deep learning and radiomics features to add insight into interpretability of machine learning algorithms and compare deep learning and radiomics models for COVID-19 pneumonia that might serve to augment human diagnostic performance.

View details for DOI 10.1007/s00259-020-05075-4

View details for PubMedID 33094432

Abstract

Artificial intelligence (AI) is a fast-growing research area in computer science that aims to mimic cognitive processes through a number of techniques. Supervised machine learning, a subfield of AI, includes methods that can identify patterns in high-dimensional data using labeled 'ground truth' data and apply these learnt patterns to analyze, interpret, or make predictions on new datasets. Supervised machine learning has become a significant area of interest within the medical community. Radiology and neuroradiology in particular are especially well suited for application of machine learning due to the vast amount of data that is generated. One devastating disease for which neuroimaging plays a significant role in the clinical management is stroke. Within this context, AI techniques can play pivotal roles for image-based diagnosis and management of stroke. This overview focuses on the recent advances of artificial intelligence methods - particularly supervised machine learning and deep learning - with respect to workflow, image acquisition and reconstruction, and image interpretation in patients with acute stroke, while also discussing potential pitfalls and future applications.

View details for DOI 10.1016/j.clinimag.2020.09.005

View details for PubMedID 32980785

Abstract

3D multi-echo gradient-recalled echo (ME-GRE) can simultaneously generate time-of-flight magnetic resonance angiography (pTOF) in addition to T2*-based susceptibility-weighted images (SWI). We assessed the clinical performance of pTOF generated from a 3D ME-GRE acquisition compared with conventional TOF-MRA (cTOF).Eighty consecutive children were retrospectively identified who obtained 3D ME-GRE alongside cTOF. Two blinded readers independently assessed pTOF derived from 3D ME-GRE and compared them with cTOF. A 5-point Likert scale was used to rank lesion conspicuity and to assess for diagnostic confidence.Across 80 pediatric neurovascular pathologies, a similar number of lesions were reported on pTOF and cTOF (43-40%, respectively, p>0.05). Rating of lesion conspicuity was higher with cTOF (4.51.0) as compared with pTOF (4.00.7), but this was not significantly different (p=0.06). Diagnostic confidence was rated higher with cTOF (4.80.5) than that of pTOF (3.70.6; p<0.001). Overall, the inter-rater agreement between two readers for lesion count on pTOF was classified as almost perfect (=0.98, 96% CI 0.8-1.0).In this study, TOF-MRA simultaneously generated in addition to SWI from 3D MR-GRE can serve as a diagnostic adjunct, particularly for proximal vessel disease and when conventional TOF-MRA images are absent.

View details for DOI 10.1007/s00234-020-02499-5

View details for PubMedID 32945913

Abstract

Background Iron oxide nanoparticles are an alternative contrast agent for MRI. Gadolinium deposition has raised safety concerns, but it is unknown whether ferumoxytol administration also deposits in the brain. Purpose To investigate whether there are signal intensity changes in the brain at multiecho gradient imaging following ferumoxytol exposure in children and young adults. Materials and Methods This retrospective case-control study included children and young adults, matched for age and sex, with brain arteriovenous malformations who received at least one dose of ferumoxytol from January 2014 to January 2018. In participants who underwent at least two brain MRI examinations (subgroup), the first and last available examinations were analyzed. Regions of interests were placed around deep gray structures on quantitative susceptibility mapping and R2* images. Mean susceptibility and R2* values of regions of interests were recorded. Measurements were assessed by linear regression analyses: a between-group comparison of ferumoxytol-exposed and unexposed participants and a within-group (subgroup) comparison before and after exposure. Results Seventeen participants (mean age standard deviation, 13 years 5; nine male) were in the ferumoxytol-exposed (case) group, 21 (mean age, 14 years 5; 11 male) were in the control group, and nine (mean age, 12 years 6; four male) were in the subgroup. The mean number of ferumoxytol administrations was 2 1 (range, one to four). Mean susceptibility (in parts per million [ppm]) and R2* (in inverse seconds [sec-1]) values of the dentate (case participants: 0.06 ppm 0.04 and 23.87 sec-1 4.13; control participants: 0.02 ppm 0.03 and 21.7 sec-1 5.26), substantia nigrae (case participants: 0.08 ppm 0.06 and 27.46 sec-1 5.58; control participants: 0.04 ppm 0.05 and 24.96 sec-1 5.3), globus pallidi (case participants: 0.14 ppm 0.05 and 30.75 sec-1 5.14; control participants: 0.08 ppm 0.07 and 28.82 sec-1 6.62), putamina (case participants: 0.03 ppm 0.02 and 20.63 sec-1 2.44; control participants: 0.02 ppm 0.02 and 19.65 sec-1 3.6), caudate (case participants: -0.1 ppm 0.04 and 18.21 sec-1 3.1; control participants: -0.06 ppm 0.05 and 18.83 sec-1 3.32), and thalami (case participants: 0 ppm 0.03 and 16.49 sec-1 3.6; control participants: 0.02 ppm 0.02 and 18.38 sec-1 2.09) did not differ between groups (susceptibility, P = .21; R2*, P = .24). For the subgroup, the mean interval between the first and last ferumoxytol administration was 14 months 8 (range, 1-25 months). Mean susceptibility and R2* values of the dentate (first MRI: 0.06 ppm 0.05 and 25.78 sec-1 5.9; last MRI: 0.06 ppm 0.02 and 25.55 sec-1 4.71), substantia nigrae (first MRI: 0.06 ppm 0.06 and 28.26 sec-1 9.56; last MRI: 0.07 ppm 0.06 and 25.65 sec-1 6.37), globus pallidi (first MRI: 0.13 ppm 0.07 and 27.53 sec-1 8.88; last MRI: 0.14 ppm 0.06 and 29.78 sec-1 6.54), putamina (first MRI: 0.03 ppm 0.03 and 19.78 sec-1 3.51; last MRI: 0.03 ppm 0.02 and 19.73 sec-1 3.01), caudate (first MRI: -0.09 ppm 0.05 and 21.38 sec-1 4.72; last MRI: -0.1 ppm 0.05 and 18.75 sec-1 2.68), and thalami (first MRI: 0.01 ppm 0.02 and 17.65 sec-1 5.16; last MRI: 0 ppm 0.02 and 15.32 sec-1 2.49) did not differ between the first and last MRI examinations (susceptibility, P = .95; R2*, P = .54). Conclusion No overall significant differences were found in susceptibility and R2* values of deep gray structures to suggest retained iron in the brain between ferumoxytol-exposed and unexposed children and young adults with arteriovenous malformations and in those exposed to ferumoxytol over time. RSNA, 2020.

View details for DOI 10.1148/radiol.2020200378

View details for PubMedID 32930651

Abstract

Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor detection and tumor pathology classification.The study cohort comprised 617 children (median age, 92months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons (n=122), medulloblastoma (n=272), pilocytic astrocytoma (n=135), and ependymoma (n=88). There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRIs as input to detect the presence of tumor and predict tumor class. Deep learning model performance was compared against that of 4 radiologists.Model tumor detection accuracy exceeded an AUROC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F1 score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate. Tumor type classification accuracy and F1 score were higher than those of 2 of the 4 radiologists.We present a multi-institutional deep learning model for pediatric posterior fossa tumor detection and classification with the potential to augment and improve the accuracy of radiologic diagnosis.

View details for DOI 10.3174/ajnr.A6704

View details for PubMedID 32816765

Abstract

To assess the incidence of central nervous system abnormalities in pediatric subjects with sensorineural hearing loss (SNHL).One hundred forty-three pediatric subjects evaluated for SNHL at a single academic center from 2007 to 2014 were included and divided into eight diagnosis groups based on etiology of SNHL. One hundred forty-three age- and gender-matched control subjects with no known brain-related pathology or history of hearing loss were included as healthy controls for comparison. Two neuroradiologists independently evaluated magnetic resonance imaging (MRI) and computed tomography (CT) scans for each subject. Comparison of abnormal cerebral development was performed using an ordinal logistic regression model. Concordance between CT and MRI of the temporal bone was assessed using the kappa statistic.The etiologies of hearing loss in our cohort were 37.8% genetic, 12.6% infectious, 1.4% ototoxin-induced, and 48.3% idiopathic. Brain MRI revealed cerebral developmental abnormalities in defined regions in >30% of the SNHL cohort, significantly more than in normal-hearing pediatric controls. The Sylvian fissure, Virchow-Robin spaces, and lateral ventricles were most commonly affected. In the temporal bone, the percentage of subjects with concordant findings on CT and MRI was 92% across all anatomical structures.MRI revealed a high incidence of intracranial abnormalities, suggestive of aberrant development of auditory and nonauditory neural structures associated with SNHL. CT and MRI share a high degree of concordance in detecting temporal bone anomalies. Inclusion of MRI as part of the workup of congenital SNHL may facilitate the detection of developmental anomalies of the brain associated with SNHL.

View details for DOI 10.1097/MAO.0000000000002778

View details for PubMedID 32740546

Abstract

Sensorineural hearing loss (SNHL) is the most prevalent congenital sensory deficit in children. Information regarding underlying brain microstructure could offer insight into neural development in deaf children and potentially guide therapies that optimize language development. We sought to quantitatively evaluate MRI-based cerebral volume and gray matter microstructure children with SNHL.We conducted a retrospective study of children with SNHL who obtained brain MRI at 3T. The study cohort comprised 63 children with congenital SNHL without known focal brain lesion or structural abnormality (33 males; mean age 5.3years; age range 1 to 11.8years) and 64 age-matched controls without neurological, developmental, or MRI-based brain macrostructure abnormality. An atlas-based analysis was used to extract quantitative volume and median diffusivity (ADC) in the following brain regions: cerebral cortex, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens, brain stem, and cerebral white matter. SNHL patients were further stratified by severity scores and hearing loss etiology.Children with SNHL showed higher median ADC of the cortex (p=.019), thalamus (p<.001), caudate (p=.005), and brainstem (p=.003) and smaller brainstem volumes (p=.007) compared to controls. Patients with profound bilateral SNHL did not show any significant differences compared to patients with milder bilateral SNHL, but both cohorts independently had smaller brainstem volumes compared to controls. Children with unilateral SNHL showed greater amygdala volumes compared to controls (p=.021), but no differences were found comparing unilateral SNHL to bilateral SNHL. Based on etiology for SNHL, patients with Pendrin mutations showed higher ADC values in the brainstem (p=.029, respectively); patients with Connexin 26 showed higher ADC values in both the thalamus (p<.001) and brainstem (p<.001) compared to controls.SNHL patients showed significant differences in diffusion and volume in brain subregions, with region-specific findings for patients with Connexin 26 and Pendrin mutations. Future longitudinal studies could examine macro- and microstructure changes in children with SNHL over development and potential predictive role for MRI after interventions including cochlear implant outcome.

View details for DOI 10.1016/j.nicl.2020.102328

View details for PubMedID 32622314

Abstract

Conventional single-shot FSE commonly used for fast MRI may be suboptimal for brain evaluation due to poor image contrast, SNR, or image blurring. We investigated the clinical performance of variable refocusing flip angle single-shot FSE, a variation of single-shot FSE with lower radiofrequency energy deposition and potentially faster acquisition time, as an alternative approach to fast brain MR imaging.We retrospectively compared half-Fourier single-shot FSE with half- and full-Fourier variable refocusing flip angle single-shot FSE in 30 children. Three readers reviewed images for motion artifacts, image sharpness at the brain-fluid interface, and image sharpness/tissue contrast at gray-white differentiation on a modified 5-point Likert scale. Two readers also evaluated full-Fourier variable refocusing flip angle single-shot FSE against T2-FSE for brain lesion detectability in 38 children.Variable refocusing flip angle single-shot FSE sequences showed more motion artifacts (P<.001). Variable refocusing flip angle single-shot FSE sequences scored higher regarding image sharpness at brain-fluid interfaces (P<.001) and gray-white differentiation (P<.001). Acquisition times for half- and full-Fourier variable refocusing flip angle single-shot FSE were faster than for single-shot FSE (P<.001) with a 53% and 47% reduction, respectively. Intermodality agreement between full-Fourier variable refocusing flip angle single-shot FSE and T2-FSE findings was near-perfect ( = 0.90, = 0.95), with an 8% discordance rate for ground truth lesion detection.Variable refocusing flip angle single-shot FSE achieved 2 faster scan times than single-shot FSE with improved image sharpness at brain-fluid interfaces and gray-white differentiation. Such improvements are likely attributed to a combination of improved contrast, spatial resolution, SNR, and reduced T2-decay associated with blurring. While variable refocusing flip angle single-shot FSE may be a useful alternative to single-shot FSE and, potentially, T2-FSE when faster scan times are desired, motion artifacts were more common in variable refocusing flip angle single-shot FSE, and, thus, they remain an important consideration before clinical implementation.

View details for DOI 10.3174/ajnr.A6616

View details for PubMedID 32586967

Abstract

Paediatric low-grade gliomas (also known as pLGG) are the most common type of CNS tumours in children. In general, paediatric low-grade gliomas show clinical and biological features that are distinct from adult low-grade gliomas, and the developing paediatric brain is more susceptible to toxic late effects of the tumour and its treatment. Therefore, response assessment in children requires additional considerations compared with the adult Response Assessment in Neuro-Oncology criteria. There are no standardised response criteria in paediatric clinical trials, which makes it more difficult to compare responses across studies. 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. We established a subcommittee to develop consensus recommendations for response assessment in paediatric low-grade gliomas. Final recommendations were based on literature review, current practice, and expert opinion of working group members. Consensus recommendations include imaging response assessments, with additional guidelines for visual functional outcomes in patients with optic pathway tumours. As with previous consensus recommendations, these recommendations will need to be validated in prospective clinical trials.

View details for DOI 10.1016/S1470-2045(20)30064-4

View details for PubMedID 32502457

Abstract

Epidemiological studies indicate a link between obsessive-compulsive disorder and infections, particularly streptococcal pharyngitis. Pediatric acute-onset neuropsychiatric syndrome (PANS) manifests suddenly with obsessions, compulsions, and other behavioral disturbances, often after an infectious trigger. The current working model suggests a unifying inflammatory process involving the central nervous system, particularly the basal ganglia.To investigate whether diffusion-weighted magnetic resonance imaging (DWI) detects microstructural abnormalities across the brain regions of children with PANS.Case-control study performed at a single-center, multidisciplinary clinic in the United States focusing on the evaluation and treatment of children with PANS. Sixty consecutive patients who underwent 3 Tesla (T) magnetic resonance imaging (MRI) before immunomodulation from September 3, 2012, to March 30, 2018, were retrospectively reviewed for study inclusion. Six patients were excluded by blinded investigators because of imaging or motion artifacts, 3 patients for major pathologies, and 17 patients for suboptimal atlas image registration. In total, 34 patients with PANS before initiation of treatment were compared with 64 pediatric control participants.Using atlas-based MRI analysis, regional brain volume, diffusion, and cerebral blood flow were measured in the cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, and brainstem. An age and sex-controlled multivariable analysis of covariance was used to compare patients with control participants.This study compared 34 patients with PANS (median age, 154 months; age range, 55-251 months; 17 girls and 17 boys) and 64 pediatric control participants (median age, 139 months; age range, 48-213 months); 41 girls and 23 boys). Multivariable analysis demonstrated a statistically significant difference in MRI parameters between patients with PANS and control participants (F21,74=6.91; P<.001; partial 2=0.662). All assessed brain regions had statistically significantly increased median diffusivity compared with 64 control participants. Specifically, the deep gray matter (eg, the thalamus, basal ganglia, and amygdala) demonstrated the most profound increases in diffusivity consistent with the cardinal clinical symptoms of obsessions, compulsions, emotional dysregulation, and sleep disturbances. No statistically significant differences were found regarding volume and cerebral blood flow.This study identifies cerebral microstructural differences in children with PANS in multiple brain structures, including the deep gray matter structures (eg, the thalamus, basal ganglia, and amygdala). Further study of MRI is warranted in prospective, clinical trials as a potential quantitative method for assessing patients under evaluation for PANS.

View details for DOI 10.1001/jamanetworkopen.2020.4063

View details for PubMedID 32364596

Abstract

OBJECTIVE: While conventional imaging can readily identify ventricular enlargement in hydrocephalus, structural changes that underlie microscopic tissue injury might be more difficult to capture. MRI-based diffusion tensor imaging (DTI) uses properties of water motion to uncover changes in the tissue microenvironment. The authors hypothesized that DTI can identify alterations in optic nerve microstructure in children with hydrocephalus.METHODS: The authors retrospectively reviewed 21 children (< 18 years old) who underwent DTI before and after neurosurgical intervention for acute obstructive hydrocephalus from posterior fossa tumors. Their optic nerve quantitative DTI metrics of mean diffusivity (MD) and fractional anisotropy (FA) were compared to those of 21 age-matched healthy controls.RESULTS: Patients with hydrocephalus had increased MD and decreased FA in bilateral optic nerves, compared to controls (p < 0.001). Normalization of bilateral optic nerve MD and FA on short-term follow-up (median 1 day) after neurosurgical intervention was observed, as was near-complete recovery of MD on long-term follow-up (median 1.8 years).CONCLUSIONS: DTI was used to demonstrate reversible alterations of optic nerve microstructure in children presenting acutely with obstructive hydrocephalus. Alterations in optic nerve MD and FA returned to near-normal levels on short- and long-term follow-up, suggesting that surgical intervention can restore optic nerve tissue microstructure. This technique is a safe, noninvasive imaging tool that quantifies alterations of neural tissue, with a potential role for evaluation of pediatric hydrocephalus.

View details for DOI 10.3171/2019.9.FOCUS19619

View details for PubMedID 31786546

View details for DOI 10.1016/j.pediatrneurol.2019.03.006

View details for Web of Science ID 000501411700002

Abstract

PURPOSE: To demonstrate the feasibility and evaluate the performance of a deep-learning convolutional neural network (CNN) classification model for automated identification of different types of inferior vena cava (IVC) filters on radiographs.MATERIALS AND METHODS: In total, 1,375 cropped radiographic images of 14 types of IVC filters were collected from patients enrolled in a single-center IVC filter registry, with 139 images withheld as a test set and the remainder used to train and validate the classification model. Image brightness, contrast, intensity, and rotation were varied to augment the training set. A 50-layer ResNet architecture with fixed pre-trained weights was trained using a soft margin loss over 50 epochs. The final model was evaluated on the test set.RESULTS: The CNN classification model achieved a F1 score of 0.97 (0.92-0.99) for the test set overall and of 1.00 for 10 of 14 individual filter types. Of the 139 test set images, 4 (2.9%) were misidentified, all mistaken for other filter types that appear highly similar. Heat maps elucidated salient features for each filter type that the model used for class prediction.CONCLUSIONS: A CNN classification model was successfully developed to identify 14 types of IVC filters on radiographs and demonstrated high performance. Further refinement and testing of the model is necessary before potential real-world application.

View details for DOI 10.1016/j.jvir.2019.05.026

View details for PubMedID 31542278

Abstract

To predict gait impairment in toddlers born preterm with very-low-birth-weight (VLBW), from near-term white-matter microstructure assessed with diffusion tensor imaging (DTI), using exhaustive feature selection, and cross-validation.Near-term MRI and DTI of 48 bilateral and corpus callosum regions were assessed in 66 VLBW preterm infants; at 18-22 months adjusted-age, 52/66 participants completed follow-up gait assessment of velocity, step length, step width, single-limb support and the Toddle Temporal-spatial Deviation Index (TDI). Multiple linear models with exhaustive feature selection and leave-one-out cross-validation were employed in this prospective cohort study: linear and logistic regression identified three brain regions most correlated with gait outcome.Logistic regression of near-term DTI correctly classified infants high-risk for impaired gait velocity (93% sensitivity, 79% specificity), right and left step length (91% and 93% sensitivity, 85% and 76% specificity), single-limb support (100% and 100% sensitivity, 100% and 100% specificity), step width (85% sensitivity, 80% specificity), and Toddle TDI (85% sensitivity, 75% specificity). Linear regression of near-term brain DTI and toddler gait explained 32%-49% variance in gait temporal-spatial parameters. Traditional MRI methods did not predict gait in toddlers.Near-term brain microstructure assessed with DTI and statistical learning methods predicted gait impairment, explaining substantial variance in toddler gait. Results indicate that at near term age, analysis of a set of brain regions using statistical learning methods may offer more accurate prediction of outcome at toddler age. Infants high risk for single-limb support impairment were most accurately predicted. As a fundamental element of biped gait, single-limb support may be a sensitive marker of gait impairment, influenced by early neural correlates that are evolutionarily and developmentally conserved. For infants born preterm, early prediction of gait impairment can help guide early, more effective intervention to improve quality of life. Accurate prediction of toddler gait from near-term brain microstructure on DTI. Use of machine learning analysis of neonatal neuroimaging to predict gait. Early prediction of gait impairment to guide early treatment for children born preterm.

View details for DOI 10.3389/fnhum.2019.00305

View details for PubMedID 31619977

View details for PubMedCentralID PMC6760000

View details for DOI 10.3389/fnhum.2019.00305

View details for Web of Science ID 000486616900001

Abstract

BACKGROUND: Cerebellar Mutism Syndrome (CMS) is a common complication following resection of posterior fossa tumors, most commonly after surgery for medulloblastoma. Medulloblastoma subgroups have historically been treated as a single entity when assessing CMS risk; however, recent studies highlighting their clinical heterogeneity suggest the need for subgroup-specific analysis. Here, we examine a large international multicenter cohort of molecularly characterized medulloblastoma patients to assess predictors of CMS.METHODS: We assembled a cohort of 370 molecularly characterized medulloblastoma subjects with available neuroimaging from five sites globally including Great Ormond Street Hospital, Christian Medical College and Hospital, Hospital for Sick Children, King Hussein Cancer Center, and Lucile Packard Children's Hospital. Age at diagnosis, sex, tumour volume, and CMS development were assessed in addition to molecular subgroup.RESULTS: Overall, 23.8% of patients developed CMS. CMS patients were younger (mean difference -2.05 years 0.50, P=0.0218) and had larger tumours (mean difference 10.25 cm3 4.60, P=0.0010) that were more often midline (OR=5.72, P<0.0001). In a multivariable analysis adjusting for age, sex, midline location, and tumour volume, WNT (Wingless) (adjusted OR=4.91, p=0.0063), Group 3 (adjusted OR=5.56, p=0.0022) and Group 4 (adjusted OR=8.57 p=9.1x10-5) tumours were found to be independently associated with higher risk of CMS compared with SHH (Sonic Hedgehog) tumours.CONCLUSIONS: Medulloblastoma subgroup is a very strong predictor of CMS development, independent of tumour volume and midline location. These findings have significant implications for management of both the tumour and CMS.

View details for DOI 10.1093/neuonc/noz158

View details for PubMedID 31504816

Abstract

OBJECTIVE: Posterior fossa syndrome (PFS) is a common postoperative complication following resection of posterior fossa tumors in children. It typically presents 1 to 2 days after surgery with mutism, ataxia, emotional lability, and other behavioral symptoms. Recent structural MRI studies have found an association between PFS and hypertrophic olivary degeneration, which is detectable as T2 hyperintensity in the inferior olivary nuclei (IONs) months after surgery. In this study, the authors investigated whether immediate postoperative diffusion tensor imaging (DTI) of the ION can serve as an early imaging marker of PFS.METHODS: The authors retrospectively reviewed pediatric brain tumor patients treated at their institution, Lucile Packard Children's Hospital at Stanford, from 2004 to 2016. They compared the immediate postoperative DTI studies obtained in 6 medulloblastoma patients who developed PFS to those of 6 age-matched controls.RESULTS: Patients with PFS had statistically significant increased mean diffusivity (MD) in the left ION (1085.17 215.51 vs 860.17 102.64, p = 0.044) and variably increased MD in the right ION (923.17 119.2 vs 873.67 60.16, p = 0.385) compared with age-matched controls. Patients with PFS had downward trending fractional anisotropy (FA) in both the left (0.28 0.06 vs 0.23 0.03, p = 0.085) and right (0.29 0.06 vs 0.25 0.02, p = 0.164) IONs compared with age-matched controls, although neither of these values reached statistical significance.CONCLUSIONS: Increased MD in the ION is associated with development of PFS. ION MD changes may represent an early imaging marker of PFS.

View details for DOI 10.3171/2019.5.PEDS1964

View details for PubMedID 31349230

Abstract

OBJECTIVE: Spine MRI is a diagnostic modality for evaluating pediatric CNS tumors. Applying diffusion-weighted MRI (DWI) or diffusion tensor imaging (DTI) to the spine poses challenges due to intrinsic spinal anatomy that exacerbates various image-related artifacts, such as signal dropouts or pileups, geometrical distortions, and incomplete fat suppression. The zonal oblique multislice (ZOOM)-echo-planar imaging (EPI) technique reduces geometric distortion and image blurring by reducing the field of view (FOV) without signal aliasing into the FOV. The authors hypothesized that the ZOOM-EPI method for spine DTI in concert with conventional spinal MRI is an efficient method for augmenting the evaluation of pediatric spinal tumors.METHODS: Thirty-eight consecutive patients (mean age 8 years) who underwent ZOOM-EPI spine DTI for CNS tumor workup were retrospectively identified. Patients underwent conventional spine MRI and ZOOM-EPI DTI spine MRI. Two blinded radiologists independently reviewed two sets of randomized images: conventional spine MRI without ZOOM-EPI DTI, and conventional spine MRI with ZOOM-EPI DTI. For both image sets, the reviewers scored the findings based on lesion conspicuity and diagnostic confidence using a 5-point Likert scale. The reviewers also recorded presence of tumors. Quantitative apparent diffusion coefficient (ADC) measurements of various spinal tumors were extracted. Tractography was performed in a subset of patients undergoing presurgical evaluation.RESULTS: Sixteen patients demonstrated spinal tumor lesions. The readers were in moderate agreement (kappa = 0.61, 95% CI 0.30-0.91). The mean scores for conventional MRI and combined conventional MRI and DTI were as follows, respectively: 3.0 and 4.0 for lesion conspicuity (p = 0.0039), and 2.8 and 3.9 for diagnostic confidence (p < 0.001). ZOOM-EPI DTI identified new lesions in 3 patients. In 3 patients, tractography used for neurosurgical planning showed characteristic fiber tract projections. The mean weighted ADCs of low- and high-grade tumors were 1201 * 10-6 and 865 * 10-6 mm2/sec (p = 0.002), respectively; the mean minimum weighted ADCs were 823 * 10-6 and 474 * 10-6 mm2/sec (p = 0.0003), respectively.CONCLUSIONS: Diffusion MRI with ZOOM-EPI can improve the detection of spinal lesions while providing quantitative diffusion information that helps distinguish low- from high-grade tumors. By adding a 2-minute DTI scan, quantitative diffusion information and tract profiles can reliably be obtained and serve as a useful adjunct to presurgical planning for pediatric spinal tumors.

View details for DOI 10.3171/2019.4.SPINE19178

View details for PubMedID 31277060

Abstract

BACKGROUND: Moyamoya disease often leads to ischemic strokes visible on diffusion-weighted imaging (DWI) and T2-weighted magnetic resonance imaging (MRI) with subsequent cognitive impairment. In adults with moyamoya, apparent diffusion coefficient (ADC) is correlated with regions of steal phenomenon and executive dysfunction prior to white matter changes.OBJECTIVE: To investigate quantitative global diffusion changes in pediatric moyamoya patients prior to explicit structural ischemic damage.METHODS: We retrospectively reviewed children (<20 yr old) with moyamoya disease and syndrome who underwent bypass surgery at our institution. We identified 29 children with normal structural preoperative MRI and without findings of cortical infarction or chronic white matter ischemic changes. DWI datasets were used to calculate ADC maps for each subject as well as for 60 age-matched healthy controls. Using an atlas-based approach, the cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, and brainstem were segmented in each DWI dataset and used to calculate regional volumes and ADC values.RESULTS: Multivariate analysis of covariance using the regional ADC and volume values as dependent variables and age and gender as covariates revealed a significant difference between the groups (P<.001). Post hoc analysis demonstrated significantly elevated ADC values for children with moyamoya in the cerebral cortex, white matter, caudate, putamen, and nucleus accumbens. No significant volume differences were found.CONCLUSION: Prior to having bypass surgery, and in the absence of imaging evidence of ischemic stroke, children with moyamoya exhibit cerebral diffusion changes. These findings could reflect microstructural changes stemming from exhaustion of cerebrovascular reserve.

View details for DOI 10.1093/neuros/nyz230

View details for PubMedID 31245817

View details for DOI 10.1007/s12311-018-1003-9

View details for Web of Science ID 000468112900008

View details for DOI 10.3171/2018.11.PEDS18498

View details for Web of Science ID 000462877000011

View details for DOI 10.1016/j.wneu.2018.11.039

View details for Web of Science ID 000457328100158

Abstract

OBJECTIVEMoyamoya disease is a dynamic cerebrovascular condition that often requires vascular surveillance. Arterial spin labeling (ASL) is an MR perfusion method that is increasingly used for stroke and other various neurovascular pathologies. Unlike perfusion-weighted MRI, ASL uses endogenous water molecules for signal and therefore obviates gadolinium use; and provides direct, not relative, quantitative cerebral blood flow (CBF) measures. Presently, the potential role of ASL for evaluating postoperative pediatric moyamoya patients is relatively unexplored. This study investigated the role for ASL in evaluating cerebral hemodynamic changes in children who underwent revascularization surgery.METHODSThis retrospective study examined 15 consecutive pediatric patients with moyamoya disease (n = 7) or moyamoya syndrome (n = 8) presenting between 2010 and 2014 who underwent revascularization and in whom 3T ASL was performed pre- and postoperatively. Postoperative MRI at least 3 months after revascularization procedure was used for analysis. Quantitative CBF in various vascular territories was interrogated: anterior, middle, and posterior cerebral arteries, and basal ganglia supplied by the lenticulostriate collaterals, resulting in evaluation of 20 brain regions.RESULTSAfter revascularization, CBF in the high middle cerebral artery territory significantly increased (p = 0.0059), accompanied by a decrease in CBF to the ipsilateral lenticulostriate-supplied basal ganglia (p = 0.0053). No perfusion changes occurred in the remaining cerebral vascular territories after surgery.CONCLUSIONSASL-based quantitative CBF showed improved cerebral perfusion to the middle cerebral artery territory after revascularization in children with both moyamoya syndrome and disease. Reduced perfusion to the basal ganglia might reflect pruning of the lenticulostriate collaterals, potentially from effects of revascularization. ASL can quantitatively evaluate hemodynamic changes in children with moyamoya after revascularization, and it may be a useful adjunct to routine clinical MRI surveillance.

View details for PubMedID 30738390

Abstract

Despite evidence for macrostructural alteration in epilepsy patients later in life, little is known about the underlying pathological or compensatory mechanisms at younger ages causing these alterations. The aim of this work was to investigate the impact of pediatric epilepsy on the central nervous system, including gray matter volume, cerebral blood flow, and water diffusion, compared with neurologically normal children.Inter-ictal magnetic resonance imaging data was obtained from 30 children with epilepsy ages 1-16 (73% F, 27% M). An atlas-based approach was used to determine values for volume, cerebral blood flow, and apparent diffusion coefficient in the cerebral cortex, hippocampus, thalamus, caudate, putamen, globus pallidus, amygdala, and nucleus accumbens. These values were then compared with previously published values from 100 neurologically normal children using a MANCOVA analysis.Most brain volumes of children with epilepsy followed a pattern similar to typically developing children, except for significantly larger putamen and amygdala. Cerebral blood flow was also comparable between the groups, except for the putamen, which demonstrated decreased blood flow in children with epilepsy. Diffusion (apparent diffusion coefficient) showed a trend towards higher values in children with epilepsy, with significantly elevated diffusion within the thalamus in children with epilepsy compared with neurologically normal children.Children with epilepsy show statistically significant differences in volume, diffusion, and cerebral blood flow within their thalamus, putamen, and amygdala, suggesting that epilepsy is associated with structural changes of the central nervous system influencing brain development and potentially leading to poorer neurocognitive outcomes.

View details for DOI 10.1007/s00234-019-02332-8

View details for PubMedID 31853588

Abstract

Children with Langerhans cell histiocytosis (LCH) may develop a wide array of neurological symptoms, but associated cerebral physiologic changes are poorly understood. We examined cerebral hemodynamic properties of pediatric LCH using arterial spin-labeling (ASL) perfusion magnetic resonance imaging (MRI).A retrospective study was performed in 23 children with biopsy-proven LCH. Analysis was performed on routine brain MRI obtained before or after therapy. Region of interest (ROI) methodology was used to determine ASL cerebral blood flow (CBF) (mL/100g/min) in the following bilateral regions: angular gyrus, anterior prefrontal cortex, orbitofrontal cortex, dorsal anterior cingulate cortex, and hippocampus. Quantile (median) regression was performed for each ROI location. CBF patterns were compared between pre- and posttreatment LCH patients as well as with age-matched healthy controls.Significantly reduced CBF was seen in posttreatment children with LCH compared to age-matched controls in angular gyrus (P=.046), anterior prefrontal cortex (P=.039), and dorsal anterior cingulate cortex (P=.023). Further analysis revealed dominant perfusion abnormalities in the right hemisphere. No significant perfusion differences were observed in the hippocampus or orbitofrontal cortex.Perfusion in specific cerebral regions may be consistently reduced in children with LCH, and may represent effects of underlying disease physiology and/or sequelae of chemotherapy. Studies that combine a formal cognitive assessment and hemodynamic data may further provide insight into perfusion deficits associated with the disease and the potential neurotoxic effects in children treated by chemotherapy.

View details for DOI 10.1002/pbc.28104

View details for PubMedID 31802628

Abstract

We propose a statistical multiscale mapping approach to identify microscopic and molecular heterogeneity across a tumor microenvironment using multiparametric MR (mp-MR). Twenty-nine patients underwent pre-surgical mp-MR followed by MR-guided stereotactic core biopsy. The locations of the biopsy cores were identified in the pre-surgical images using stereotactic bitmaps acquired during surgery. Feature matrices mapped the multiparametric voxel values in the vicinity of the biopsy cores to the pathologic outcome variables for each patient and logistic regression tested the individual and collective predictive power of the MR contrasts. A non-parametric weighted k-nearest neighbor classifier evaluated the feature matrices in a leave-one-out cross validation design across patients. Resulting class membership probabilities were converted to chi-square statistics to develop full-brain parametric maps, implementing Gaussian random field theory to estimate inter-voxel dependencies. Corrections for family-wise error rates were performed using Benjamini-Hochberg and random field theory, and the resulting accuracies were compared. The combination of all five image contrasts correlated with outcome (P<10-4) for all four microscopic variables. The probabilistic mapping method using Benjamini-Hochberg generated statistically significant results (0.05) for three of the four dependent variables: (1) IDH1, (2) MGMT, and (3) microvascular proliferation, with an average classification accuracy of 0.9840.02 and an average classification sensitivity of 1.567%0.967. The images corrected by random field theory demonstrated improved classification accuracy (0.9890.008) and classification sensitivity (5.967%2.857) compared with Benjamini-Hochberg. Microscopic and molecular tumor properties can be assessed with statistical confidence across the brain from minimally-invasive, mp-MR.

View details for DOI 10.1038/s41598-019-53256-5

View details for PubMedID 31745125

Abstract

Completion corpus callosotomy can offer further remission from disabling seizures when a prior partial corpus callosotomy has failed and residual callosal tissue is identified on imaging. Traditional microsurgical approaches to section residual fibers carry risks associated with multiple craniotomies and the proximity to the medially oriented motor cortices. Laser interstitial thermal therapy (LITT) represents a minimally invasive approach for the ablation of residual fibers following a prior partial corpus callosotomy. Here, the authors report clinical outcomes of 6 patients undergoing LITT for completion corpus callosotomy and characterize the radiological effects of ablation.A retrospective clinical review was performed on a series of 6 patients who underwent LITT completion corpus callosotomy for medically intractable epilepsy at Stanford University Medical Center and Lucile Packard Children's Hospital at Stanford between January 2015 and January 2018. Detailed structural and diffusion-weighted MR images were obtained prior to and at multiple time points after LITT. In 4 patients who underwent diffusion tensor imaging (DTI), streamline tractography was used to reconstruct and evaluate tract projections crossing the anterior (genu and rostrum) and posterior (splenium) parts of the corpus callosum. Multiple diffusion parameters were evaluated at baseline and at each follow-up.Three pediatric (age 8-18 years) and 3 adult patients (age 30-40 years) who underwent completion corpus callosotomy by LITT were identified. Mean length of follow-up postoperatively was 21.2 (range 12-34) months. Two patients had residual splenium, rostrum, and genu of the corpus callosum, while 4 patients had residual splenium only. Postoperative complications included asymptomatic extension of ablation into the left thalamus and transient disconnection syndrome. Ablation of the targeted area was confirmed on immediate postoperative diffusion-weighted MRI in all patients. Engel class I-II outcomes were achieved in 3 adult patients, whereas all 3 pediatric patients had Engel class III-IV outcomes. Tractography in 2 adult and 2 pediatric patients revealed time-dependent reduction of fractional anisotropy after LITT.LITT is a safe, minimally invasive approach for completion corpus callosotomy. Engel outcomes for completion corpus callosotomy by LITT were similar to reported outcomes of open completion callosotomy, with seizure reduction primarily observed in adult patients. Serial DTI can be used to assess the presence of tract projections over time but does not classify treatment responders or nonresponders.

View details for DOI 10.3171/2019.5.PEDS19117

View details for PubMedID 31374542

Abstract

Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, background phase removal and solving an ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution. The resulting susceptibility map is known to suffer from inaccuracy near the edges of the brain tissues, in part due to imperfect brain extraction, edge erosion of the brain tissue and the lack of phase measurement outside the brain. This inaccuracy has thus hindered the application of QSM for measuring susceptibility of tissues near the brain edges, e.g., quantifying cortical layers and generating superficial venography. To address these challenges, we propose a learning-based QSM reconstruction method that directly estimates the magnetic susceptibility from total phase images without the need for brain extraction and background phase removal, referred to as autoQSM. The neural network has a modified U-net structure and is trained using QSM maps computed by a two-step QSM method. 209 healthy subjects with ages ranging from 11 to 82 years were employed for patch-wise network training. The network was validated on data dissimilar to the training data, e.g., in vivo mouse brain data and brains with lesions, which suggests that the network generalized and learned the underlying mathematical relationship between magnetic field perturbation and magnetic susceptibility. Quantitative and qualitative comparisons were performed between autoQSM and other two-step QSM methods. AutoQSM was able to recover magnetic susceptibility of anatomical structures near the edges of the brain including the veins covering the cortical surface, spinal cord and nerve tracts near the mouse brain boundaries. The advantages of high-quality maps, no need for brain volume extraction, and high reconstruction speed demonstrate autoQSM's potential for future applications.

View details for DOI 10.1016/j.neuroimage.2019.116064

View details for PubMedID 31377323

Abstract

Posterior fossa syndrome (PFS) is a common complication following the resection of posterior fossa tumors in children. The pathophysiology of PFS remains incompletely elucidated; however, the wide-ranging symptoms of PFS suggest the possibility of widespread cortical dysfunction. In this study, the authors utilized arterial spin labeling (ASL), an MR perfusion modality that provides quantitative measurements of cerebral blood flow without the use of intravenous contrast, to assess cortical blood flow in patients with PFS.A database of medulloblastoma treated at the authors' institution from 2004 to 2016 was retrospectively reviewed, and 14 patients with PFS were identified. Immediate postoperative ASL for patients with PFS and medulloblastoma patients who did not develop PFS were compared. Additionally, in patients with PFS, ASL following the return of speech was compared with immediate postoperative ASL.On immediate postoperative ASL, patients who subsequently developed PFS had statistically significant decreases in right frontal lobe perfusion and a trend toward decreased perfusion in the left frontal lobe compared with controls. Patients with PFS had statistically significant increases in bilateral frontal lobe perfusion after the resolution of symptoms compared with their immediate postoperative imaging findings.ASL perfusion imaging identifies decreased frontal lobe blood flow as a strong physiological correlate of PFS that is consistent with the symptomatology of PFS. This is the first study to demonstrate that decreases in frontal lobe perfusion are present in the immediate postoperative period and resolve with the resolution of symptoms, suggesting a physiological explanation for the transient symptoms of PFS.

View details for DOI 10.3171/2019.5.PEDS18452

View details for PubMedID 31374541

Abstract

Children with intracranial arteriovenous malformations (AVMs) undergo digital DSA for lesion surveillance following their initial diagnosis. However, DSA carries risks of radiation exposure, particularly for the growing pediatric brain and over lifetime. The authors evaluated whether MRI enhanced with a blood pool ferumoxytol (Fe) contrast agent (Fe-MRI) can be used for surveillance of residual or recurrent AVMs.A retrospective cohort was assembled of children with an established AVM diagnosis who underwent surveillance by both DSA and 3-T Fe-MRI from 2014 to 2016. Two neuroradiologists blinded to the DSA results independently assessed Fe-enhanced T1-weighted spoiled gradient recalled acquisition in steady state (Fe-SPGR) scans and, if available, arterial spin labeling (ASL) perfusion scans for residual or recurrent AVMs. Diagnostic confidence was examined using a Likert scale. Sensitivity, specificity, and intermodality reliability were determined using DSA studies as the gold standard. Radiation exposure related to DSA was calculated as total dose area product (TDAP) and effective dose.Fifteen patients were included in this study (mean age 10 years, range 3-15 years). The mean time between the first surveillance DSA and Fe-MRI studies was 17 days (SD 47). Intermodality agreement was excellent between Fe-SPGR and DSA ( = 1.00) but poor between ASL and DSA ( = 0.53; 95% CI 0.18-0.89). The sensitivity and specificity for detecting residual AVMs using Fe-SPGR were 100% and 100%, and using ASL they were 72% and 100%, respectively. Radiologists reported overall high diagnostic confidence using Fe-SPGR. On average, patients received two surveillance DSA studies over the study period, which on average equated to a TDAP of 117.2 Gycm2 (95% CI 77.2-157.4 Gycm2) and an effective dose of 7.8 mSv (95% CI 4.4-8.8 mSv).Fe-MRI performed similarly to DSA for the surveillance of residual AVMs. Future multicenter studies could further investigate the efficacy of Fe-MRI as a noninvasive alternative to DSA for monitoring AVMs in children.

View details for DOI 10.3171/2019.5.PEDS1957

View details for PubMedID 31323627

Abstract

Deep learning has the potential to augment clinician performance in medical imaging interpretation and reduce time to diagnosis through automated segmentation. Few studies to date have explored this topic.To develop and apply a neural network segmentation model (the HeadXNet model) capable of generating precise voxel-by-voxel predictions of intracranial aneurysms on head computed tomographic angiography (CTA) imaging to augment clinicians' intracranial aneurysm diagnostic performance.In this diagnostic study, a 3-dimensional convolutional neural network architecture was developed using a training set of 611 head CTA examinations to generate aneurysm segmentations. Segmentation outputs from this support model on a test set of 115 examinations were provided to clinicians. Between August 13, 2018, and October 4, 2018, 8 clinicians diagnosed the presence of aneurysm on the test set, both with and without model augmentation, in a crossover design using randomized order and a 14-day washout period. Head and neck examinations performed between January 3, 2003, and May 31, 2017, at a single academic medical center were used to train, validate, and test the model. Examinations positive for aneurysm had at least 1 clinically significant, nonruptured intracranial aneurysm. Examinations with hemorrhage, ruptured aneurysm, posttraumatic or infectious pseudoaneurysm, arteriovenous malformation, surgical clips, coils, catheters, or other surgical hardware were excluded. All other CTA examinations were considered controls.Sensitivity, specificity, accuracy, time, and interrater agreement were measured. Metrics for clinician performance with and without model augmentation were compared.The data set contained 818 examinations from 662 unique patients with 328 CTA examinations (40.1%) containing at least 1 intracranial aneurysm and 490 examinations (59.9%) without intracranial aneurysms. The 8 clinicians reading the test set ranged in experience from 2 to 12 years. Augmenting clinicians with artificial intelligence-produced segmentation predictions resulted in clinicians achieving statistically significant improvements in sensitivity, accuracy, and interrater agreement when compared with no augmentation. The clinicians' mean sensitivity increased by 0.059 (95% CI, 0.028-0.091; adjusted P=.01), mean accuracy increased by 0.038 (95% CI, 0.014-0.062; adjusted P=.02), and mean interrater agreement (Fleiss ) increased by 0.060, from 0.799 to 0.859 (adjusted P=.05). There was no statistically significant change in mean specificity (0.016; 95% CI, -0.010 to 0.041; adjusted P=.16) and time to diagnosis (5.71 seconds; 95% CI, 7.22-18.63 seconds; adjusted P=.19).The deep learning model developed successfully detected clinically significant intracranial aneurysms on CTA. This suggests that integration of an artificial intelligence-assisted diagnostic model may augment clinician performance with dependable and accurate predictions and thereby optimize patient care.

View details for DOI 10.1001/jamanetworkopen.2019.5600

View details for PubMedID 31173130

View details for DOI 10.1148/radiol.2018181204

View details for Web of Science ID 000453784400037

Abstract

Currently, there are an estimated 400,000 long-term survivors of childhood cancer in the United States. Chronic leukoencephalopathy is a potential devastating late effect that can manifest as a range of neurological and neurocognitive sequelae. Survivors of the acute lymphocytic leukemia, central nervous system tumors, and stem cell transplant have frequently been exposed to cranial radiation, systemic and intrathecal chemotherapy, which places them at risk of developing chronic leukoencephalopathy. Defining leukoencephalopathy and its neuroimaging characteristics, the population of survivors at risk, its long-term consequences, and identifying prevention and intervention strategies can potentially mitigate the morbidity of these survivors. Better understanding of those at risk of leukoencephalopathy and its symptoms can lead to an improved quality of life for these cancer survivors.

View details for PubMedID 31047756

View details for DOI 10.1002/mrm.27236

View details for Web of Science ID 000450220400021

Abstract

Advanced neuroimaging and computational methods offer opportunities for more accurate prognosis. We hypothesized that near-term regional white matter (WM) microstructure, assessed on diffusion tensor imaging (DTI), using exhaustive feature selection with cross-validation would predict neurodevelopment in preterm children.Near-term MRI and DTI obtained at 36.61.8weeks postmenstrual age in 66 very-low-birth-weight preterm neonates were assessed. 60/66 had follow-up neurodevelopmental evaluation with Bayley Scales of Infant-Toddler Development, 3rd-edition (BSID-III) at 18-22months. Linear models with exhaustive feature selection and leave-one-out cross-validation computed based on DTI identified sets of three brain regions most predictive of cognitive and motor function; logistic regression models were computed to classify high-risk infants scoring one standard deviation below mean.Cognitive impairment was predicted (100% sensitivity, 100% specificity; AUC=1) by near-term right middle-temporal gyrus MD, right cingulate-cingulum MD, left caudate MD. Motor impairment was predicted (90% sensitivity, 86% specificity; AUC=0.912) by left precuneus FA, right superior occipital gyrus MD, right hippocampus FA. Cognitive score variance was explained (29.6%, cross-validated R2=0.296) by left posterior-limb-of-internal-capsule MD, Genu RD, right fusiform gyrus AD. Motor score variance was explained (31.7%, cross-validated R2=0.317) by left posterior-limb-of-internal-capsule MD, right parahippocampal gyrus AD, right middle-temporal gyrus AD.Search in large DTI feature space more accurately identified neonatal neuroimaging correlates of neurodevelopment.

View details for DOI 10.1016/j.nicl.2017.11.023

View details for PubMedID 29234600

View details for PubMedCentralID PMC5722472

Abstract

OBJECT: Current standard of care for children with infratentorial ependymoma includes maximal safe resection and local radiation of 54-59gy. High-dose local radiation has been associated with declines in multiple cognitive domains. The anatomic and physiologic correlates of this cognitive decline remain undefined and there have been no radiographic studies on the long-term effects of this treatment paradigm.METHODS: A comprehensive database of pediatric brain tumor patients treated at Stanford Children's from 2004-2016 was queried. Seven patients with posterior fossa ependymoma were identified who were treated with surgery and local radiation alone, who had no evidence of recurrent disease, and had imaging suitable for analysis. Diffusion-weighted MRI (DWI) datasets were used to calculate apparent diffusion coefficient (ADC) maps for each subject, while arterial spin labeling (ASL) datasets were used to calculated maps of cerebral blood flow (CBF). DWI and ASL datasets of 52 age-matched healthy children were a analyzed in the same fashion to enable group comparisons.RESULTS: Several statistically significant differences were detected between the two groups. CBF was lower in the caudate and pallidum and higher in the nucleus accumbens in the ependymoma cohort compared to controls. ADC was increased in the thalamus and trended towards decreased in the amygdala.CONCLUSIONS: Surgery and local radiation for posterior fossa ependymoma are associated with supratentorial ADC and CBF alterations, which may represent an anatomic and physiologic correlate to the previously published decline in neurocognitive outcomes in this population.

View details for PubMedID 30448581

Abstract

BACKGROUND: Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect millions of people worldwide each year. This time-consuming task typically requires expert radiologists to read the images, leading to fatigue-based diagnostic error and lack of diagnostic expertise in areas of the world where radiologists are not available. Recently, deep learning approaches have been able to achieve expert-level performance in medical image interpretation tasks, powered by large network architectures and fueled by the emergence of large labeled datasets. The purpose of this study is to investigate the performance of a deep learning algorithm on the detection of pathologies in chest radiographs compared with practicing radiologists.METHODS AND FINDINGS: We developed CheXNeXt, a convolutional neural network to concurrently detect the presence of 14 different pathologies, including pneumonia, pleural effusion, pulmonary masses, and nodules in frontal-view chest radiographs. CheXNeXt was trained and internally validated on the ChestX-ray8 dataset, with a held-out validation set consisting of 420 images, sampled to contain at least 50 cases of each of the original pathology labels. On this validation set, the majority vote of a panel of 3 board-certified cardiothoracic specialist radiologists served as reference standard. We compared CheXNeXt's discriminative performance on the validation set to the performance of 9 radiologists using the area under the receiver operating characteristic curve (AUC). The radiologists included 6 board-certified radiologists (average experience 12 years, range 4-28 years) and 3 senior radiology residents, from 3 academic institutions. We found that CheXNeXt achieved radiologist-level performance on 11 pathologies and did not achieve radiologist-level performance on 3 pathologies. The radiologists achieved statistically significantly higher AUC performance on cardiomegaly, emphysema, and hiatal hernia, with AUCs of 0.888 (95% confidence interval [CI] 0.863-0.910), 0.911 (95% CI 0.866-0.947), and 0.985 (95% CI 0.974-0.991), respectively, whereas CheXNeXt's AUCs were 0.831 (95% CI 0.790-0.870), 0.704 (95% CI 0.567-0.833), and 0.851 (95% CI 0.785-0.909), respectively. CheXNeXt performed better than radiologists in detecting atelectasis, with an AUC of 0.862 (95% CI 0.825-0.895), statistically significantly higher than radiologists' AUC of 0.808 (95% CI 0.777-0.838); there were no statistically significant differences in AUCs for the other 10 pathologies. The average time to interpret the 420 images in the validation set was substantially longer for the radiologists (240 minutes) than for CheXNeXt (1.5 minutes). The main limitations of our study are that neither CheXNeXt nor the radiologists were permitted to use patient history or review prior examinations and that evaluation was limited to a dataset from a single institution.CONCLUSIONS: In this study, we developed and validated a deep learning algorithm that classified clinically important abnormalities in chest radiographs at a performance level comparable to practicing radiologists. Once tested prospectively in clinical settings, the algorithm could have the potential to expand patient access to chest radiograph diagnostics.

View details for PubMedID 30457988

View details for DOI 10.1371/journal.pmed.1002699

View details for Web of Science ID 000451827800015

View details for DOI 10.3171/2018.3.PEDS17723

View details for Web of Science ID 000443304500007

Abstract

OBJECTIVE Fast magnetic resonance imaging (fsMRI) sequences are single-shot spin echo images with fast acquisition times that have replaced CT scans for many conditions. Introduced as a means of evaluating children with hydrocephalus and macrocephaly, these sequences reduce the need for anesthesia and can be more cost-effective, especially for children who require multiple surveillance scans. However, the role of fsMRI has yet to be investigated in evaluating the posterior fossa in patients with Chiari I abnormality (CM-I). The goal of this study was to examine the diagnostic performance of fsMRI in evaluating the cerebellar tonsils in comparison to conventional MRI. METHODS The authors performed a retrospective analysis of 18 pediatric patients with a confirmed diagnosis of CM-I based on gold-standard conventional brain MRI and 30 controls without CM-I who had presented with various neurosurgical conditions. The CM-I patients were included if fsMRI studies had been obtained within 1 year of conventional MRI with no surgical intervention between the studies. Two neuroradiologists reviewed the studies in a blinded fashion to determine the diagnostic performance of fsMRI in detecting CM-I. For the CM-I cohort, the fsMRI and T2-weighted MRI exams were randomized, and the blinded reviewers performed tonsillar measurements on both scans. RESULTS The mean age of the CM-I cohort was 7.39 years, and 50% of these subjects were male. The mean time interval between fsMRI and conventional T2-weighted MRI was 97.8 days. Forty-four percent of the subjects had undergone imaging after posterior fossa decompression. The sensitivity and specificity of fsMRI in detecting CM-I was 100% (95% CI 71.51%-100%) and 92.11% (95% CI 78.62%-98.34%), respectively. If only preoperative patients are considered, both sensitivity and specificity increase to 100%. The authors also performed a cost analysis and determined that fsMRI was significantly cost-effective compared to T2-weighted MRI or CT. CONCLUSIONS Despite known limitations, fsMRI may serve as a useful diagnostic and surveillance tool for CM-I. It is more cost-effective than full conventional brain MRI and decreases the need for sedation in young children.

View details for PubMedID 29749883

View details for DOI 10.1016/j.wneu.2018.05.210

View details for Web of Science ID 000439498500151

Abstract

OBJECT: The need for neurosurgical supervision as well as the general safety and utility of dynamic MRI of the cervical spine in children remains controversial. We present the largest descriptive cohort study of cervical flexion-extension MRIs in a pediatric population to help elucidate the safety and utility of this technique.METHODS: All cervical spine MRIs performed at Lucile Packard Children's Hospital at Stanford from 2009-2015 were retrospectively reviewed. Sixty-six dynamic cervical MRIs performed in 45 children and two young adults were identified for further study.RESULTS: Forty-three scans were imaged under general anesthesia. All imaging was performed by the neuroradiology team with no direct supervision by the neurosurgery team. There were no adverse events. Dynamic MRI detected significant instability that was not clearly seen on dynamic radiographs (5 patients) as well as cord compression not seen on static MR scans (9 patients). One patient with asymptomatic instability found on flexion-extension radiographs had no cord compression with movement on MRI and was managed conservatively. Two neonates with significant congenital malformations of the cervical spine were cleared for OR positioning for cardiac procedures based on flexion-extension MR imaging.CONCLUSIONS: Dynamic MRI represents a safe and useful tool for evaluating the cervical spine and cervicomedullary junction in a variety of pediatric patient populations and can be performed safely without direct neurosurgical supervision. Additionally, we describe for the first time the use of flexion-extension MRI to clear neonates with severe congenital cervical spine abnormalities for complex operative positioning and ICU care.

View details for PubMedID 29883828

Abstract

PURPOSE: Amplified magnetic resonance imaging (aMRI) was recently introduced as a new brain motion detection and visualization method. The original aMRI approach used a video-processing algorithm, Eulerian video magnification (EVM), to amplify cardio-ballistic motion in retrospectively cardiac-gated MRI data. Here, we strive to improve aMRI by incorporating a phase-based motion amplification algorithm.METHODS: Phase-based aMRI was developed and tested for correct implementation and ability to amplify sub-voxel motions using digital phantom simulations. The image quality of phase-based aMRI was compared with EVM-based aMRI in healthy volunteers at 3T, and its amplified motion characteristics were compared with phase-contrast MRI. Data were also acquired on a patient with Chiari I malformation, and qualitative displacement maps were produced using free form deformation (FFD) of the aMRI output.RESULTS: Phantom simulations showed that phase-based aMRI has a linear dependence of amplified displacement on true displacement. Amplification was independent of temporal frequency, varying phantom intensity, Rician noise, and partial volume effect. Phase-based aMRI supported larger amplification factors than EVM-based aMRI and was less sensitive to noise and artifacts. Abnormal biomechanics were seen on FFD maps of the Chiari I malformation patient.CONCLUSION: Phase-based aMRI might be used in the future for quantitative analysis of minute changes in brain motion and may reveal subtle physiological variations of the brain as a result of pathology using processing of the fundamental harmonic or by selectively varying temporal harmonics. Preliminary data shows the potential of phase-based aMRI to qualitatively assess abnormal biomechanics in Chiari I malformation.

View details for PubMedID 29845645

Abstract

Tension-type and migraine-type headaches are the most common chronic paroxysmal disorders of childhood. The goal of this study was to compare regional cerebral volumes and diffusion in tension-type and migraine-type headaches against published controls.Patients evaluated for tension-type or migraine-type headache without aura from May 2014 to July 2016 in a single center were retrospectively reviewed. Thirty-two patients with tension-type headache and 23 with migraine-type headache at an average of 4 months after diagnosis were enrolled. All patients underwent DWI at 3T before the start of pharmacotherapy. Using atlas-based DWI analysis, we determined regional volumetric and diffusion properties in the cerebral cortex, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens, brain stem, and cerebral white matter. Multivariate analysis of covariance was used to test for differences between controls and patients with tension-type and migraine-type headaches.There were no significant differences in regional brain volumes between the groups. Patients with tension-type and migraine-type headaches showed significantly increased ADC in the hippocampus and brain stem compared with controls. Additionally, only patients with migraine-type headache showed significantly increased ADC in the thalamus and a trend toward increased ADC in the amygdala compared with controls.This study identifies early cerebral diffusion changes in patients with tension-type and migraine-type headaches compared with controls. The hypothesized mechanisms of nociception in migraine-type and tension-type headaches may explain the findings as a precursor to structural changes seen in adult patients with chronic headache.

View details for PubMedID 29545251

Abstract

Optogenetic tools have opened a rich experimental landscape for understanding neural function and disease. Here, we present the first validation of eight optogenetic constructs driven by recombinant adeno-associated virus (AAV) vectors and a WGA-Cre based dual injection strategy for projection targeting in a widely-used New World primate model, the common squirrel monkey Saimiri sciureus. We observed opsin expression around the local injection site and in axonal projections to downstream regions, as well as transduction to thalamic neurons, resembling expression patterns observed in macaques. Optical stimulation drove strong, reliable excitatory responses in local neural populations for two depolarizing opsins in anesthetized monkeys. Finally, we observed continued, healthy opsin expression for at least one year. These data suggest that optogenetic tools can be readily applied in squirrel monkeys, an important first step in enabling precise, targeted manipulation of neural circuits in these highly trainable, cognitively sophisticated animals. In conjunction with similar approaches in macaques and marmosets, optogenetic manipulation of neural circuits in squirrel monkeys will provide functional, comparative insights into neural circuits which subserve dextrous motor control as well as other adaptive behaviors across the primate lineage. Additionally, development of these tools in squirrel monkeys, a well-established model system for several human neurological diseases, can aid in identifying novel treatment strategies.

View details for PubMedID 29712920

Abstract

Diffusion imaging coupled with tractography algorithms allows researchers to image human white matter fiber bundles in-vivo. These bundles are three-dimensional structures with shapes that change over time during the course of development as well as in pathologic states. While most studies on white matter variability focus on analysis of tissue properties estimated from the diffusion data, e.g. fractional anisotropy, the shape variability of white matter fiber bundle is much less explored. In this paper, we present a set of tools for shape analysis of white matter fiber bundles, namely: (1) a concise geometric model of bundle shapes; (2) a method for bundle registration between subjects; (3) a method for deformation estimation. Our framework is useful for analysis of shape variability in white matter fiber bundles. We demonstrate our framework by applying our methods on two datasets: one consisting of data for 6 normal adults and another consisting of data for 38 normal children of age 11 days to 8.5 years. We suggest a robust and reproducible method to measure changes in the shape of white matter fiber bundles. We demonstrate how this method can be used to create a model to assess age-dependent changes in the shape of specific fiber bundles. We derive such models for an ensemble of white matter fiber bundles on our pediatric dataset and show that our results agree with normative human head and brain growth data. Creating these models for a large pediatric longitudinal dataset may improve understanding of both normal development and pathologic states and propose novel parameters for the examination of the pediatric brain.

View details for PubMedID 29203454

View details for PubMedCentralID PMC5845796

Abstract

New MRI sequences based on rapid radial acquisition have reduced gradient noise. The purpose of this study was to compare Silent T1-weighted and unenhanced MR angiography (MRA) against conventional sequences in a clinical population.The study cohort consisted of 40 patients with suspected brain metastases (median age, 60 years; range, 23-91 years) who underwent T1-weighted contrast-enhanced MRI and 51 patients with suspected vascular lesions or cerebral ischemia (median age, 60 years; range, 16-94 years) who underwent unenhanced intracranial MRA. Three neuroradiologists reviewed the images blindly and rated several measures of image quality on a 5-point Likert scale. Reviewers recorded the number of enhancing lesions and whether Silent images were better than, worse than, or equivalent to conventional images.For T1-weighted MR images, ratings were slightly lower for Silent versus conventional images, except for diagnostic confidence. Although more lesions were detected on conventional images, this difference was not statistically significant; agreement was seen in 88% of cases. In 48% of cases, T1-weighted scans were deemed equivalent, but when a preference existed, it was usually for conventional images (38% vs 14%). Conventional MRA images were rated higher on all image quality metrics and were strongly preferred (reviewers preferred conventional images in 69% of cases, rated the images as equivalent in 27% of cases, and preferred Silent images in 4% of cases). In some cases, artifacts on Silent images caused reduced vessel caliber, vessel irregularities, and even absent vessels.Although conventional T1-weighted images were preferred overall, most Silent T1-weighted images were rated as equivalent to or better than conventional images and represent a potential alternative for imaging of noise-averse patients. Silent MRA scored significantly worse and could not be recommended at this time, suggesting that it requires additional refinement before routine clinical use.

View details for PubMedID 29112472

Abstract

Unilateral anterior plagiocephaly is most commonly the result of deformational plagiocephaly or unilateral coronal synostosis, a premature fusion of the frontoparietal suture. However, other sutures within the coronal ring have been implicated in producing anterior cranial asymmetries. These fusions can occur in isolation or in concert with adjacent sutures. The frontosphenoidal suture is one such suture within the coronal ring that has been involved both concomitantly with and independently of frontoparietal suture fusion. Although isolated frontosphenoidal synostosis has been presented previously in the literature, these reports include patients with fusion of the extraorbital portion of the frontosphenoidal suture. This clinical report presents the first clearly documented patient of isolated frontosphenoidal synostosis that occurs entirely within the intraorbital region.The patient presented to Plastic Surgery Clinic at 3 months of age with left frontal flattening, supraorbital rim retrusion, and temporal bulging that was noted soon after birth. Computed tomography analysis revealed an isolated fusion of the greater and lesser wings of the sphenoid bone to the frontal bone on the left side. The patient had no family history of cranial anomalies and genetic testing was negative for mutations. The infant was treated with a cranial orthotic for 3 months, underwent open fronto-orbital advancement and cranial vault remodeling at 6 months, and continued wearing a cranial orthotic for another 4.5 months. Following surgical and orthotic treatment, the patient achieved a satisfactory result.

View details for DOI 10.1097/SCS.0000000000004074

View details for PubMedID 29068968

Abstract

Purpose To investigate ferumoxytol-enhanced MRI as a noninvasive imaging biomarker of macrophages in adults with high-grade gliomas. Materials and Methods In this prospective study, adults with high-grade gliomas were enrolled between July 2015 and July 2017. Each participant was administered intravenous ferumoxytol (5 mg/kg) and underwent 3.0-T MRI 24 hours later. Two sites in each tumor were selected for intraoperative sampling on the basis of the degree of ferumoxytol-induced signal change. Susceptibility and the relaxation rates R2* (1/T2*) and R2 (1/T2) were obtained by region-of-interest analysis by using the respective postprocessed maps. Each sample was stained with Prussian blue, CD68, CD163, and glial fibrillary acidic protein. Pearson correlation and linear mixed models were performed to assess the relationship between imaging measurements and number of 400 magnification high-power fields with iron-containing macrophages. Results Ten adults (four male participants [mean age, 65 years 9 {standard deviation}; age range, 57-74 years] and six female participants [mean age, 53 years 12 years; age range, 32-65 years]; mean age of all participants, 58 years 12 [age range, 32-74 years]) with high-grade gliomas were included. Significant positive correlations were found between susceptibility, R2*, and R2' and the number of high-power fields with CD163-positive (r range, 0.64-0.71; P < .01) and CD68-positive (r range, 0.55-0.57; P value range, .01-.02) iron-containing macrophages. No significant correlation was found between R2 and CD163-positive (r = 0.33; P = .16) and CD68-positive (r = 0.24; P = .32) iron-containing macrophages. Similar significance results were obtained with linear mixed models. At histopathologic analysis, iron particles were found only in macrophages; none was found in glial fibrillary acidic protein-positive tumor cells. Conclusion MRI measurements of susceptibility, R2*, and R2' (R2* - R2) obtained after ferumoxytol administration correlate with iron-containing macrophage concentration, and this shows their potential as quantitative imaging markers of macrophages in malignant gliomas. RSNA, 2018 Online supplemental material is available for this article.

View details for PubMedID 30398435

Abstract

OBJECTIVE Patients with brain arteriovenous malformations (AVMs) often require repeat imaging with MRI or MR angiography (MRA), CT angiography (CTA), and digital subtraction angiography (DSA). The ideal imaging modality provides excellent vascular visualization without incurring added risks, such as radiation exposure. The purpose of this study is to evaluate the performance of ferumoxytol-enhanced MRA using a high-resolution 3D volumetric sequence (fe-SPGR) for visualizing and grading pediatric brain AVMs in comparison with CTA and DSA, which is the current imaging gold standard. METHODS In this retrospective cohort study, 21 patients with AVMs evaluated by fe-SPGR, CTA, and DSA between April 2014 and August 2017 were included. Two experienced raters graded AVMs using Spetzler-Martin criteria on all imaging studies. Lesion conspicuity (LC) and diagnostic confidence (DC) were assessed using a 5-point Likert scale, and interrater agreement was determined. The Kruskal-Wallis test was performed to assess the raters' grades and scores of LC and DC, with subsequent post hoc pairwise comparisons to assess for statistically significant differences between pairs of groups at p < 0.05. RESULTS Assigned Spetzler-Martin grades for AVMs on DSA, fe-SPGR, and CTA were not significantly different (p = 0.991). LC and DC scores were higher with fe-SPGR than with CTA (p < 0.05). A significant difference in LC scores was found between CTA and fe-SPGR (p < 0.001) and CTA and DSA (p < 0.001) but not between fe-SPGR and DSA (p = 0.146). A significant difference in DC scores was found among DSA, fe-SPGR, and CTA (p < 0.001) and between all pairs of the groups (p < 0.05). Interrater agreement was good to very good for all image groups ( = 0.77-1.0, p < 0.001). CONCLUSIONS Fe-SPGR performed robustly in the diagnostic evaluation of brain AVMs, with improved visual depiction of AVMs compared with CTA and comparable Spetzler-Martin grading relative to CTA and DSA.

View details for PubMedID 29882734

Abstract

Intracranial arteriopathies are frequent causes of pediatric stroke and important risk factors for stroke recurrence. Without tissue diagnosis, vascular imaging is relied upon to identify the underlying etiology and prognosis. We hypothesized that children with unilateral intracranial arteriopathy with lenticulostriate collaterals would demonstrate distinct vascular outcomes compared with children without collaterals.We retrospectively identified children with unilateral intracranial arteriopathy from two institutions. Two blinded raters from each institution reviewed magnetic resonance or digital subtraction angiography at baseline and 12 months. Patients were grouped according to presence or absence of lenticulostriate collaterals. Clinical features and vascular imaging outcomes were compared using univariate analysis and multivariate logistic regression.Forty-four children were included: 22 males, median age 8.2 years (range two to 16.9 years), and further stratified into the collateral group (n=20) and non-collateral group (n=24), with median follow-up of 25.5 months and 23 months, respectively. Both groups demonstrated similar rates of progression on vascular imaging at 12 months, 50% in the collateral group versus 37.5% in the non-collateral group (P>0.05). The collateral group was associated with asymptomatic clinical presentation, normal brain MRI, border zone infarcts, and either vascular stabilization or new contralateral disease. The non-collateral group demonstrated either vascular improvement or discordant progression (combination of improved and progressive lesions). Using a multivariate model, collaterals continued to be an independent predictor of vascular outcome.This study suggests that lenticulostriate collaterals in children with unilateral intracranial arteriopathy may serve as a useful neuroimaging biomarker that helps to stratify patients with distinct clinical features and patterns of vascular evolution.

View details for PubMedID 29174857

View details for DOI 10.21037/tcr.2017.10.15

View details for Web of Science ID 000418881000029

Abstract

Of the 4 medulloblastoma subgroups, Group 3 is the most aggressive but the importance of angiogenesis is unknown. This study sought to determine the role of angiogenesis and identify clinically relevant biomarkers of tumor vascularity and survival in Group 3 medulloblastoma.VEGFA mRNA expression and survival from several patient cohorts were analyzed. Group 3 xenografts were implanted intracranially in nude rats. Dynamic susceptibility weighted (DSC) MRI and susceptibility weighted imaging (SWI) were obtained. DSC MRI was used to calculate relative cerebral blood volume (rCBV) and flow (rCBF). Tumor vessel density and rat vascular endothelial growth factor alpha (VEGFA) expression were determined.Patient VEGFA mRNA levels were significantly elevated in Group 3 compared with the other subgroups (P < 0.001) and associated with survival. Xenografts D283, D341, and D425 were identified as Group 3 by RNA hierarchical clustering and MYC amplification. The D283 group had the lowest rCBV and rCBF, followed by D341 and D425 (P < 0.05). These values corresponded to histological vessel density (P < 0.05), rat VEGFA expression (P < 0.05), and survival (P = 0.002). Gene set enrichment analysis identified 5 putative genes with expression profiles corresponding with these findings: RNH1, SCG2, VEGFA, AGGF1, and PROK2. SWI identified 3 xenograft-independent categories of intratumoral vascular architecture with distinct survival (P = 0.004): organized, diffuse microvascular, and heterogeneous.Angiogenesis plays an important role in Group 3 medulloblastoma pathogenesis and survival. DSC MRI and SWI are clinically relevant biomarkers for tumor vascularity and overall survival and can be used to direct the use of antivascular therapies for patients with Group 3 medulloblastoma.

View details for PubMedID 28379574

Abstract

Medulloblastoma patients are treated with surgery, radiation and chemotherapy. Radiation dose to the temporal lobe may be associated with neurocognitive sequelae. Longitudinal changes of temporal lobe cortical thickness may result from neurodevelopmental processes such as synaptic pruning. This study applies longitudinal image analysis to compare developmental change in cortical thickness in medulloblastoma (MB) patients who were treated by combined modality therapy to that of cerebellar juvenile pilocytic astrocytoma (JPA) patients who were treated by surgery alone. We hypothesized that the rates of developmental change in cortical thickness would differ between these two groups. This retrospective cohort study assessed changes in cortical thickness over time between MB and JPA patients. High-resolution magnetic resonance (MR) images of 14MB and 7JPA subjects were processed to measure cortical thickness of bilateral temporal lobe substructures. A linear mixed effects model was used to identify differences in substructure longitudinal changes in cortical thickness. The left temporal lobe exhibited overall increased cortical thickness in MB patients relative to JPA patients who showed overall cortical thinning (mean annual cortical thickness change: MB 0.14mm/year versus JPA -0.018mm/year across all substructures), particularly in the inferior temporal lobe substructures (p<0.0001). The cortical thickness change of the right temporal lobe substructures exhibited similar, though attenuated trends (p=0.002). MB patients exhibit overall increased cortical thickness rather than cortical thinning as seen in JPA patients and as expected in normal cortical development. These observations are possibly due to chemoradiation induced-disruption of normal neuronal mechanisms. Longitudinal image analysis may identify early biomarkers for neurocognitive function with routine imaging.

View details for DOI 10.1007/s11060-017-2453-5

View details for PubMedID 28534154

Abstract

To compare cerebral perfusion and diffusion in survivors of childhood posterior fossa brain tumor with neurologically normal controls and correlate differences with cognitive dysfunction.We analyzed retrospectively arterial spin-labeled cerebral blood flow (CBF) and apparent diffusion coefficient (ADC) in 21 patients with medulloblastoma (MB), 18 patients with pilocytic astrocytoma (PA), and 64 neurologically normal children. We generated ANCOVA models to evaluate treatment effects on the cerebral cortex, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens, and cerebral white matter at time points an average of 5.7 years after original diagnosis. A retrospective review of patient charts identified 12 patients with neurocognitive data and in whom the relationship between IQ and magnetic resonance imaging variables was assessed for each brain structure.Patients with MB (all treated with surgery, chemotherapy, and radiation) had significantly lower global CBF relative to controls (10%-23% lower, varying by anatomic region, all adjusted P<.05), whereas patients with PA (all treated with surgery alone) had normal CBF. ADC was decreased specifically in the hippocampus and amygdala of patients with MB and within the amygdala of patients with PA but otherwise remained normal after therapy. In the patients with tumor previously evaluated for IQ, regional ADC, but not CBF, correlated with IQ (R(2)=0.33-0.75).The treatment for MB, but not PA, was associated with globally reduced CBF. Treatment in both tumor types was associated with diffusion abnormalities of the mesial temporal lobe structures. Despite significant perfusion abnormalities in patients with MB, diffusion, but not perfusion, correlated with cognitive outcomes.

View details for DOI 10.1016/j.jpeds.2017.01.019

View details for PubMedID 28187964

Abstract

Purpose To develop a positron emission tomography (PET)/magnetic resonance (MR) imaging protocol for evaluation of the brain, heart, and joints of pediatric cancer survivors for chemotherapy-induced injuries in one session. Materials and Methods Three teams of experts in neuroimaging, cardiac imaging, and bone imaging were tasked to develop a 20-30-minute PET/MR imaging protocol for detection of chemotherapy-induced tissue injuries of the brain, heart, and bone. In an institutional review board-approved, HIPAA-compliant, prospective study from April to July 2016, 10 pediatric cancer survivors who completed chemotherapy underwent imaging of the brain, heart, and bone with a 3-T PET/MR imager. Cumulative chemotherapy doses and clinical symptoms were correlated with the severity of MR imaging abnormalities by using linear regression analyses. MR imaging measures of brain perfusion and metabolism were compared among eight patients who were treated with methotrexate and eight untreated age-matched control subjects by using Wilcoxon rank-sum tests. Results Combined brain, heart, and bone examinations were completed within 90 minutes. Eight of 10 cancer survivors had abnormal findings on brain, heart, and bone images, including six patients with and two patients without clinical symptoms. Cumulative chemotherapy doses correlated significantly with MR imaging measures of left ventricular ejection fraction and end-systolic volume, but not with the severity of brain or bone abnormalities. Methotrexate-treated cancer survivors had significantly lower cerebral blood flow and metabolic activity in key brain areas compared with control subjects. Conclusion The feasibility of a single examination for assessment of chemotherapy-induced injuries of the brain, heart, and joints was shown. Earlier detection of tissue injuries may enable initiation of timely interventions and help to preserve long-term health of pediatric cancer survivors. () RSNA, 2017 Online supplemental material is available for this article.

View details for PubMedID 28777701

Abstract

Radiomics describes a broad set of computational methods that extract quantitative features from radiographic images. The resulting features can be used to inform imaging diagnosis, prognosis, and therapy response in oncology. However, major challenges remain for methodologic developments to optimize feature extraction and provide rapid information flow in clinical settings. Equally important, to be clinically useful, predictive radiomic properties must be clearly linked to meaningful biologic characteristics and qualitative imaging properties familiar to radiologists. Here we use a cross-disciplinary approach to highlight studies in radiomics. We review brain tumor radiologic studies (eg, imaging interpretation) through computational models (eg, computer vision and machine learning) that provide novel clinical insights. We outline current quantitative image feature extraction and prediction strategies with different levels of available clinical classes for supporting clinical decision-making. We further discuss machine-learning challenges and data opportunities to advance radiomic studies.

View details for DOI 10.3174/ajnr.A5391

View details for PubMedID 28982791

Abstract

Sclerotherapy is one of the most commonly used minimally invasive interventions in the treatment of macrocystic lymphatic malformations (LMs). Several different sclerosing agents and injection protocols have been reported in the literature, each with varying degrees of success. The safety and efficacy of the treatments have not been evaluated comparatively in the pediatric population.Chart review of pediatric patients with macrocystic/mixed head and neck LMs who underwent sclerotherapy using OK-432, doxycycline, or ethanolamine oleate at Lucile Packard Children's Hospital at Stanford during 2000-2014. Clinical evaluation and radiographic imaging were reviewed to assess lesion characteristics and response to sclerotherapy following each treatment session. The post-intervention clinical response was categorized as excellent, good, fair, or poor.Among the 41 pediatric cases reviewed, 10 patients were treated with OK-432, 19 patients received doxycycline, and 12 patients received ethanolamine. In univariate analysis, different sclerosants had similar effectiveness after the first injection and final clinical outcome (p=0.5317). In multivariate analysis controlling for disease severity stage as well as disease characteristics (macrocystic vs mixed subtypes), different sclerosants also had similar effectiveness after the first injection (p=0.1192). Radiologic analysis indicated an 84.5% average volume reduction, with similar effectiveness between the different sclerosants (p=0.9910).In this series of LM cases treated at Stanford, we found that doxycycline, OK-432, and ethanolamine oleate sclerotherapy appear to have a similar safety and efficacy profile in the treatment of macrocystic and mixed LMs of the head and neck in the pediatric population.

View details for DOI 10.1136/neurintsurg-2016-012660

View details for PubMedID 27707871

Abstract

In contrast to more common nasal and cervical lesions, the frontotemporal pit is a rarely encountered lesion that is often associated with a dermoid and may track intracranially. Due to delays in diagnosis, the propensity to spread intracranially, and the risk of infection, awareness of these lesions and appropriate diagnosis and management are important. The authors present 2 cases of frontotemporal pits from a single institution. Epidemiology, presentation, and management recommendations are discussed.

View details for DOI 10.3171/2016.5.PEDS1687

View details for Web of Science ID 000383938500015

View details for PubMedID 27391653

Abstract

Normal values of gray matter volume, cerebral blood flow, and water diffusion have not been established for healthy children. We sought to determine reference values for age-dependent changes of these parameters in healthy children.We retrospectively reviewed MR imaging data from 100 healthy children. Using an atlas-based approach, age-related normal values for regional CBF, apparent diffusion coefficient, and volume were determined for the cerebral cortex, hippocampus, thalamus, caudate, putamen, globus pallidus, amygdala, and nucleus accumbens.All gray matter structures grew rapidly before the age of 10 years and then plateaued or slightly declined thereafter. The ADC of all structures decreased with age, with the most rapid changes occurring prior to the age of 5 years. With the exception of the globus pallidus, CBF increased rather linearly with age.Normal brain gray matter is characterized by rapid early volume growth and increasing CBF with concomitantly decreasing ADC. The extracted reference data that combine CBF and ADC parameters during brain growth may provide a useful resource when assessing pathologic changes in children.

View details for DOI 10.3174/ajnr.A4772

View details for PubMedID 27102314

Abstract

Tumor location has been shown to be a significant prognostic factor in patients with glioblastoma. The purpose of this study was to characterize glioblastoma lesions by identifying MR imaging voxel-based tumor location features that are associated with tumor molecular profiles, patient characteristics, and clinical outcomes.Preoperative T1 anatomic MR images of 384 patients with glioblastomas were obtained from 2 independent cohorts (n = 253 from the Stanford University Medical Center for training and n = 131 from The Cancer Genome Atlas for validation). An automated computational image-analysis pipeline was developed to determine the anatomic locations of tumor in each patient. Voxel-based differences in tumor location between good (overall survival of >17 months) and poor (overall survival of <11 months) survival groups identified in the training cohort were used to classify patients in The Cancer Genome Atlas cohort into 2 brain-location groups, for which clinical features, messenger RNA expression, and copy number changes were compared to elucidate the biologic basis of tumors located in different brain regions.Tumors in the right occipitotemporal periventricular white matter were significantly associated with poor survival in both training and test cohorts (both, log-rank P < .05) and had larger tumor volume compared with tumors in other locations. Tumors in the right periatrial location were associated with hypoxia pathway enrichment and PDGFRA amplification, making them potential targets for subgroup-specific therapies.Voxel-based location in glioblastoma is associated with patient outcome and may have a potential role for guiding personalized treatment.

View details for DOI 10.3174/ajnr.A4631

View details for Web of Science ID 000373346900014

Abstract

This case series assesses white matter microstructure of the cerebellar peduncles in 4 adolescents born preterm with enlarged ventricles and reduced white matter volume in the cerebrum but no apparent injury to the cerebellum. Subjects (ages 12-17 years, gestational age 26-32 weeks, birth weight 825-2211 g) were compared to a normative sample of 19 full-term controls (9-17 years, mean gestational age 39 weeks, mean birth weight 3154 g). Tract profiles for each of the cerebellar peduncles were generated by calculating fractional anisotropy at 30 points along the central portion of each tract. One or more case subjects exhibited higher fractional anisotropy beyond the 90th percentile in the inferior, middle, and superior cerebellar peduncles. Findings demonstrate that differences in cerebellar white matter microstructure can be detected in the absence of macrostructural cerebellar abnormalities.

View details for DOI 10.1177/0883073815592223

View details for PubMedID 26116381

Abstract

Intact development of cerebellar connectivity is essential for healthy neuromotor and neurocognitive development. To date, limited knowledge about the microstructural properties of the cerebellar peduncles, the major white matter tracts of the cerebellum, is available for children and adolescents. Such information would be useful as a comparison for studies of normal development, clinical conditions, or associations of cerebellar structures with cognitive and motor functions. The goal of the present study was to evaluate the variability in diffusion measures of the cerebellar peduncles within individuals and within a normative sample of healthy children. Participants were 19 healthy children and adolescents, aged 9-17years, mean age 13.02.3. We analyzed diffusion magnetic resonance imaging (dMRI) data with deterministic tractography. We generated tract profiles for each of the cerebellar peduncles by extracting four diffusion properties (fractional anisotropy (FA) and mean, radial, and axial diffusivity) at 30 equidistant points along each tract. We were able to identify the middle cerebellar peduncle and the bilateral inferior and superior cerebellar peduncles in all participants. The results showed that within each of the peduncles, the diffusion properties varied along the trajectory of the tracts. However, the tracts showed consistent patterns of variation across individuals; the coefficient of variation for FA across individual profiles was low (20%) for each tract. We observed no systematic variation of the diffusion properties with age. These cerebellar tract profiles of the cerebellar peduncles can serve as a reference for future studies of children across the age range and for children and adolescents with clinical conditions that affect the cerebellum.

View details for DOI 10.1007/s12311-015-0652-1

View details for PubMedID 25648754

Abstract

Near-term brain structure was examined in preterm infants in relation to neurodevelopment. We hypothesized that near-term macrostructural brain abnormalities identified using conventional magnetic resonance imaging (MRI), and white matter (WM) microstructure detected using diffusion tensor imaging (DTI), would correlate with lower cognitive and motor development and slower, less-stable gait at 18-22 mo of age.One hundred and two very-low-birth-weight preterm infants (1,500g birth weight; 32wk gestational age) were recruited prior to routine near-term brain MRI at 36.61.8wk postmenstrual age. Cerebellar and WM macrostructure was assessed on conventional structural MRI. DTI was obtained in 66 out of 102 and WM microstructure was assessed using fractional anisotropy and mean diffusivity (MD) in six subcortical brain regions defined by DiffeoMap neonatal atlas. Neurodevelopment was assessed with Bayley-Scales-of-Infant-Toddler-Development, 3rd-Edition (BSID-III); gait was assessed using an instrumented mat.Neonates with cerebellar abnormalities identified using MRI demonstrated lower mean BSID-III cognitive composite scores (89.010.1 vs. 97.812.4; P = 0.002) at 18-22 mo. Neonates with higher DTI-derived left posterior limb of internal capsule (PLIC) MD demonstrated lower cognitive and motor composite scores (r = -0.368; P = 0.004; r = -0.354; P = 0.006) at 18-22 mo; neonates with higher genu MD demonstrated slower gait velocity (r = -0.374; P = 0.007). Multivariate linear regression significantly predicted cognitive (adjusted r(2) = 0.247; P = 0.002) and motor score (adjusted r(2) = 0.131; P = 0.017).Near-term cerebellar macrostructure and PLIC and genu microstructure were predictive of early neurodevelopment and gait.

View details for DOI 10.1038/pr.2015.157

View details for PubMedID 26322412

Abstract

Glioblastoma (GBM) is the most common and highly lethal primary malignant brain tumor in adults. There is a dire need for easily accessible, noninvasive biomarkers that can delineate underlying molecular activities and predict response to therapy. To this end, we sought to identify subtypes of GBM, differentiated solely by quantitative magnetic resonance (MR) imaging features, that could be used for better management of GBM patients. Quantitative image features capturing the shape, texture, and edge sharpness of each lesion were extracted from MR images of 121 single-institution patients with de novo, solitary, unilateral GBM. Three distinct phenotypic "clusters" emerged in the development cohort using consensus clustering with 10,000 iterations on these image features. These three clusters--pre-multifocal, spherical, and rim-enhancing, names reflecting their image features--were validated in an independent cohort consisting of 144 multi-institution patients with similar tumor characteristics from The Cancer Genome Atlas (TCGA). Each cluster mapped to a unique set of molecular signaling pathways using pathway activity estimates derived from the analysis of TCGA tumor copy number and gene expression data with the PARADIGM (Pathway Recognition Algorithm Using Data Integration on Genomic Models) algorithm. Distinct pathways, such as c-Kit and FOXA, were enriched in each cluster, indicating differential molecular activities as determined by the image features. Each cluster also demonstrated differential probabilities of survival, indicating prognostic importance. Our imaging method offers a noninvasive approach to stratify GBM patients and also provides unique sets of molecular signatures to inform targeted therapy and personalized treatment of GBM.

View details for DOI 10.1126/scitranslmed.aaa7582

View details for PubMedID 26333934

View details for PubMedCentralID PMC4666025

Abstract

To determine the prevalence of radiographic and histologic superior semicircular canal dehiscence (SSCD) and posterior semicircular canal dehiscence (PSCD) and associated changes in temporal bone thickness in children aged 0 to 7 years.Retrospective chart review and histopathologic review of cadaveric bone specimens.Two tertiary referral centers.Children younger than 7 years who underwent high-resolution computed tomography scan including the temporal bones between 1998 and 2013 and temporal bones harvested from children younger than 7 years.Two hundred twenty-eight computed tomography studies and 58 temporal bone specimens were reviewed. Available patient demographics were tabulated.Prevalence of SSCD and PSCD and bone thickness over semicircular canals, with comparison across age groups. Clinical data were extracted for patients with radiographic dehiscence.Prevalence by ear of SSCD was 11.9%, 4.9%, 2.8%, and 0% and of PSCD was 16.7%, 2.4%, 1.4%, and 0% in children aged less than 6 months, 6 to 11 months, 12 to 35 months, and 3 to 7 years, respectively. SSCD was statistically more common before 1 year of age and PSCD before 6 months of age. Bone thickness overlying both the SSC and the PSC increased with age. Radiographic PSC bone was significantly thicker than SSC bone in patients older than 12 months. No dehiscences were found in the histologic specimens.Radiographic dehiscence of the canals is common in the first 6 months of life, with thin bone seen histologically. Prevalence decreases with increasing age as the bone overlying the canals increases in thickness.

View details for DOI 10.1097/MAO.0000000000000811

View details for Web of Science ID 000360488000015

Abstract

To determine the prevalence of radiographic and histologic superior semicircular canal dehiscence (SSCD) and posterior semicircular canal dehiscence (PSCD) and associated changes in temporal bone thickness in children aged 0 to 7 years.Retrospective chart review and histopathologic review of cadaveric bone specimens.Two tertiary referral centers.Children younger than 7 years who underwent high-resolution computed tomography scan including the temporal bones between 1998 and 2013 and temporal bones harvested from children younger than 7 years.Two hundred twenty-eight computed tomography studies and 58 temporal bone specimens were reviewed. Available patient demographics were tabulated.Prevalence of SSCD and PSCD and bone thickness over semicircular canals, with comparison across age groups. Clinical data were extracted for patients with radiographic dehiscence.Prevalence by ear of SSCD was 11.9%, 4.9%, 2.8%, and 0% and of PSCD was 16.7%, 2.4%, 1.4%, and 0% in children aged less than 6 months, 6 to 11 months, 12 to 35 months, and 3 to 7 years, respectively. SSCD was statistically more common before 1 year of age and PSCD before 6 months of age. Bone thickness overlying both the SSC and the PSC increased with age. Radiographic PSC bone was significantly thicker than SSC bone in patients older than 12 months. No dehiscences were found in the histologic specimens.Radiographic dehiscence of the canals is common in the first 6 months of life, with thin bone seen histologically. Prevalence decreases with increasing age as the bone overlying the canals increases in thickness.

View details for DOI 10.1097/MAO.0000000000000811

View details for PubMedID 26164444

Abstract

Focal cerebral arteriopathy is a term used to describe unilateral intracranial arteriopathy involving the distal internal carotid artery and proximal segments of the middle and anterior cerebral artery. We describe the disease course of 10 pediatric arterial ischemic stroke patients with focal cerebral arteriopathy from a single quaternary-care center.We retrospectively reviewed pediatric stroke patients with focal cerebral arteriopathy without lenticulostriate collaterals treated at our institution between 2005 and 2014. Angiography was reviewed by a child neurologist and a pediatric neuroradiologist, and chart reviews were performed.Ten individuals with focal cerebral arteriopathy were identified. At the time of stroke presentation, four patients were diagnosed with arterial dissection, two with moyamoya disease, one with embolic occlusion, one with hemorrhagic stroke, and two with arterial dissection or vasculitis. At last follow-up, six patients had a change in diagnosis: four were diagnosed with transient cerebral arteriopathy, two with arterial dissection, and four with moyamoya disease. Four children experienced stroke recurrence. All were administered aspirin, one was administered heparin, two were administered intravenous tissue plasminogen activator, and five underwent surgical revascularization.Among pediatric stroke patients with a similar angiographic appearance, there is variable concordance between diagnosis, prognosis and treatment choice. Improved consensus-based diagnostic criteria and further research is needed to identify disease biomarkers and predictors of arterial progression.

View details for DOI 10.1016/j.pediatrneurol.2015.05.008

View details for PubMedID 26122406

Abstract

Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique that enhances image contrast by using the susceptibility differences between tissues. It is created by combining both magnitude and phase in the gradient echo data. SWI is sensitive to both paramagnetic and diamagnetic substances which generate different phase shift in MRI data. SWI images can be displayed as a minimum intensity projection that provides high resolution delineation of the cerebral venous architecture, a feature that is not available in other MRI techniques. As such, SWI has been widely applied to diagnose various venous abnormalities. SWI is especially sensitive to deoxygenated blood and intracranial mineral deposition and, for that reason, has been applied to image various pathologies including intracranial hemorrhage, traumatic brain injury, stroke, neoplasm, and multiple sclerosis. SWI, however, does not provide quantitative measures of magnetic susceptibility. This limitation is currently being addressed with the development of quantitative susceptibility mapping (QSM) and susceptibility tensor imaging (STI). While QSM treats susceptibility as isotropic, STI treats susceptibility as generally anisotropic characterized by a tensor quantity. This article reviews the basic principles of SWI, its clinical and research applications, the mechanisms governing brain susceptibility properties, and its practical implementation, with a focus on brain imaging. J. Magn. Reson. Imaging 2015;42:23-41. 2014 Wiley Periodicals, Inc.

View details for DOI 10.1002/jmri.24768

View details for PubMedID 25270052

Abstract

Here we investigate the utility of a dual-echo Echo-Planar Imaging (DE-EPI) Diffusion Weighted Imaging (DWI) approach to improve lesion conspicuity in pediatric imaging. This method delivers two 'echo images' for one diffusion-preparation period. We also demonstrate how the echoes can be utilized to remove transmit/receive coil-induced and static magnetic field intensity modulations on both echo images, which often mimic pathology and thereby pose diagnostic challenges. DE-EPI DWI data were acquired in 18 pediatric patients with abnormal diffusion lesions, and 46 pediatric patient controls at 3T. Echo1 [TE = 45ms] and Echo2 [TE = 86ms] were corrected for signal intensity variation across the images by exploiting the images equivalent coil-sensitivity and susceptibility-induced modulations. Two neuroradiologists independently reviewed Echo1 and Echo2 and their intensity-corrected variants (cEcho1 and cEcho2) on a 7-point Likert scale, with grading on lesion conspicuity diagnostic confidence. The apparent diffusion coefficient (ADC) map from Echo1 was used to validate presence of true pathology. Echo2 was unanimously favored over Echo1 for its sensitivity for detecting acute brain injury, with a mean respective lesion conspicuity of 5.7/4.4 (p < 0.005) and diagnostic confidence of 5.1/4.3 (p = 0.025). cEcho2 was rated higher than cEcho1, with a mean respective lesion conspicuity of 5.5/4.3 (p < 0.005) and diagnostic confidence of 5.4/4.4 (p < 0.005). cEcho2 was favored over all echoes for its diagnostic reliability, particularly in regions close to the head coil. This work concludes that DE-EPI DWI is a useful alternative to conventional single-echo EPI DWI, whereby Echo2 and cEcho2 allows for improved lesion detection and overall higher diagnostic confidence.

View details for DOI 10.1371/journal.pone.0129325

View details for Web of Science ID 000356327000065

View details for PubMedID 26069959

Abstract

Susceptibility-weighted imaging (SWI) in neuroimaging can be challenging due to long scan times of three-dimensional (3D) gradient recalled echo (GRE), while faster techniques such as 3D interleaved echo-planar imaging (iEPI) are prone to motion artifacts. Here we outline and implement a 3D short-axis propeller echo-planar imaging (SAP-EPI) trajectory as a faster, motion-correctable approach for SWI.Experiments were conducted on a 3T MRI system. The 3D SAP-EPI, 3D iEPI, and 3D GRE SWI scans were acquired on two volunteers. Controlled motion experiments were conducted to test the motion-correction capability of 3D SAP-EPI. The 3D SAP-EPI SWI data were acquired on two pediatric patients as a potential alternative to 2D GRE used clinically.The 3D GRE images had a better target resolution (0.47 0.94 2 mm, scan time=5 min), iEPI and SAP-EPI images (resolution=0.94 0.94 2 mm) were acquired in a faster scan time (1:52 min) with twice the brain coverage. SAP-EPI showed motion-correction capability and some immunity to undersampling from rejected data.While 3D SAP-EPI suffers from some geometric distortion, its short scan time and motion-correction capability suggest that SAP-EPI may be a useful alternative to GRE and iEPI for use in SWI, particularly in uncooperative patients.J. Magn. Reson. Imaging 2014. 2014 Wiley Periodicals, Inc.

View details for DOI 10.1002/jmri.24675

View details for PubMedID 24956237

View details for PubMedCentralID PMC4275419

Abstract

Recent small, retrospective series suggest bevacizumab may be a therapeutic option for recurrent pediatric low-grade glioma (LGG). Assessment of therapeutic responses is complicated by the unpredictable natural history of these tumors. Because diffusion-weighted imaging quantifies microscopic water motion affected by cellular density and histologic features, we hypothesized that it may be helpful in monitoring therapeutic response of LGG to bevacizumab. We retrospectively reviewed eight consecutive patients, median age 4.8 (range 2.3-12.3) years at initiation of bevacizumab therapy for recurrent or refractory LGG. Patients received 10 mg/kg/dose every 2 weeks (median 16 doses/therapy course). Mean apparent diffusion coefficient (ADC) was measured and analyzed in respect to tumor volume. Following the first treatment course, seven of eight patients had reduced tumor volume (25 %) and ADC. The median decrease in tumor volume was 47% (range -6 to 78 %) and the median decrease in ADC was 14 % (range -5 to 30 %). The ADC was significantly decreased during therapy, whereas the decrease in volume was seen only after therapy completion. There was a positive correlation between percent change in tumor volume and ADC (p < 0.05). We report a decrease in tumor ADC during initial bevacizumab therapy that is accompanied by a decrease in volume following therapy. Imaging changes in microscopic water motion associated with histology may be useful in monitoring the therapeutic response of LGG to bevacizumab.

View details for DOI 10.1007/s11060-015-1754-9

View details for Web of Science ID 000354717800008

View details for PubMedID 25758812

Abstract

Citrate, a tricarboxylic acid cycle intermediate, is present in high concentrations in pediatric diffuse intrinsic pontine gliomas (DIPG). Since citrate increases during hypoxia in animal studies, we hypothesized that it accumulates in DIPG when hypoperfused. Relative tumor blood volumes (rTBV) were determined, using dynamic susceptibility contrast-enhanced magnetic resonance imaging, in twelve children [median age 8.2 (range 3.2-14.5) years] with DIPG and compared to citrate concentrations measured with in vivo proton magnetic resonance spectroscopy ((1)H MRS). Tissue perfusion and metabolite concentration were assessed at initial presentation and over the clinical course, yielding 36 and 46 perfusion and MR spectroscopy datasets, respectively. At presentation, DIPG blood volume was 6027% of that measured for normal cerebellum. Citrate, which is not detectable in normal brain tissue, was present in DIPG at concentrations of 3.811.44mmol/kg tissue. Over the course of the disease and treatment, rTBV increased and citrate decreased (both p<0.05) with an inverse correlation (p=0.028). Citrate accumulation is associated with tissue hypoperfusion in DIPG.

View details for DOI 10.1007/s11060-015-1726-0

View details for Web of Science ID 000351856300017

View details for PubMedID 25670389

Abstract

Head and neck masses occurring in the neonatal period and early infancy consist of vascular tumors, vascular malformations, benign and malignant soft tissue tumors, and other developmental lesions. Although some lesions can be diagnosed on clinical grounds, others can only be diagnosed by imaging. Beyond diagnosis, imaging plays a significant role in evaluating the location and extent of a lesion for possible intervention. In this article, we review the clinical presentation and imaging appearance of common and rare masses that may be encountered in this age group. We also highlight current treatment strategies for specific lesions.

View details for DOI 10.1053/j.sult.2015.01.004

View details for Web of Science ID 000355575300003

View details for PubMedID 26001942

Abstract

Congenital brain malformations are a major cause of morbidity and mortality in pediatric patients who are younger than 2 years. Optimization of patient care requires accurate diagnosis, which can be challenging as congenital brain malformations include an extensive variety of anomalies. Radiologic imaging helps to identify the malformations and to guide management. Understanding radiologic findings necessitates knowledge of central nervous system embryogenesis. This review discusses the imaging of congenital brain malformations encountered in patients who are younger than 2 years in the context of brain development.

View details for DOI 10.1053/j.sult.2015.01.003

View details for PubMedID 26001941

Abstract

OBJECT The authors describe the application of a flexible CO2 laser for corpus callosotomy in children with epilepsy. METHODS This retrospective case series reviews all cases in which pediatric patients underwent a corpus callosotomy performed using the CO2 OmniGuide laser between May 2005 and October 2012. Data were collected from 8 corpus callosotomy procedures in 6 pediatric patients presenting with medically refractory epilepsy marked by drop attacks. RESULTS Complete corpus callosotomies were performed in 6 patients (3 boys, 3 girls; ages 5-14 years). In 4 patients the complete callosotomy occurred as a single procedure, and in 2 patients an anterior two-thirds callosotomy was performed first. These 2 patients subsequently required a complete callosotomy due to inadequate control of their drop attacks. In all cases there was clean lesioning of the tract with preservation of the ependymal plane and less inadvertent thermal tissue damage due to low penetration of the laser through cerebrospinal fluid. All patients had resolution or improvement of drop attacks after surgery. No complications were encountered, and imaging demonstrated a clean sectioning of callosal fibers with preservation of normal ventricular anatomy. CONCLUSIONS These cases illustrate the use of this device in completing corpus callosotomy in pediatric patients. The low-profile laser fiber tip was well suited for working in the depths of the interhemispheric fissure with minimal brain retraction. The flexible CO2 laser allows a precise callosal lesioning through an interhemispheric approach and is a useful adjunct to be employed in these cases.

View details for DOI 10.3171/2014.10.PEDS13498

View details for PubMedID 25525931

Abstract

Diffusion tensor imaging (DTI) is useful for multiple clinical applications, but its routine implementation for children may be difficult due to long scan times. This study evaluates the impact of decreasing the number of DTI acquisitions (NEX) on interpretability of pediatric brain DTI.15 children with MRI-visible neuropathologies were imaged at 3T using our motion-corrected, parallel imaging- accelerated DT-EPI technique with 3 NEX (scan time 8.25 min). Using these acquisitions, NEX = 1 (scan time 2.75 min) and NEX = 2 (scan time 5.5 min) images were simulated. Two neuroradiologists scored diffusion-weighted images (DWI), apparent diffusion coefficient (ADC), fractional anisotropy (FA), and first eigenvector color-encoded (EV) images from each NEX for perceived SNR, lesion conspicuity and clinical confidence. ROI FA/ADC and image SNR values were also compared across NEX.NEX = 2 perceived SNR, lesion conspicuity, and clinical confidence were not inferior to NEX = 3 images. NEX = 1 images showed comparable lesion conspicuity and clinical confidence as NEX = 3, but inferior perceived SNR. FA and ADC ROI measurements demonstrated no significant difference across NEX. The greatest SNR increase was seen between NEX = 1 and NEX = 2.Reducing NEX to shorten imaging time may impact clinical utility in a manner that does not directly correspond with SNR changes.

View details for DOI 10.1111/jon.12093

View details for PubMedID 24593174

Abstract

Current neuroimaging provides detailed anatomic and functional evaluation of brain tumors, allowing for improved diagnostic and prognostic capabilities. Some challenges persist even with today's advanced imaging techniques, including accurate delineation of tumor margins and distinguishing treatment effects from residual or recurrent tumor. Ultrasmall superparamagnetic iron oxide nanoparticles are an emerging tool that can add clinically useful information due to their distinct physiochemical features and biodistribution, while having a good safety profile. Nanoparticles can be used as a platform for theranostic drugs, which have shown great promise for the treatment of CNS malignancies. This review will provide an overview of clinical ultrasmall superparamagnetic iron oxides and how they can be applied to the diagnostic and therapeutic neuro-oncologic setting.

View details for DOI 10.2217/NNM.14.203

View details for Web of Science ID 000352806000009

View details for PubMedID 25867862

Abstract

Here we investigate the utility of a dual-echo Echo-Planar Imaging (DE-EPI) Diffusion Weighted Imaging (DWI) approach to improve lesion conspicuity in pediatric imaging. This method delivers two 'echo images' for one diffusion-preparation period. We also demonstrate how the echoes can be utilized to remove transmit/receive coil-induced and static magnetic field intensity modulations on both echo images, which often mimic pathology and thereby pose diagnostic challenges. DE-EPI DWI data were acquired in 18 pediatric patients with abnormal diffusion lesions, and 46 pediatric patient controls at 3T. Echo1 [TE = 45ms] and Echo2 [TE = 86ms] were corrected for signal intensity variation across the images by exploiting the images equivalent coil-sensitivity and susceptibility-induced modulations. Two neuroradiologists independently reviewed Echo1 and Echo2 and their intensity-corrected variants (cEcho1 and cEcho2) on a 7-point Likert scale, with grading on lesion conspicuity diagnostic confidence. The apparent diffusion coefficient (ADC) map from Echo1 was used to validate presence of true pathology. Echo2 was unanimously favored over Echo1 for its sensitivity for detecting acute brain injury, with a mean respective lesion conspicuity of 5.7/4.4 (p < 0.005) and diagnostic confidence of 5.1/4.3 (p = 0.025). cEcho2 was rated higher than cEcho1, with a mean respective lesion conspicuity of 5.5/4.3 (p < 0.005) and diagnostic confidence of 5.4/4.4 (p < 0.005). cEcho2 was favored over all echoes for its diagnostic reliability, particularly in regions close to the head coil. This work concludes that DE-EPI DWI is a useful alternative to conventional single-echo EPI DWI, whereby Echo2 and cEcho2 allows for improved lesion detection and overall higher diagnostic confidence.

View details for DOI 10.1371/journal.pone.0129325

View details for PubMedID 26069959

Abstract

Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups.All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (wingless, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes.Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100%, P = .007), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%-100%), and sonic hedgehog tumors arose in the cerebellar hemispheres with a positive predictive value of 100% (95% CI, 59%-100%). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91% (95% CI, 59%-98%). When we used the MR imaging feature-based regression model, 66% of medulloblastomas were correctly predicted in the discovery cohort, and 65%, in the validation cohort.Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.

View details for DOI 10.3174/ajnr.A3990

View details for PubMedID 24831600

Abstract

Reduced cerebral perfusion has been observed with elevated intracranial pressure. We hypothesized that arterial spin-labeled CBF can be used as a marker for symptomatic hydrocephalus.We compared baseline arterial spin-labeled CBF in 19 children (median age, 6.5 years; range, 1-17 years) with new posterior fossa brain tumors and clinical signs of intracranial hypertension with arterial spin-labeled CBF in 16 age-matched controls and 4 patients with posterior fossa tumors without ventriculomegaly or signs of intracranial hypertension. Measurements were recorded in the cerebrum at the vertex, deep gray nuclei, and periventricular white matter and were assessed for a relationship to ventricular size. In 16 symptomatic patients, we compared cerebral perfusion before and after alleviation of hydrocephalus.Patients with uncompensated hydrocephalus had lower arterial spin-labeled CBF than healthy controls for all brain regions interrogated (P < .001). No perfusion difference was seen between asymptomatic patients with posterior fossa tumors and healthy controls (P = 1.000). The median arterial spin-labeled CBF increased after alleviation of obstructive hydrocephalus (P < .002). The distance between the frontal horns inversely correlated with arterial spin-labeled CBF of the cerebrum (P = .036) but not the putamen (P = .156), thalamus (P = .111), or periventricular white matter (P = .121).Arterial spin-labeled-CBF was reduced in children with uncompensated hydrocephalus and restored after its alleviation. Arterial spin-labeled-CBF perfusion MR imaging may serve a future role in the neurosurgical evaluation of hydrocephalus, as a potential noninvasive method to follow changes of intracranial pressure with time.

View details for DOI 10.3174/ajnr.A3891

View details for PubMedID 24651817

Abstract

Parallel imaging facilitates the acquisition of echo-planar images with a reduced TE, enabling the incorporation of an additional image at a later TE. Here we investigated the use of a parallel imaging-enhanced dual-echo EPI sequence to improve lesion conspicuity in diffusion-weighted imaging.Parallel imaging-enhanced dual-echo DWI data were acquired in 50 consecutive patients suspected of stroke at 1.5T. The dual-echo acquisition included 2 EPI for 1 diffusion-preparation period (echo 1 [TE = 48 ms] and echo 2 [TE = 105 ms]). Three neuroradiologists independently reviewed the 2 echoes by using the routine DWI of our institution as a reference. Images were graded on lesion conspicuity, diagnostic confidence, and image quality. The apparent diffusion coefficient map from echo 1 was used to validate the presence of acute infarction. Relaxivity maps calculated from the 2 echoes were evaluated for potential complementary information.Echo 1 and 2 DWIs were rated as better than the reference DWI. While echo 1 had better image quality overall, echo 2 was unanimously favored over both echo 1 and the reference DWI for its high sensitivity in detecting acute infarcts.Parallel imaging-enhanced dual-echo diffusion-weighted EPI is a useful method for evaluating lesions with reduced diffusivity. The long TE of echo 2 produced DWIs that exhibited superior lesion conspicuity compared with images acquired at a shorter TE. Echo 1 provided higher SNR ADC maps for specificity to acute infarction. The relaxivity maps may serve to complement information regarding blood products and mineralization.

View details for DOI 10.3174/ajnr.A3921

View details for PubMedID 24763417

View details for DOI 10.1089/jayao.2013.0041

View details for Web of Science ID 000350130800008

Abstract

Tracking the progression of low grade tumors (LGTs) is a challenging task, due to their slow growth rate and associated complex internal tumor components, such as heterogeneous enhancement, hemorrhage, and cysts. In this paper, the authors show a semiautomatic method to reliably track the volume of LGTs and the evolution of their internal components in longitudinal MRI scans.The authors' method utilizes a spatiotemporal evolution modeling of the tumor and its internal components. Tumor components gray level parameters are estimated from the follow-up scan itself, obviating temporal normalization of gray levels. The tumor delineation procedure effectively incorporates internal classification of the baseline scan in the time-series as prior data to segment and classify a series of follow-up scans. The authors applied their method to 40 MRI scans of ten patients, acquired at two different institutions. Two types of LGTs were included: Optic pathway gliomas and thalamic astrocytomas. For each scan, a "gold standard" was obtained manually by experienced radiologists. The method is evaluated versus the gold standard with three measures: gross total volume error, total surface distance, and reliability of tracking tumor components evolution.Compared to the gold standard the authors' method exhibits a mean Dice similarity volumetric measure of 86.58% and a mean surface distance error of 0.25 mm. In terms of its reliability in tracking the evolution of the internal components, the method exhibits strong positive correlation with the gold standard.The authors' method provides accurate and repeatable delineation of the tumor and its internal components, which is essential for therapy assessment of LGTs. Reliable tracking of internal tumor components over time is novel and potentially will be useful to streamline and improve follow-up of brain tumors, with indolent growth and behavior.

View details for DOI 10.1118/1.4871040

View details for PubMedID 24784396

View details for PubMedCentralID PMC4000396

Abstract

Injury to the dentatothalamic pathway that originates in the cerebellum has been suggested as a mechanism for neurologic complications in children treated for posterior fossa tumors. We hypothesized that time-dependent changes occur in the dentatothalamic pathway.Diffusion tensor evaluation was performed in 14 children (median age, 4.1 years; age range, 1-20 years) who underwent serial MR imaging at 3T as part of routine follow-up after posterior fossa tumor resection with or without adjuvant therapy. Tensor metrics were obtained in the acute (1 week), subacute (1 to <6 months), and chronic (6 months) periods after surgery. We evaluated the following dentatothalamic constituents: bilateral dentate nuclei, cerebellar white matter, and superior cerebellar peduncles. Serial dentate nuclei volumes were also obtained and compared with the patient's baseline.The most significant tensor changes to the superior cerebellar peduncles and cerebellar white matter occurred in the subacute period, regardless of the tumor pathology or therapy regimen, with signs of recovery in the chronic period. However, chronic volume loss and reduced mean diffusivity were observed in the dentate nuclei and did not reverse. This atrophy was associated with radiation therapy and symptoms of ataxia.Longitudinal diffusion MR imaging in children treated for posterior fossa tumors showed time-dependent tensor changes in components of the dentatothalamic pathway that suggest evolution of structural damage with inflammation and recovery of tissue directionality. However, the dentate nuclei did not show tensor or volumetric recovery, suggesting that the injury may be chronic.

View details for DOI 10.3174/ajnr.A3735

View details for PubMedID 24052507

Abstract

Glial cysts of the pineal gland can frequently be found in adults and children, but only rarely do they enlarge to become clinically relevant. We report a unique presentation of a pineal cyst in the midbrain tectum of a 16-month-old girl who initially presented with ptosis and strabismus. Preoperative imaging studies and intraoperative findings revealed no continuity between the tectal cyst and the pineal gland proper. We surmise that this tectal pineal cyst may have arisen from duplicated pineal gland tissue.

View details for DOI 10.1016/j.humpath.2013.10.002

View details for PubMedID 24411061

Abstract

While pediatric diffuse intrinsic pontine gliomas (DIPG) remain fatal, recent data have shown subgroups with distinct molecular biology and clinical behavior. We hypothesized that diffusion-weighted MRI can be used as a prognostic marker to stratify DIPG subsets with distinct clinical behavior. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted MRI were computed in 20 consecutive children with treatment-nave DIPG tumors. The median ADC for the cohort was used to stratify the tumors into low and high ADC groups. Survival, gender, therapy, and potential steroid effects were compared between the ADC groups. Median age at diagnosis was 6.6 (range 2.3-13.2) years, with median follow-up seven (range 1-36) months. There were 14 boys and six girls. Seventeen patients received radiotherapy, five received chemotherapy, and six underwent cerebrospinal fluid diversion. The median ADC of 1,29510(-6)mm(2)/s for the cohort partitioned tumors into low or high diffusion groups, which had distinct median survivals of 3 and 13months, respectively (log-rank p<0.001). Low ADC tumors were found only in boys, whereas high ADC tumors were found in both boys and girls. Available tissue specimens in three low ADC tumors demonstrated high-grade histology, whereas one high ADC tumor demonstrated low-grade histology with a histone H3.1 K27M mutation and high-grade metastatic lesion at autopsy. ADC derived from diffusion-weighted MRI may identify prognostically distinct subgroups of pediatric DIPG.

View details for DOI 10.1007/s11060-014-1375-8

View details for PubMedID 24522717

Abstract

Magnetic resonance imaging (MRI) is routinely obtained in patients with central nervous system (CNS) tumors, but few studies have been conducted to evaluate this practice. We assessed the benefits of surveillance MRI and more specifically spine MRI in a contemporary cohort. We evaluated MRI results of children diagnosed with CNS tumors from January 2000 to December 2011. Children with at least one surveillance MRI following the diagnosis of medulloblastoma (MB), atypical teratoid rhabdoid tumor (ATRT), pineoblastoma (PB), supratentorial primitive neuroectodermal tumor, supratentorial high-grade glioma (World Health Organization grade III-IV), CNS germ cell tumors or ependymoma were included. A total of 2,707 brain and 1,280 spine MRI scans were obtained in 258 patients. 97% of all relapses occurred in the brain and 3% were isolated to the spine. Relapse was identified in 226 (8%) brain and 48 (4%) spine MRI scans. The overall rate of detecting isolated spinal relapse was 9/1,000 and 7/1,000 for MB patients. MRI performed for PB showed the highest rate for detecting isolated spinal recurrence with 49/1,000. No initial isolated spinal relapse was identified in patients with glioma, supratentorial primitive neuroectodermal tumor and ATRT. Isolated spinal recurrences are infrequent in children with malignant CNS tumors and the yield of spine MRI is very low. Tailoring surveillance spine MRI to patients with higher spinal relapse risk such as PB, MB with metastatic disease and within 3years of diagnosis could improve allocation of resources without compromising patient care.

View details for DOI 10.1007/s11060-013-1347-4

View details for PubMedID 24401959

Abstract

Pediatric brain tumors have diverse pathologic features, which poses diagnostic challenges. Although perfusion evaluation of adult tumors is well established, hemodynamic properties are not well characterized in children. Our goal was to apply arterial spin-labeling perfusion for various pathologic types of pediatric brain tumors and evaluate the role of arterial spin-labeling in the prediction of tumor grade.Arterial spin-labeling perfusion of 54 children (mean age, 7.5 years; 33 boys and 21 girls) with treatment-naive brain tumors was retrospectively evaluated. The 3D pseudocontinuous spin-echo arterial spin-labeling technique was acquired at 3T MR imaging. Maximal relative tumor blood flow was obtained by use of the ROI method and was compared with tumor histologic features and grade.Tumors consisted of astrocytic (20), embryonal (11), ependymal (3), mixed neuronal-glial (8), choroid plexus (5), craniopharyngioma (4), and other pathologic types (3). The maximal relative tumor blood flow of high-grade tumors (grades III and IV) was significantly higher than that of low-grade tumors (grades I and II) (P < .001). There was a wider relative tumor blood flow range among high-grade tumors (2.14 1.78) compared with low-grade tumors (0.60 0.29) (P < .001). Across the cohort, relative tumor blood flow did not distinguish individual histology; however, among posterior fossa tumors, relative tumor blood flow was significantly higher for medulloblastoma compared with pilocytic astrocytoma (P = .014).Characteristic arterial spin-labeling perfusion patterns were seen among diverse pathologic types of brain tumors in children. Arterial spin-labeling perfusion can be used to distinguish high-grade and low-grade tumors.

View details for DOI 10.3174/ajnr.A3670

View details for PubMedID 23907239

Abstract

BACKGROUND AND PURPOSE:2D gradient-echo imaging is sensitive to T2* lesions (hemorrhages, mineralization, and vascular lesions), and susceptibility-weighted imaging is even more sensitive, but at the cost of additional scan time (SWI: 5-10 minutes; 2D gradient-echo: 2 minutes). The long acquisition time of SWI may pose challenges in motion-prone patients. We hypothesized that 2D SWI/phase unwrapped images processed from 2D gradient-echo imaging could improve T2* lesion detection.MATERIALS AND METHODS:2D gradient-echo brain images of 50 consecutive pediatric patients (mean age, 8 years) acquired at 3T were retrospectively processed to generate 2D SWI/phase unwrapped images. The 2D gradient-echo and 2D SWI/phase unwrapped images were compared for various imaging parameters and were scored in a blinded fashion.RESULTS:Of 50 patients, 2D gradient-echo imaging detected T2* lesions in 29 patients and had normal findings in 21 patients. 2D SWI was more sensitive than standard 2D gradient-echo imaging in detecting T2* lesions (P < .0001). 2D SWI/phase unwrapped imaging also improved delineation of normal venous structures and nonpathologic calcifications and helped distinguish calcifications from hemorrhage. A few pitfalls of 2D SWI/phase unwrapped imaging were noted, including worsened motion and dental artifacts and challenges in detecting T2* lesions adjacent to calvaria or robust deoxygenated veins.CONCLUSIONS:2D SWI and associated phase unwrapped images processed from standard 2D gradient-echo images were more sensitive in detecting T2* lesions and delineating normal venous structures and nonpathologic mineralization, and they also helped distinguish calcification at no additional scan time. SWI processing of 2D gradient-echo images may be a useful adjunct in cases in which longer scan times of 3D SWI are difficult to implement.

View details for DOI 10.3174/ajnr.A3595

View details for PubMedID 23744690

Abstract

Embryonal tumors of the central nervous system (CNS) share histological features and were therefore initially grouped as primitive neuroectodermal tumors (PNET) and treated similarly. We sought to determine the relapse patterns of specific embryonal CNS tumors. We conducted a historical cohort study of children diagnosed with CNS embryonal tumors from January 2000 to December 2011 in two pediatric neuro-oncology centers. Patients of 21years of age or younger at time of presentation with a diagnosis of medulloblastoma, supratentorial PNET, pineoblastoma or atypical teratoid/rhabdoid tumor (ATRT) and at least one surveillance MRI were included. A total of 133 patients met inclusion criteria and 49 (37%) patients relapsed during the observation period. The majority (79%) of sPNET relapses were local, whereas all (100%) PB relapses were associated with diffuse leptomeningeal disease. Relapse patterns for MB were more diverse with local recurrence in 27%, distant recurrence in 35% and diffuse leptomeningeal disease in 38%. The frequency of relapses involving the spine differed (p<0.001) between tumor types (MB 28/55 [51%], sPNET 3/33 [9%], ATRT 3/7 [43%] and PB 12/12 [100%]). No sPNET patients had isolated spinal relapse (0/14). Embryonal tumors were found to have divergent patterns of recurrence. While medulloblastoma has variable relapse presentations, sPNET relapses locally and pineoblastoma recurs with diffuse leptomeningeal disease involving the spine. These results point toward possibly new upfront treatment stratification among embryonal tumors in accordance with relapse pattern.

View details for DOI 10.1007/s11060-013-1213-4

View details for PubMedID 23921420

Abstract

Object Focal hemosiderin deposition (FHD) is commonly observed on brain MRI scans of patients treated for childhood medulloblastoma (MB). The authors sought to determine the clinical significance of FHD and its relationship to patient age, radiation dose, and cognitive outcomes. Methods A single-institution retrospective study of 93 MB patients at Lucile Packard Children's Hospital at Stanford from 1998 to 2011 identified 41 patients with a negative baseline MRI scan and at least 2 posttreatment MRI scans obtained with T2* gradient recalled echo (GRE). The number and cumulative rate of FHDs detectable by GRE were compared between patients aged 6 years and younger (early age) and aged 7-21 years (late age) at the time of radiotherapy (RT) and between low-dose (1800-2340 cGy) and high-dose (2920-3960 cGy) RT. Results The median age at MB diagnosis was 7.3 years (range 0.9-21.0 years), the median clinical follow-up period was 5.8 years (range 0.8-13.4 years), and the median 5-year overall survival was 81% 7%. Of 30 school-aged children with MB, 21 (70%) required special education, and the median IQ of 10 tested patients was 100 (range 50-118). Thirty-three patients (80%) had FHD after a median latency of 1.9 years (range 0.1-5.9 years). Ninety-four percent (436 of 466) of the lesions arose in the supratentorial region of the brain, whereas 29 (6%) resided in the brainstem or the cerebellum. No spinal lesions were observed on routine spine MRI scans using T2 fast spin echo imaging. The mean cumulative lesion rate per year was 2.23 3.05, and this rate was higher in older children at the time of RT compared with younger children (3.23 vs 0.67 per year, p = 0.002) but did not differ among different RT doses (p = 0.395). A child's IQ or need for special education showed no significant correlation with the rate of lesion development or number of lesions. None of the lesions resulted in symptomatic hemorrhage that required surgical intervention. Conclusions More FHD was observed in children treated for MB at the older ages than in those treated at the younger ages. There was no significant association of the incidence of FHD with radiation dose or cognitive outcomes, and none of the lesions required surgical intervention.

View details for DOI 10.3171/2013.7.PEDS1330

View details for PubMedID 23992236

Abstract

BACKGROUND AND PURPOSE:Neurofibromatosis type 1 is associated with increased risk for stroke, cerebral vasculopathy, and neurocognitive deficits, but underlying hemodynamic changes in asymptomatic children remain poorly understood. We hypothesized that children with neurofibromatosis type 1 have decreased cerebral blood flow.MATERIALS AND METHODS:Arterial spin-labeled CBF was measured in 14 children with neurofibromatosis type 1 (median age, 9.7 years; mean, 10.2 years; range, 22 months to 18 years) and compared with age-matched control subjects on 3T MR imaging. Three-dimensional pseudocontinuous spin-echo arterial spin-labeled technique was used. Measurements were obtained at cortical gray matter of bilateral cerebral hemispheres and centrum semiovale by use of the ROI method. Comparison by Mann-Whitney test was used, with Bonferroni-adjusted P values .004 judged as significant.RESULTS:We identified 7 of 12 areas with significantly diminished arterial spin-labeled CBF in patients with neurofibromatosis type 1 compared with control subjects. These areas included the anterior cingulate gyrus (P = .001), medial frontal cortex (P = .004), centrum semiovale (P = .004), temporo-occipital cortex (P = .002), thalamus (P = .001), posterior cingulate gyrus (P = .002), and occipital cortex (P = .001). Among patients with neurofibromatosis type 1, there were no significant differences in these regions on the basis of the presence of neurofibromatosis type 1 spots or neurocognitive deficits.CONCLUSIONS:Reduced cerebral perfusion was seen in children with neurofibromatosis type 1, particularly in the posterior circulation and the vascular borderzones of the middle and posterior cerebral arteries.

View details for DOI 10.3174/ajnr.A3649

View details for Web of Science ID 000329848800034

View details for PubMedID 23764727

Abstract

Optic pathway glioma (OPG) has an unpredictable course, with poor correlation between conventional imaging features and tumor progression. We investigated whether diffusion-weighted MRI (DWI) predicts the clinical behavior of these tumors. Twelve children with OPG (median age 2.7years; range 0.4-6.2years) were followed for a median 4.4years with DWI. Progression-free survival (time to requiring therapy) was compared between tumors stratified by apparent diffusion coefficient (ADC) from initial pre-treatment scans. Tumors with baseline ADC greater than 1,40010(-6)mm(2)/s required treatment earlier than those with lower ADC (log-rank p=0.002). In some cases, ADC increased leading up to treatment, and declined following treatment with surgery, chemotherapy, or radiation. Baseline ADC was higher in tumors that eventually required treatment (1,56219210(-6)mm(2)/s), compared with those conservatively managed (1,12311410(-6)mm(2)/s) (Kruskal-Wallis test p=0.013). Higher ADC predicted earlier tumor progression in this cohort and in some cases declined after therapy. Evaluation of OPG with DWI may therefore be useful for predicting tumor behavior and assessing treatment response.

View details for DOI 10.1007/s11060-013-1140-4

View details for PubMedID 23673514

Abstract

This case series assesses white matter microstructure in 3 adolescents born preterm with nonshunted ventricular dilation secondary to intraventricular hemorrhage. Subjects (ages 12-17 years, gestational age 26-29 weeks, birth weight 825-1624 g) were compared to 3 full-term controls (13-17 years, 39-40 weeks, 3147-3345 g) and 3 adolescents born preterm without ventricular dilation (10-13 years, 26-29 weeks, 630-1673 g). Tractography using a 2 region of interest method reconstructed the following white matter tracts: superior longitudinal/arcuate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, and corticospinal tract. Subjects showed increased fractional anisotropy and changes in the pattern of fractional anisotropy along the trajectory of tracts adjacent to the lateral ventricles. Tensor shape at areas of increased fractional anisotropy demonstrated increased linear anisotropy at the expense of planar and spherical anisotropy. These findings suggest increased axonal packing density and straightening of fibers secondary to ventricular enlargement.

View details for DOI 10.1177/0883073812449693

View details for PubMedID 22859695

Abstract

Sturge-Weber syndrome is a neurocutaneous disorder associated with vascular abnormalities in the skin, eye, and brain leading to both acute and chronic cerebral hypoperfusion and, in some affected children, brain injury. Aspirin can reduce stroke-like events and seizure episodes and prevent further brain injuries in these patients. Although a few cases of intracranial hemorrhage in patients with Sturge-Weber syndrome have been reported, prior reports have not discussed this complication with regard to particular therapies. The authors present a toddler with Sturge-Weber syndrome who developed a subdural hematoma in the setting of a mechanical fall with minor head trauma. They discuss the possible role of aspirin in contributing to, or perhaps protecting against, intracranial hemorrhage in patients with Sturge-Weber syndrome. Further data are needed to establish the utility of aspirin in Sturge-Weber syndrome.

View details for DOI 10.1177/0883073812449514

View details for PubMedID 22805242

View details for DOI 10.2214/AJR.12.9854

View details for PubMedID 23617511

View details for DOI 10.3174/ajnr.A3333

View details for PubMedID 23124635

Abstract

To compare the diagnostic value of magnetic resonance (MR) imaging and ophthalmoscopy for staging of retinoblastoma.MR and ophthalmoscopic images of 36 patients who underwent enucleation were evaluated retrospectively following institutional review board approval. Histopathology being the standard of reference, the sensitivity and specificity of both diagnostic modalities were compared regarding growth pattern, iris neoangiogenesis, retinal detachment, vitreous seeds and optic nerve invasion. Data were analysed via McNemar's test.Both investigations showed no significant difference in accuracy for the detection of different tumour growth patterns (P = 0.80). Vitreous seeding detection was superior by ophthalmoscopy (P < 0.001). For prelaminar optic nerve invasion, MR imaging showed similar sensitivity as ophthalmoscopy but increased specificity of 40 % (CI 0.12-0.74) vs. 20 % (0.03-0.56). MR detected optic nerve involvement past the lamina cribrosa with a sensitivity of 80 % (0.28-0.99) and a specificity of 74 % (0.55-0.88). The absence of optic nerve enhancement excluded histopathological infiltration, but the presence of optic nerve enhancement included a high number of false positives (22-24 %).Ophthalmoscopy remains the method of choice for determining extent within the globe while MR imaging is useful for evaluating extraocular tumour extension. Thus, both have their own strengths and contribute uniquely to the staging of retinoblastoma. Ophthalmoscopy: method of choice for determining extent of retinoblastoma within the globe. MR imaging provides optimal evaluation of extrascleral and extraocular tumour extension. Positive enhancement of the optic nerve on MRI does not necessarily indicate involvement.

View details for DOI 10.1007/s00330-012-2707-8

View details for Web of Science ID 000317427500015

View details for PubMedID 23160663

Abstract

Chordoma and chondrosarcoma of the skull base are rare tumors with overlapping presentations and anatomic imaging features but different prognoses. We hypothesized that these tumors might be distinguished by using diffusion-weighted MR imaging.We retrospectively reviewed 19 patients with pathologically confirmed chordoma or chondrosarcoma who underwent both conventional and diffusion-weighted MR imaging. Differences in distributions of ADC were assessed by the Kruskal-Wallis test. Associations between histopathologic diagnosis and conventional MR imaging features (T2 signal intensity, contrast enhancement, and tumor location) were assessed with the Fisher exact test.Chondrosarcoma was associated with the highest mean ADC value (2051 261 10(-6) mm(2)/s) and was significantly different from classic chordoma (1474 117 10(-6) mm(2)/s) and poorly differentiated chordoma (875 100 10(-6) mm(2)/s) (P < .001). Poorly differentiated chordoma was characterized by low T2 signal intensity (P = .001), but other conventional MR imaging features of enhancement and/or lesion location did not reliably distinguish these tumor types.Diffusion-weighted MR imaging may be useful in assessing clival tumors, particularly in differentiating chordoma from chondrosarcoma. A prospective study of a larger cohort will be required to determine the value of ADC in predicting histopathologic diagnosis.

View details for DOI 10.3174/ajnr.A3333

View details for PubMedID 23124635

Abstract

We hypothesized that the apparent diffusion coefficient (ADC) and other MRI features can be used to predict medulloblastoma histologic subtypes, as defined by the World Health Organization (WHO) in WHO Classification of Tumours of the Central Nervous System.A retrospective review of pediatric patients with medulloblastoma between 1989 and 2011 identified 38 patients with both pretreatment MRI and original pathology slides. The mean and minimum tumor ADC values and conventional MRI features were compared among medulloblastoma histologic subtypes.The cohort of 38 patients included the following histologic subtypes: 24 classic medulloblastomas, nine large cell (LC) or anaplastic medulloblastomas, four desmoplastic medulloblastomas, and one medulloblastoma with extensive nodularity. The median age at diagnosis was 8 years (range, 1-21 years) and the median follow-up time was 33 months (range, 0-150 months). The mean ADC ( 10(-3) mm(2)/s) was lower in classic medulloblastoma (0.733 0.046 [SD]) than in LC or anaplastic medulloblastoma (0.935 0.127) (Mann-Whitney test, p = 0.004). Similarly, the minimum ADC was lower in classic medulloblastoma (average SD, 0.464 0.056) than in LC or anaplastic medulloblastoma (0.630 0.053) (p = 0.004). The MRI finding of focal cysts correlated with the classic and desmoplastic subtypes (Fisher exact test, p = 0.026). Leptomeningeal enhancement positively correlated with the LC or anaplastic medulloblastoma subtype and inversely correlated with the classic medulloblastoma and desmoplastic medulloblastoma subtypes (p = 0.04). Ring enhancement correlated with tumor necrosis (p = 0.022) and with the LC or anaplastic medulloblastoma histologic subtype (p < 0.001).The LC or anaplastic medulloblastoma subtype was associated with increased ADC and with ring enhancement, the latter of which correlated with tumor necrosis. These features could be considered in the evaluation of high-risk medulloblastoma subtypes.

View details for DOI 10.2214/AJR.12.9249

View details for PubMedID 23521467

Abstract

Children born preterm are at risk for deficits in language and reading. They are also at risk for injury to the white matter of the brain. The goal of this study was to determine whether performance in language and reading skills would be associated with white matter properties in children born preterm and full-term. Children born before 36 weeks gestation (n=23, meanSD age 12.52.0 years, gestational age 28.72.5 weeks, birth weight 1184431 g) and controls born after 37 weeks gestation (n=19, 13.12.1 years, 39.31.0 weeks, 3178413 g) underwent a battery of language and reading tests. Diffusion tensor imaging (DTI) scans were processed using tract-based spatial statistics to generate a core white matter skeleton that was anatomically comparable across participants. Fractional anisotropy (FA) was the diffusion property used in analyses. In the full-term group, no regions of the whole FA-skeleton were associated with language and reading. In the preterm group, regions of the FA-skeleton were significantly associated with verbal IQ, linguistic processing speed, syntactic comprehension, and decoding. Combined, the regions formed a composite map of 22 clusters on 15 tracts in both hemispheres and in the ventral and dorsal streams. ROI analyses in the preterm group found that several of these regions also showed positive associations with receptive vocabulary, verbal memory, and reading comprehension. Some of the same regions showed weak negative correlations within the full-term group. Exploratory multiple regression in the preterm group found that specific white matter pathways were related to different aspects of language processing and reading, accounting for 27-44% of the variance. The findings suggest that higher performance in language and reading in a group of preterm but not full-term children is associated with higher fractional anisotropy of a bilateral and distributed white matter network.

View details for DOI 10.1016/j.neuropsychologia.2012.10.014

View details for PubMedID 23088817

Abstract

To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high-quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts.We implemented an in-house built generalized autocalibrating partially parallel acquisitions (GRAPPA)-accelerated diffusion tensor (DT) echo-planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion.The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high-quality data for routine evaluation.This work suggests that, apart from the rare instance of continuous motion throughout the scan, high-quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data.

View details for DOI 10.1002/jmri.23710

View details for Web of Science ID 000308884300022

View details for PubMedID 22689498

View details for PubMedCentralID PMC3443529

Abstract

Magnetic resonance imaging is commonly used in diagnosis and surveillance for optic pathway glioma (OPG). The authors investigated the role of diffusion tensor (DT) tractography in assessing the location of visual pathway fibers in the presence of tumor.Data in 10 children with OPG were acquired using a 3T MRI generalized autocalibrating parallel acquisitions DT-echo planar imaging sequence (25 isotropic directions with a b value of 1000 seconds/mm(2), slice thickness 3 mm). Fiber tractography was performed, with seed regions placed within the optic chiasm and bilateral nerves on the coronal plane, including the tumor and surrounding normal-appearing tissue. Tracking was performed with a curvature threshold of 30.For prechiasmatic lesions, fibers either stopped abruptly at the tumor or traversed abnormally dilated nerve segments. Similar findings were seen with chiasmatic lesions, with an additional arrangement in which fibers diverged around the tumor. For each patient, DT tractography provided additional information about visual fiber arrangement in relation to the tumor that was not evident by using conventional MRI methods. Retrospective reconstruction of visual fibers in 1 patient with new postoperative hemianopia revealed an unexpected superior displacement of the optic tract that might have been helpful information had it been applied to preoperative planning or surgical navigation.Optic pathway DT tractography is feasible in patients with OPG and provides new information about the arrangement of visual fibers in relation to tumors that could be incorporated into surgical navigation for tumor biopsy or debulking procedures.

View details for DOI 10.3171/2012.7.PEDS1270

View details for PubMedID 22900485

Abstract

To use objective, nonverbal oculomotor tasks to assess executive function and infer the neural basis of impairments in preterm children.Cross-sectional study of preterm children age 9-16 years (n = 69; mean gestational age 29 weeks) and full-term controls (n = 43). Tasks assessed sensorimotor function (reflexive prosaccades); resistance to peripheral distracters (fixation); response inhibition, response preparation, and execution of a voluntary saccade (antisaccades); and spatial working memory (memory-guided saccades). Group differences were analyzed using ANOVA. We used linear regression to analyze the contributions of age, sex, gestational age, and white matter category to task performance.Preterm children did not differ from controls on basic sensorimotor function, response inhibition, and working memory. Compared with controls, preterm children showed greater susceptibility to peripheral distracters (P = .008) and were slower to initiate an inhibitory response (P = .003). Regression models showed contributions of age and white matter category to task performance.Preterm children show intact basic sensorimotor function and demonstrate difficulties in processes underlying executive control, including increased distractibility and prolonged response preparation. These limitations may reflect specific neural abnormalities in fronto-subcortical executive control of behavior.

View details for DOI 10.1016/j.jpeds.2012.02.037

View details for PubMedID 22480696

Abstract

Retinoblastoma is the most common intraocular childhood malignancy, with a prevalence of one in 18,000 children younger than 5 years old in the United States. In 80% of patients, retinoblastoma is diagnosed before the age of three, and in 95% of patients, retinoblastoma is diagnosed before the age of five. Although reports exist of retinoblastoma in adults, onset beyond 6 years of age is rare. Broadly, retinoblastoma may be classified into two groups: sporadic and heritable. In either case, the origin of the tumor is a biallelic mutation in primitive neuroepithelial cells. Although their details vary, several staging schemes are used to describe the extent of retinoblastoma according to the following four general criteria: intraocular location, extraocular (extraorbital) location, central nervous system disease, and systemic metastases. In the past decade, substantial changes have taken place in terms of staging and monitoring treatment in patients with retinoblastoma. Diagnosis and treatment of retinoblastoma involve a multidisciplinary approach, for which imaging is a vital component. Increasing awareness and concerns about the effects of radiation in patients with retinoblastoma have led to a shift away from external-beam radiation therapy and toward chemotherapy and locoregional treatment, as well as the establishment of magnetic resonance imaging as the most important imaging modality for diagnosis, staging, and treatment monitoring.

View details for DOI 10.1148/rg.325115176

View details for Web of Science ID 000308632900010

View details for PubMedID 22977020

Abstract

Diffusion tensor imaging (DTI) was used to evaluate white matter architecture after preterm birth. The goals were (1) to compare white matter microstructure in two cohorts of preterm- and term-born children; and (2) within preterm groups, to determine if sex, gestational age, birthweight, white matter injury score from conventional magnetic resonance imaging (MRI), or IQ was associated with DTI measures.Participants (n=121; 66 females, 55 males) were aged 9 to 16 years. They comprised 58 preterm children (site 1, n=25; and site 2, n=33) born at less than 36 weeks' gestation (mean 29.4 wks; birthweight 1289g) and 63 term children (site 1, n=40; site 2, n=23) born at more than 37 weeks' gestation. DTI was analyzed using tract-based spatial statistics. Diffusion measures were fractional anisotropy, axial, radial, and mean diffusivity.In no region of the white matter skeleton was fractional anisotropy lower in the preterm group at either site. Within the preterm groups, fractional anisotropy was significantly associated with white matter injury score, but not sex, gestational age, or birthweight. At site 1, fractional anisotropy was associated with IQ.DTI contributes to understanding individual differences after preterm birth but may not differentiate a relatively high-functioning group of preterm children from a matched group of term-born children.

View details for DOI 10.1111/j.1469-8749.2012.04378.x

View details for PubMedID 22803787

Abstract

RS-EPI has been suggested as an alternative approach to EPI for high-resolution DWI with reduced distortions. To determine whether RS-EPI is a useful approach for routine clinical use, we implemented GRAPPA-accelerated RS-EPI DWI at our pediatric hospital and graded the images alongside standard accelerated (ASSET) EPI DWI used routinely for clinical studies.GRAPPA-accelerated RS-EPI DWIs and ASSET EPI DWIs were acquired on 35 pediatric patients using a 3T system in 35 pediatric patients. The images were graded alongside each other by using a 7-point Likert scale as follows: 1, nondiagnostic; 2, poor; 3, acceptable; 4, standard; 5, above average; 6, good; and 7, outstanding.The following were the average scores for EPI and RS-EPI, respectively: resolution, 3.5/5.2; distortion level, 2.9/6.0; SNR, 3.4/4.1; lesion conspicuity, 3.3/5.9; and diagnostic confidence, 3.2/6.0. Overall, the RS-EPI had significantly improved diagnostic confidence and more reliably defined the extent and structure of several lesions. Although ASSET EPI scans had better SNR per scanning time, the higher spatial resolution as well as reduced blurring and distortions on RS-EPI scans helped to better reveal important anatomic details at the cortical-subcortical levels, brain stem, temporal and inferior frontal lobes, skull base, sinonasal cavity, cranial nerves, and orbits.This work shows the importance of both resolution and decreased distortions in the clinics, which can be accomplished by a combination of parallel imaging and alternative k-space trajectories such as RS-EPI.

View details for DOI 10.3174/ajnr.A2481

View details for Web of Science ID 000294275100023

View details for PubMedID 21596809

Abstract

Regular, chronic red cell transfusions (CTX) have been shown to be effective prophylaxis against stroke in sickle cell disease (SCD) in those at risk. Because serial brain imaging is not routinely performed, little is known about the impact of CTX on silent infarcts (SI) and cerebral vascular pathology. Thus, we retrospectively evaluated the magnetic resonance imaging reports of a cohort of SCD patients who were prescribed CTX for either primary or secondary stroke prophylaxis. Seventeen patients with Hb SS were included (mean age 15 years, mean follow-up 4.3 years). Eight patients were on CTX for primary prophylaxis. New SI occurred in 17.6% of patients corresponding to an SI rate of 5.42 per 100 patient-years. Vasculopathy of the cerebral arteries was present in 65% of patients and progressed in 63% of these patients. Those who developed progressive vasculopathy were on CTX for an average of 8 years before lesions progressed. Patients on CTX for secondary prophylaxis had more SIs and evidence of progressive vascular disease than patients on CTX for primary prophylaxis. We conclude that adherence to CTX does not necessarily prevent SI or halt cerebral vasculopathy progression, especially in those with a history of overt stroke.

View details for DOI 10.1002/ajh.21901

View details for PubMedID 21117059

Abstract

Chordomas are malignant neoplasms that typically arise in the axial spine and primarily affect adults. When chordomas arise in pediatric patients they are more likely to display unusual histological features and aggressive behavior. We noted the absence of SMARCB1/INI1 expression by immunohistochemistry in an index case of poorly differentiated chordoma of the sacrum, leading us to further examine SMARCB1/INI1 expression as well as that of brachyury, a highly specific marker of notochordal differentiation, in 3 additional poorly differentiated chordomas of the clivus, 10 typical chordomas, and 8 atypical teratoid/rhabdoid tumors (AT/RTs). All 4 poorly differentiated chordomas and all AT/RTs lacked nuclear expression of SMARCB1/INI1, while the 10 typical chordomas maintained strong nuclear SMARCB1/INI1 immunoreactivity. All 10 typical and 4 poorly differentiated chordomas expressed brachyury; all 8 AT/RTs were brachyury immunonegative. Cytogenetic evaluation utilizing FISH probes near the SMARCB1/INI1 locus on chromosome 22q was also performed in all of the poorly differentiated chordomas in this series. Three of the four poorly differentiated chordomas had evidence for deletion of this region by FISH. Analysis of the SMARCB1/INI1 gene sequence was performed using formalin-fixed paraffin-embedded tissue in all cases and no point mutations were observed. In summary, all poorly differentiated chordomas in this series showed the absence of SMARCB1/INI1 expression, and were reliably distinguished from AT/RTs, clinically by their characteristic primary sites of origin and pathologically by strong nuclear brachyury expression. Our findings reveal a likely role for SMARCB1/INI1 in a subset of chordomas with aggressive features.

View details for DOI 10.1007/s00401-010-0767-x

View details for PubMedID 21057957

Abstract

Langerhans cell histiocytosis (LCH) is a rare proliferative disorder that occurs most commonly in the pediatric population as a result of pathological clonal proliferation of Langerhans cells with subsequent damage and destruction to surrounding tissue. Clinically, LCH presents in a variety of ways, which often results in prolonged time to diagnosis and subsequently poorer outcomes. In this case report, the authors describe an unusually early presentation of multisystem LCH in a patient at birth, which resulted in a 5-month delay to diagnosis and treatment. This patient presented both atypically young and with an uncommon initial manifestation of multisystem disease with multiple soft-tissue swellings rather than early skin involvement. Additionally, this patient had an unusual radiographic appearance with biparietal skull destruction on initial skull radiographs and biparietal soft-tissue lesions on CT resembling cephalohematoma at 3 months of age. The clinical and radiological evaluation, pathology, and treatment strategies are discussed, with particular attention paid to the importance of further workup of atypical nonresolving cephalohematomas to prevent disease progression and poorer outcomes.

View details for DOI 10.3171/2010.7.PEDS10149

View details for PubMedID 20887116

Abstract

Curative therapy for childhood cancer has dramatically improved over past decades. Therapeutic radiation has been instrumental in this success. Unfortunately, irradiation is associated with untoward effects, including stroke and other cerebrovascular disease (CVD). The Children's Oncology Group (COG) has developed guidelines for screening survivors at risk for persistent or late sequelae of cancer therapy.This review summarizes the pathophysiology and relevant manifestations of radiation-induced CVD and outlines the specific patient groups at risk for early-onset stroke. The reader will be alerted to the availability of the COG recommendations for monitoring, and, when applicable, specific screening and treatment recommendations will be highlighted.A multidisciplinary task force critically reviewed the existing literature and scored the evidence to establish the current COG guidelines for monitoring health of survivors treated with head and neck irradiation.Previous head and neck exposure to therapeutic radiation is associated with latent CVD and increased risk for stroke in some patient groups. Common manifestations of radiation-induced CVD includes steno-occlusive disease, moyamoya, aneurysm, mineralizing microangiopathy, vascular malformations, and strokelike migraines.Risk for stroke is increased in survivors of pediatric CNS tumors, Hodgkin lymphoma, and acute lymphoblastic leukemia who received radiation to the brain and/or neck. As the population of survivors ages, vigilance for stroke and cerebrovascular disease needs to continue based on specific exposures during curative cancer therapy.

View details for DOI 10.1212/WNL.0b013e3181c17ea8

View details for Web of Science ID 000272205200015

View details for PubMedID 19812380

View details for PubMedCentralID PMC2788797

Abstract

The aim was to investigate the potential impact of positron emission tomography (PET)/computed tomography (CT) as compared to PET and CT on the staging of patients with indolent lymphoma.PET/CTs from 45 patients with indolent lymphoma undergoing staging or restaging were studied. Clinical follow-up, additional imaging, and histology served as the gold standard.PET/CT correctly diagnosed 92 nodal regions as positive for lymphomatous involvement and 458 as disease free vs 68 and 449 for PET and 64 and 459 for CT, respectively. The respective sensitivities, specificities, and accuracies were 99%, 100%, and 99.8% for PET/CT, 68%, 97.5%, and 92.2% for PET, and 70%, 100%, and 94.7% for CT. PET/CT performed significantly better than PET (p < 0.001 for sensitivity, specificity, and accuracy) and CT (p < 0.001 for sensitivity and accuracy). PET/CT also correctly identified significantly more extra-nodal lesions (22) than CT (14) and PET (nine).PET/CT provides significantly more accurate information compared to PET and CT for the staging and re-staging of patients with indolent lymphoma.

View details for DOI 10.1007/s11307-009-0200-9

View details for Web of Science ID 000266830700009

View details for PubMedID 19326177

View details for PubMedCentralID PMC2693779

Abstract

Human herpesvirus 6 has rarely been identified as a cause of encephalitis in immunocompetent adults. We describe a patient who had severe encephalomyelitis, hypoglycorrhachia, and human herpesvirus 6 identified in his cerebrospinal fluid and serum and who recovered after treatment with foscarnet and ganciclovir. Human herpesvirus 6 should be considered in immunocompetent patients with encephalitis.

View details for DOI 10.1086/593315

View details for PubMedID 18991511

Abstract

(18)F-FDG PET has a high accuracy for re-staging of head and neck cancer. The purpose of this study was to determine whether the diagnostic accuracy can be further improved with integrated PET/CT.Forty-nine patients with a mean age of 59+/-18 years were studied retrospectively. Histo-pathological verification was available either from complete tumor resection with or without lymph node dissection (n=27) or direct endoscopic biopsy (n=16) or ultrasound guided biopsy (n=6). Two reviewers blinded to the pathological findings read all PET images in consensus. An experienced radiologist was added for the interpretation of the PET/CT images.Tissue verification was available for 110 lesions in 49 patients. Sixty-seven lesions (61%) were biopsy positive and 43 (39%) were negative for malignant disease. PET and PET/CT showed an overall accuracy for cancer detection of 84 and 88% (p=0.06), respectively. Sensitivity and specificity for PET were 78 and 93% versus 84 (p=NS) and 95% (p=NS) with PET/CT. A patient-by-patient analysis yielded a sensitivity, specificity and accuracy for PET of 80, 56 and 76%, compared to 88% (p=NS), 78% (p=NS) and 86% (p=0.06) for PET/CT.The results of this study indicate that PET/CT does not significantly improve the detection of recurrence of head and neck cancer. However, a trend towards improved accuracy was observed (p=0.06).

View details for DOI 10.1016/j.ejrad.2006.11.037

View details for Web of Science ID 000246613700010

View details for PubMedID 17223003

Abstract

The incidence of malignancy associated with subcentimeter pulmonary nodules (micronodules) in patients with malignant disease has been reported to be as high as 58%. Thus, detection of small lung nodules is important for appropriate staging of lung cancer. Because of respiratory motion, small parenchymal lung lesions can be missed on CT acquired during shallow breathing. Micronodules are usually too small to be characterized reliably with 18F-FDG PET. We aimed to determine the incidence of missed pulmonary micronodules on PET/CT studies acquired during shallow breathing.The study included 142 consecutive cancer patients (62 male and 80 female; mean age, 54 y) who underwent whole-body PET/CT during shallow breathing and breath-hold CT of the chest during maximal inspiration. CT findings were reviewed independently, and noncalcified nodules missed on the shallow-breathing scan were evaluated for size, location, and metabolic activity.Breath-hold chest CT detected an additional 125 parenchymal lung nodules (mean size, 3.4 +/- 1.6 mm; range, 1-9 mm) in 48 (34%) of the 142 patients. In these patients, 3 nodules, on average, were missed during shallow breathing. In 18 patients (13%), micronodules were identified exclusively on breath-hold images. None of the missed nodules demonstrated 18F-FDG uptake.Acquisition of standard PET/CT chest images during shallow breathing is inadequate for comprehensive cancer staging.

View details for Web of Science ID 000235283500030

View details for PubMedID 16455636