Quantitative Sodium (23Na) MRI in Pediatric Gliomas: Initial Experience.

Background: 23Na MRI correlates with tumor proliferation, and studies in pediatric patients are lacking. The purpose of the study: (1) to compare total sodium concentration (TSC) between pediatric glioma and non-neoplastic brain tissue using 23Na MRI; (2) compare tissue conspicuity of bound sodium concentration (BSC) using 23Na MRI dual echo relative to TSC imaging. Methods: TSC was measured in: (1) non-neoplastic brain tissues and (2) three types of manually segmented gliomas (diffuse intrinsic brainstem glioma (DIPG), recurrent supratentorial low-grade glioma (LGG), and high-grade glioma (HGG)). In a subset of patients, serial changes in both TSC and BSC (dual echo 23Na MRI) were assessed. Results: Twenty-six pediatric patients with gliomas (median age of 12.0 years, range 4.9−23.3 years) were scanned with 23Na MRI. DIPG treated with RT demonstrated higher TSC values than the uninvolved infratentorial tissues (p < 0.001). Recurrent supratentorial LGG and HGG exhibited higher TSC values than the uninvolved white matter (WM) and gray matter (GM) (p < 0.002 for LGG, and p < 0.02 for HGG). The dual echo 23Na MRI suppressed the sodium signal within both CSF and necrotic foci. Conclusion: Quantitative 23Na MRI of pediatric gliomas demonstrates a range of values that are higher than non-neoplastic tissues. Dual echo 23Na MRI of BCS improves tissue conspicuity relative to TSC imaging.

Localization of epileptic seizure focus by computerized analysis of fMRI recordings.

By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovative machine learning techniques involve intensive analysis of large matrices of mutual information coefficients between pairs of anatomically identified cortical regions. Drastic selection of pairs of regions with biologically significant inter-connectivity provides efficient inputs for our multi-layer perceptron (MLP) classifier. By imposing rigorous parameter parsimony to avoid overfitting, we construct a small-size MLP with very good percentages of successful classification.

Normalization enhances brain network features that predict individual intelligence in children with epilepsy.

BACKGROUND AND PURPOSE: Architecture of the cerebral network has been shown to associate with IQ in children with epilepsy. However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children with epilepsy, has yet to be achieved. We compared two network normalization strategies in terms of their ability to optimize subject-level inferences on the relationship between brain network architecture and brain function. MATERIALS AND METHODS: Patients with epilepsy and resting state fMRI were retrospectively identified. Brain network nodes were defined by anatomic parcellation, first in patient space (nodes defined for each patient) and again in template space (same nodes for all patients). Whole-brain weighted graphs were constructed according to pair-wise correlation of BOLD-signal time courses between nodes. The following metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Metrics computed on graphs in patient space were normalized to the same metric computed on a random network of identical size. A machine learning algorithm was used to predict patient IQ given access to only the network metrics. RESULTS: Twenty-seven patients (8-18 years) comprised the final study group. All brain networks demonstrated expected small world properties. Accounting for intrinsic population heterogeneity had a significant effect on prediction accuracy. Specifically, transformation of all patients into a common standard space as well as normalization of metrics to those computed on a random network both substantially outperformed the use of non-normalized metrics. CONCLUSION: Normalization contributed significantly to accurate subject-level prediction of cognitive function in children with epilepsy. These findings support the potential for quantitative network approaches to contribute clinically meaningful information in children with neurological disorders.

Mutual Information Better Quantifies Brain Network Architecture in Children with Epilepsy.

PURPOSE: Metrics of the brain network architecture derived from resting-state fMRI have been shown to provide physiologically meaningful markers of IQ in children with epilepsy. However, traditional measures of functional connectivity (FC), specifically the Pearson correlation, assume a dominant linear relationship between BOLD time courses; this assumption may not be valid. Mutual information is an alternative measure of FC which has shown promise in the study of complex networks due to its ability to flexibly capture association of diverse forms. We aimed to compare network metrics derived from mutual information-defined FC to those derived from traditional correlation in terms of their capacity to predict patient-level IQ. MATERIALS AND METHODS: Patients were retrospectively identified with the following: (1) focal epilepsy; (2) resting-state fMRI; and (3) full-scale IQ by a neuropsychologist. Brain network nodes were defined by anatomic parcellation. Parcellation was performed at the size threshold of 350 mm2, resulting in networks containing 780 nodes. Whole-brain, weighted graphs were then constructed according to the pairwise connectivity between nodes. In the traditional condition, edges (connections) between each pair of nodes were defined as the absolute value of the Pearson correlation coefficient between their BOLD time courses. In the mutual information condition, edges were defined as the mutual information between time courses. The following metrics were then calculated for each weighted graph: clustering coefficient, modularity, characteristic path length, and global efficiency. A machine learning algorithm was used to predict the IQ of each individual based on their network metrics. Prediction accuracy was assessed as the fractional variation explained for each condition. RESULTS: Twenty-four patients met the inclusion criteria (age: 8-18 years). All brain networks demonstrated expected small-world properties. Network metrics derived from mutual information-defined FC significantly outperformed the use of the Pearson correlation. Specifically, fractional variation explained was 49% (95% CI: 46%, 51%) for the mutual information method; the Pearson correlation demonstrated a variation of 17% (95% CI: 13%, 19%). CONCLUSION: Mutual information-defined functional connectivity captures physiologically relevant features of the brain network better than correlation. CLINICAL RELEVANCE: Optimizing the capacity to predict cognitive phenotypes at the patient level is a necessary step toward the clinical utility of network-based biomarkers.

Comparison of the diagnostic accuracy of PET/MRI to PET/CT-acquired FDG brain exams for seizure focus detection: a prospective study.

BACKGROUND: There is great interest in positron emission tomography (PET)/magnetic resonance (MR) as a clinical tool due to its capacity to provide diverse diagnostic information in a single exam. OBJECTIVE: The goal of this exam is to compare the diagnostic accuracy of PET/MR-acquired [F-18]2-fluoro-2-deoxyglucose (FDG) brain exams to that of PET/CT with respect to identifying seizure foci in children with localization-related epilepsy. MATERIALS AND METHODS: Institutional Review Board approval and informed consent were obtained for this Health Insurance Portability and Accountability Act-compliant, prospective study. All patients referred for clinical FDG-PET/CT exams of the brain at our institution for a diagnosis of localization-related epilepsy were prospectively recruited to undergo an additional FDG-PET acquisition on a tandem PET/MR system. Attenuation-corrected FDG images acquired at PET/MR and PET/CT were interpreted independently by five expert readers. Readers were blinded to the scanner used for acquisition and attenuation correction as well as all other clinical and imaging data. A Likert scale scoring system (1-5) was used to assess image quality. The locale of seizure origin determined at multidisciplinary epilepsy surgery work rounds was considered the reference standard. Non-inferiority testing for paired data was used to compare the diagnostic accuracy of PET/MR to that of PET/CT. RESULTS: The final study population comprised 35 patients referred for a diagnosis of localization-related epilepsy (age range: 2-19 years; median: 11 years; 21 males, 14 females). Image quality did not differ significantly between the two modalities. The accuracy of PET/MR was not inferior to that of PET/CT for localization of a seizure focus (P=0.017). CONCLUSION: The diagnostic accuracy of FDG-PET images acquired on a PET/MR scanner and generated using MR-based attenuation correction was not inferior to that of PET images processed by traditional CT-based correction.

Repeatability of graph theoretical metrics derived from resting-state functional networks in paediatric epilepsy patients.

OBJECTIVE: To measure the repeatability of metrics that quantify brain network architecture derived from resting-state functional MRI in a cohort of paediatric patients with epilepsy. METHODS: We identified patients with: (1) epilepsy; (2) brain MRI at 3 T; (3) two identical resting-state functional MRI acquisitions performed on the same day. Undirected, weighted networks were constructed based on the resting-state time series using a range of processing parameters including parcellation size and graph threshold. The following topological properties were calculated: degree, strength, characteristic path length, global efficiency, clustering coefficient, modularity and small worldness. Based on repeated measures, we then calculated: (1) Pearson correlation coefficient; (2) intraclass correlation coefficient; (3) root-mean-square coefficient of variation; (4) repeatability coefficient; and (5) 95% confidence limits for change. RESULTS: 26 patients were included (age range: 4-21 years). Correlation coefficients demonstrated a highly consistent relationship between repeated observations for all metrics, and the intraclass correlation coefficients were generally in the excellent range. Repeatability in the data set was not significantly influenced by parcellation size. However, trends towards decreased repeatability were observed at higher graph thresholds. CONCLUSION: These findings demonstrate the reliability of network metrics in a cohort of paediatric patients with epilepsy. Advances in knowledge: Our results point to the potential for graph theoretical analyses of resting-state data to provide reliable markers of network architecture in children with epilepsy. At the level of an individual patient, change over time greater than the repeatability coefficient or 95% confidence limits for change is unlikely to be related to intrinsic variability of the method.

Metrics of brain network architecture capture the impact of disease in children with epilepsy.

BACKGROUND AND OBJECTIVE: Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional MRI to capture the impact of epilepsy on the developing brain. METHODS: Pediatric patients were retrospectively identified with: 1. Focal epilepsy; 2. Brain MRI at 3 Tesla, including resting state functional MRI; 3. Full scale IQ measured by a pediatric neuropsychologist. The cerebral cortex was parcellated into approximately 700 gray matter network nodes. The strength of a connection between two nodes was defined as the correlation between their resting BOLD signal time series. The following global network metrics were then calculated: clustering coefficient, transitivity, modularity, path length, and global efficiency. Epilepsy duration was used as an index for the cumulative impact of epilepsy on the brain. RESULTS: 45 patients met criteria (age: 4-19 years). After accounting for age of epilepsy onset, epilepsy duration was inversely related to IQ (p: 0.01). Epilepsy duration predicted by a machine learning algorithm on the basis of the five global network metrics was highly correlated with actual epilepsy duration (r: 0.95; p: 0.0001). Specifically, modularity and to a lesser extent path length and global efficiency were independently associated with epilepsy duration. CONCLUSIONS: We observed that a machine learning algorithm accurately predicted epilepsy duration based on global metrics of network architecture derived from resting state fMRI. These findings suggest that network metrics have the potential to form the basis for statistical models that translate quantitative imaging data into patient-level markers of cognitive deterioration.

Assessment of Sequential PET/MRI in Comparison With PET/CT of Pediatric Lymphoma: A Prospective Study.

OBJECTIVE: The objective of our study was to compare the diagnostic performance of sequential (18)F-FDG PET/MRI (PET/MRI) and (18)F-FDG PET/CT (PET/CT) in a pediatric cohort with lymphoma for lesion detection, lesion classification, and disease staging; quantification of FDG uptake; and radiation dose. SUBJECTS AND METHODS: For this prospective study of 25 pediatric patients with lymphoma, 40 PET/CT and PET/MRI examinations were performed after a single-injection dual-time-point imaging protocol. Lesions detected, lesion classification, Ann Arbor stage, and radiation dose were tabulated for each examination, and statistical evaluations were performed to compare the modalities. Quantification of standardized uptake values (SUVs) was performed for all lesions. All available examinations and clinical history were used as the reference standard. RESULTS: No statistically significant differences between PET/MRI and PET/CT were observed in lesion detection rates, lesion classification, or Ann Arbor staging. Fifty-four regions of focal uptake were observed on PET/MRI compared with 55 on PET/CT. Both modalities accurately classified 82% of the lesions relative to the reference standard. Disease staging based on PET/MRI was correct for 35 of the 40 studies, and disease staging based on PET/CT was correct for 35 of the 40 studies; there was substantial agreement between the modalities for disease staging (κ = 0.684; p < 0.001). PET SUVs were strongly correlated between PET/CT and PET/MRI (ρ > 0.72), although PET/MRI showed systematically lower SUV measurements. PET/MRI offered an average 45% reduction in radiation dose relative to PET/CT. CONCLUSION: In a pediatric cohort with lymphoma, sequential PET/MRI showed lesion detection, lesion classification, and Ann Arbor staging comparable to PET/CT. PET/MRI quantification of FDG uptake strongly correlated with PET/CT, but the SUVs were not interchangeable. PET/MRI significantly reduced radiation exposure and is a promising new alternative in the care of pediatric lymphoma patients.

Novel Association of Odontogenic Myxoma with Constitutional Chromosomal 1q21 Microduplication: Case Report and Review of the Literature.

Odontogenic myxoma (OM) is a rare, benign, and locally aggressive tumor. It tends to occur in the posterior maxilla and mandible and is often associated with root resorption and perforation of cortex. Histopathologically, there is a proliferation of spindle, bipolar, and stellate cells, with bland nuclei within a myxoid to infrequently fibromyxoid extracellular matrix. Long, thin residual bony trabeculae are often seen floating within the spindle cell proliferation because of the infiltrating nature of this tumor, and these trabeculae impart a "soap bubble" or "tennis-racket" radiologic appearance. No syndromic association of OM has been reported. Although similar histopathologic features are shared with cardiac myxoma and soft tissue myxoma, mutations in the GNAS gene have not been identified in OM to date, and only 2 of 17 OMs showed mutations in the PRKAR1A gene. In this report, we describe a case of OM in a patient with constitutional 1q21 microduplication, a locus that harbors genes encoding certain proteins in the cAMP-dependent protein kinase A (PKA) signaling pathway, including G-protein-coupled receptors and 1 phosphodiesterase interacting protein. Review of the literature describes the key clinical features and molecular pathogenesis of 1q21 microduplication, as well as highlighting the role of PKA signaling pathway in the pathogenesis of myxomas in general.

Comparison of Standardized Uptake Values in Normal Structures Between PET/CT and PET/MRI in a Tertiary Pediatric Hospital: A Prospective Study.

OBJECTIVE: The purpose of this study was to compare standardized uptake values (SUVs) of normal tissues using MR attenuation-corrected versus CT attenuation-corrected (18)F-FDG PET in a pediatric population. SUBJECTS AND METHODS: Thirty-five patients (21 boys; mean age, 13.3 years) referred for 47 PET/CT scans were recruited to undergo PET/MRI. MR attenuation correction was performed using an automated three-segment model. ROIs were drawn over nine normal structures to estimate SUV(min), SUV(mean), and SUV(max). Pearson rank correlation coefficients were calculated to compare SUVs obtained from MR and CT attenuation correction. In nine patients who underwent multiple PET/MRI studies, coefficients of variance and intraclass correlation coefficients were calculated to evaluate intrapatient SUV(max) variation. RESULTS: Mean (± SD) time to imaging after FDG injection was 108 ± 17 minutes for PET/CT and 61 ± 6 minutes for PET/MRI. PET/MRI SUVs in all tissues were lower than those for PET/CT (mean difference, -28.9% ± 31.1%; p < 0.05). Very high or high correlation between PET/MRI and PET/CT SUV(max) was found in brain (r = 0.72), myocardium (r = 0.95), and bone marrow (r = 0.85) (p < 0.001). Moderate correlation was found in liver (r = 0.54), fat (r = 0.41), mean blood pool (r = 0.40), and psoas muscle (r = 0.38) (p < 0.01). Weak correlation was found in lung (r = 0.12) and iliacus muscle (r = 0.12). Compared with PET/CT, PET/MRI systematically undermeasured SUV. In nine patients who underwent multiple PET/MRI examinations, moderate or strong agreement was found in the SUV(max) of six of nine tissues, similar to the corresponding PET/CT examinations. CONCLUSION: Our study showed overall high correlation for SUV measurements obtained from MR attenuation correction compared with CT attenuation correction, although PET/MRI underestimated SUV compared with PET/CT. SUVs measured from PET/MRI indicated good intrapatient reliability.

Qualitative FDG PET Image Assessment Using Automated Three-Segment MR Attenuation Correction Versus CT Attenuation Correction in a Tertiary Pediatric Hospital: A Prospective Study.

OBJECTIVE: The purpose of this study was to systematically evaluate the diagnostic quality of (18)F-FDG PET images generated using MR attenuation correction (MRAC) compared with those images generated using CT attenuation correction (CTAC) in a pediatric population. SUBJECTS AND METHODS: Forty-two patients (mean age, 12.8 years; percentage who were male, 57%) who were referred for 62 indicated whole-body PET/CT studies were prospectively recruited to undergo PET/MRI examinations during the same clinic visit in which PET/CT was performed. MRAC was performed using an automatic three-segment model. Three nuclear radiologists scored the diagnostic quality of the PET images generated by MRAC and CTAC using a Likert scale (range of scores, 1-5). Images graded with a score of 1-3 were considered clinically unacceptable, whereas images with a score of 4-5 were considered clinically acceptable. A Wilcoxon signed-rank test was used to compare differences in the grading of PET/MRI and PET/CT images. The Fisher exact test was used to evaluate potential differences in clinically acceptable image quality and the presence of artifact. Fleiss kappa statistics were used to examine interobserver agreement. RESULTS: There was no statistically significant difference in the proportion of PET images generated with MRAC and CTAC for which image quality was considered clinically acceptable. A total of 3.9% of PET assessments generated with MRAC were of unacceptable image quality, compared with 2.2% of PET images generated with CTAC. Two of the three radiologists who reviewed the PET images reported the presence of artifacts more often on MRAC-derived images, and they graded the mean quality of these images 0.48 and 0.29 points lower on the 5-point Likert scale than they graded the mean quality of CTAC-derived images (p < 0.0001). Interobserver agreement was fair (κ = 0.39). CONCLUSION: The diagnostic quality of PET images obtained from a pediatric population with the use of an automatic three-segmentation MRAC method was comparable to that of PET images obtained with the use of CTAC.

Failure to Identify the Left Arcuate Fasciculus at Diffusion Tractography Is a Specific Marker of Language Dysfunction in Pediatric Patients with Polymicrogyria.

BACKGROUND: Polymicrogyric cortex demonstrates interindividual variation with regard to both extent of dyslamination and functional capacity. Given the relationship between laminar structure and white matter fibers, we sought to define the relationship between polymicrogyria (PMG), intrahemispheric association pathways, and network function. METHODS: Each arcuate fasciculus (AF) was categorized as present or absent. Language was characterized by a pediatric neurologist. The presence of dysplastic cortex in the expected anatomic locations of Broca's (BA) and Wernicke's areas (WA) was evaluated by two pediatric neuroradiologists blinded to DTI and language data. RESULTS: 16 PMG patients and 16 age/gender-matched controls were included. All normative controls had an identifiable left AF. 6/7 PMG patients with dysplastic cortex within BA and/or WA had no left AF; PMG patients without involvement of these regions had a lower frequency of absence of the left AF (p < 0.006). All patients without a left AF had some degree of language impairment. PMG patients without a left AF had a significantly greater frequency of language impairment compared to those PMG patients with a left AF (p < 0.003). CONCLUSION: In patients with PMG (1) the presence of dysplastic cortex within WA and/or BA is associated with absence of the left AF and (2) absence of the left AF is associated with language impairment.

Ultra High-Resolution In vivo Computed Tomography Imaging of Mouse Cerebrovasculature Using a Long Circulating Blood Pool Contrast Agent.

Abnormalities in the cerebrovascular system play a central role in many neurologic diseases. The on-going expansion of rodent models of human cerebrovascular diseases and the need to use these models to understand disease progression and treatment has amplified the need for reproducible non-invasive imaging methods for high-resolution visualization of the complete cerebral vasculature. In this study, we present methods for in vivo high-resolution (19 µm isotropic) computed tomography imaging of complete mouse brain vasculature. This technique enabled 3D visualization of large cerebrovascular networks, including the Circle of Willis. Blood vessels as small as 40 µm were clearly delineated. ACTA2 mutations in humans cause cerebrovascular defects, including abnormally straightened arteries and a moyamoya-like arteriopathy characterized by bilateral narrowing of the internal carotid artery and stenosis of many large arteries. In vivo imaging studies performed in a mouse model of Acta2 mutations demonstrated the utility of this method for studying vascular morphometric changes that are practically impossible to identify using current histological methods. Specifically, the technique demonstrated changes in the width of the Circle of Willis, straightening of cerebral arteries and arterial stenoses. We believe the use of imaging methods described here will contribute substantially to the study of rodent cerebrovasculature.

Prenatal imaging of occipital encephaloceles.

INTRODUCTION: This retrospective study aims to describe systematically the fetal cerebral MR morphology in cases with occipital meningoencephaloceles using standard and advanced fetal MRI techniques. MATERIAL AND METHODS: The 1.5-tesla MR examinations (T1- and T2-weighted imaging, echo planar imaging, EPI, diffusion-weighted imaging, DWI) of 14 fetuses with occipital/parietal meningoencephaloceles were retrospectively analyzed for the classification of anatomic characteristics. A diffusion tensor sequence was performed in 5 cases. RESULTS: In 9/14 cases the occipital lobes were entirely or partially included in the encephalocele sac. Typical features of Chiari III malformation were seen in 6/14 cases. The displaced brain appeared grossly disorganized in 6/14. The brainstem displayed abnormal 'kinking'/rotation (3/14), a z-shape (1/14) and/or a molar tooth-like configuration of the midbrain (3/14). Tractography revealed the presence and position of sensorimotor tracts in 5/5 and the corpus callosum in 3/5. DWI was helpful in the identification of a displaced brain (in 8/9). EPI visualized the anatomy of draining cerebral veins in 7/9 cases. Clinical (9/14) and MRI (7/14) follow-up data are presented. DISCUSSION: Encephaloceles show a wide range of morphological heterogeneity. Fetal MRI serves as an accurate tool in the visualization of brainstem, white matter pathway and cerebral venous involvement and facilitates the detection of specific underlying syndromes such as ciliopathies.

Independent contribution of individual white matter pathways to language function in pediatric epilepsy patients.

BACKGROUND AND PURPOSE: Patients with epilepsy and malformations of cortical development (MCDs) are at high risk for language and other cognitive impairment. Specific impairments, however, are not well correlated with the extent and locale of dysplastic cortex; such findings highlight the relevance of aberrant cortico-cortical interactions, or connectivity, to the clinical phenotype. The goal of this study was to determine the independent contribution of well-described white matter pathways to language function in a cohort of pediatric patients with epilepsy. MATERIALS AND METHODS: Patients were retrospectively identified from an existing database of pediatric epilepsy patients with the following inclusion criteria: 1. diagnosis of MCDs, 2. DTI performed at 3 T, and 3. language characterized by a pediatric neurologist. Diffusion Toolkit and Trackvis (http://www.trackvis.org) were used for segmentation and analysis of the following tracts: corpus callosum, corticospinal tracts, inferior longitudinal fasciculi (ILFs), inferior fronto-occipital fasciculi (IFOFs), uncinate fasciculi (UFs), and arcuate fasciculi (AFs). Mean diffusivity (MD) and fractional anisotropy (FA) were calculated for each tract. Wilcoxon rank sum test (corrected for multiple comparisons) was used to assess potential differences in tract parameters between language-impaired and language-intact patients. In a separate analysis, a machine learning algorithm (random forest approach) was applied to measure the independent contribution of the measured diffusion parameters for each tract to the clinical phenotype (language impairment). In other words, the importance of each tract parameter was measured after adjusting for the contribution of all other tracts. RESULTS: Thirty-three MCD patients were included (age range: 3-18 years). Twenty-one patients had intact language, twelve had language impairment. All tracts were identified bilaterally in all patients except for the AF, which was not identified on the right in 10 subjects and not identified on the left in 11 subjects. MD and/or FA within the left AF, UF, ILF, and IFOF differed between language-intact and language-impaired groups. However, only parameters related to the left uncinate, inferior fronto-occipital, and arcuate fasciculi were independently associated with the clinical phenotype. CONCLUSIONS: Scalar metrics derived from the left uncinate, inferior fronto-occipital, and arcuate fasciculi were independently associated with language function. These results support the importance of these pathways in human language function in patients with MCDs.

Comparison of rapid cranial MRI to CT for ventricular shunt malfunction.

OBJECTIVES: To compare the accuracy of rapid cranial magnetic resonance imaging (MRI) with that of computed tomography (CT) for diagnosing ventricular shunt malfunction. METHODS: We performed a single-center, retrospective cohort study of children ≤21 years of age who underwent either rapid cranial MRI or cranial CT in the emergency department (ED) for evaluation of possible ventricular shunt malfunction. Each neuroimaging study was classified as "normal" (unchanged or decreased ventricle size) or "abnormal" (increased ventricle size). We classified a patient as having a ventricular shunt malfunction if operative revision for relief of mechanical causes of altered shunt flow was needed within 72 hours of initial ED evaluation. Our primary analysis tested noninferiority of the accuracy of rapid cranial MRI to CT for diagnosing shunt malfunction (noninferiority margin 10%). RESULTS: We included 698 ED visits for 286 unique patients, with a median age at visit of 10.0 years (interquartile range 5.9-15.5 years). Patients underwent CT in 336 (48%) or rapid cranial MRI in 362 (52%) of ED visits for evaluation of possible shunt malfunction. Patients had operative revision for ventricular shunt malfunction in 140 ED visits (20%). The accuracy of rapid cranial MRI was not inferior to that of CT scan for diagnosing ventricular shunt malfunction (81.8% MRI vs 82.4% CT; risk difference 2.0%; 95% confidence interval, -4.2% to 8.2%). CONCLUSIONS: Rapid cranial MRI was not inferior to CT for diagnosing ventricular shunt malfunction and offers the advantage of sparing a child ionizing radiation exposure.

Altered white matter connectivity and network organization in polymicrogyria revealed by individual gyral topology-based analysis.

Polymicrogyria (PMG) is a cortical malformation characterized by multiple small gyri and altered cortical lamination, which may be associated with disrupted white matter connectivity. However, little is known about the topological patterns of white matter networks in PMG. We examined structural connectivity and network topology using individual primary gyral pattern-based nodes in PMG patients, overcoming the limitations of an atlas-based approach. Structural networks were constructed from structural and diffusion magnetic resonance images in 25 typically developing and 14 PMG subjects. The connectivity analysis for different fiber groups divided based on gyral topology revealed severely reduced connectivity between neighboring primary gyri (short U-fibers) in PMG, which was highly correlated with the regional involvement and extent of abnormal gyral folding. The patients also showed significantly reduced connectivity between distant gyri (long association fibers) and between the two cortical hemispheres. In relation to these results, gyral node-based graph theoretical analysis revealed significantly altered topological organization of the network (lower clustering and higher modularity) and disrupted network hub architecture in cortical association areas involved in cognitive and language functions in PMG patients. Furthermore, the network segregation in PMG patients decreased with the extent of PMG and the degree of language impairment. Our approach provides the first detailed findings and interpretations on altered cortical network topology in PMG related to abnormal cortical structure and brain function, and shows the potential for an individualized method to characterize network properties and alterations in connections that are associated with malformations of cortical development.

Quantification and discrimination of abnormal sulcal patterns in polymicrogyria.

Polymicrogyria (PMG) is a malformation of cortical development characterized by an irregular gyral pattern and its diagnosis and severity have been qualitatively judged by visual inspection of imaging features. We aimed to provide a quantitative description of abnormal sulcal patterns for individual PMG brains using our sulcal graph-based analysis and examined the association with language impairment. The sulcal graphs were constructed from magnetic resonance images in 26 typical developing and 18 PMG subjects and the similarity between sulcal graphs was computed by using their geometric and topological features. The similarities between typical and PMG groups were significantly lower than the similarities measured within the typical group. Furthermore, more lobar regions were determined to be abnormal in most patients when compared with the visual diagnosis of PMG involvement, suggesting that PMG may have more global effects on cortical folding than previously expected. Among the PMG, the group with intact language development showed sulcal patterns more closely matched with the typical than the impaired group in the left parietal lobe. Our approach shows the potential to provide a quantitative means for detecting the severity and extent of involvement of cortical malformation and a greater understanding of genotype-phenotype and clinical-imaging features correlations.

A quantitative method for correlating observations of decreased apparent diffusion coefficient with elevated cerebral blood perfusion in newborns presenting cerebral ischemic insults.

In patients presenting with cerebral ischemic injury, the outcome of injured brain tissue quantified as decreased apparent diffusion coefficient (ADC) may depend on associated alterations in cerebral blood perfusion (CBP). This study proposes a non-biased method to quantify associations between ADC and CBP in newborns with global or focal cerebral ischemia. The study population consisted of nine neonates (age: 0 to 3 days) presenting with clinical and imaging evidence of ischemia (seven with global hypoxic ischemia, and two with focal arterial ischemic stroke) with decreased ADC. Six newborns without diffusion abnormalities on magnetic resonance (MR) imaging served as a comparative cohort (age: 0 days to 4 weeks). All patients underwent MR imaging including diffusion weighted imaging (DWI) to determine ADC and axial arterial spin labeling (ASL) to determine CBP. An algorithm was developed that uses the B0 volume from the DWI raw data as a reference, co-registers the ADC and ASL-CBP data to the B0, generates mask filters, and finally performs a statistical analysis to automatically select regions of interest (ROIs) with ADC or ASL-CBP values that deviate significantly from the rest of the brain. If ROIs are identified in this analysis, the algorithm then evaluates correlation based on ROI location and volume. A significant correlation was found between decreased ADC and elevated ASL-CBP with regions of elevated ASL-CBP typically larger than the corresponding ADC abnormality. The association between decreased diffusivity and increased ASL-CBP suggests that, for this cohort, cerebral ischemia is associated with hyperperfusion.

Imaging tumors of the pediatric central nervous system.

Primary tumors of the central nervous system (CNS) are the second most common neoplasms in children and the leading cause of death in this patient population. The primary objective of this article is to describe the most common pediatric brain tumors and to offer an overview of their respective imaging features, primarily on magnetic resonance imaging. Precise anatomic characterization is essential for developing an appropriate differential diagnosis. Once equipped with this critical information, physicians should be better able to make firm diagnoses, leading to improved disease management and patient outcomes in the setting of CNS tumors of childhood.