Postnatal Brain Trajectories and Maternal Intelligence Predict Childhood Outcomes in Complex CHD.

Objective: To determine whether early structural brain trajectories predict early childhood neurodevelopmental deficits in complex CHD patients and to assess relative cumulative risk profiles of clinical, genetic, and demographic risk factors across early development. Study Design: Term neonates with complex CHDs were recruited at Texas Children's Hospital from 2005-2011. Ninety-five participants underwent three structural MRI scans and three neurodevelopmental assessments. Brain region volumes and white matter tract fractional anisotropy and radial diffusivity were used to calculate trajectories: perioperative, postsurgical, and overall. Gross cognitive, language, and visuo-motor outcomes were assessed with the Bayley Scales of Infant and Toddler Development and with the Wechsler Preschool and Primary Scale of Intelligence and Beery-Buktenica Developmental Test of Visual-Motor Integration. Multi-variable models incorporated risk factors. Results: Reduced overall period volumetric trajectories predicted poor language outcomes: brainstem ((ß, 95% CI) 0.0977, 0.0382-0.1571; p = 0.0022) and white matter (0.0023, 0.0001-0.0046; p = 0.0397) at 5 years; brainstem (0.0711, 0.0157-0.1265; p = 0.0134) and deep grey matter (0.0085, 0.0011-0.0160; p = 0.0258) at 3 years. Maternal IQ was the strongest contributor to language variance, increasing from 37% at 1 year, 62% at 3 years, and 81% at 5 years. Genetic abnormality's contribution to variance decreased from 41% at 1 year to 25% at 3 years and was insignificant at 5 years. Conclusion: Reduced postnatal subcortical-cerebral white matter trajectories predicted poor early childhood neurodevelopmental outcomes, despite high contribution of maternal IQ. Maternal IQ was cumulative over time, exceeding the influence of known cardiac and genetic factors in complex CHD, underscoring the importance of heritable and parent-based environmental factors.

Cognitive Sparing in Proton versus Photon Radiotherapy for Pediatric Brain Tumor Is Associated with White Matter Integrity: An Exploratory Study.

Radiotherapy for pediatric brain tumors is associated with reduced white matter structural integrity and neurocognitive decline. Superior cognitive outcomes have been reported following proton radiotherapy (PRT) compared to photon radiotherapy (XRT), presumably due to improved sparing of normal brain tissue. This exploratory study examined the relationship between white matter change and late cognitive effects in pediatric brain tumor survivors treated with XRT versus PRT. Pediatric brain tumor survivors treated with XRT (n = 10) or PRT (n = 12) underwent neuropsychological testing and diffusion weighted imaging >7 years post-radiotherapy. A healthy comparison group (n = 23) was also recruited. Participants completed age-appropriate measures of intellectual functioning, visual-motor integration, and motor coordination. Tractography was conducted using automated fiber quantification (AFQ). Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) were extracted from 12 tracts of interest. Overall, both white matter integrity (FA) and neuropsychological performance were lower in XRT patients while PRT patients were similar to healthy control participants with respect to both FA and cognitive functioning. These findings support improved long-term outcomes in PRT versus XRT. This exploratory study is the first to directly support for white matter integrity as a mechanism of cognitive sparing in PRT.

Superior verbal learning and memory in pediatric brain tumor survivors treated with proton versus photon radiotherapy.

OBJECTIVE: Radiotherapy for pediatric brain tumor has been associated with late cognitive effects. Compared to conventional photon radiotherapy (XRT), proton radiotherapy (PRT) delivers lower doses of radiation to healthy brain tissue. PRT has been associated with improved long-term cognitive outcomes compared to XRT. However, there is limited research comparing the effects of XRT and PRT on verbal memory. METHOD: Survivors of pediatric brain tumor treated with either XRT (n = 29) or PRT (n = 51) completed neuropsychological testing > 1 year following radiotherapy. Performance on neuropsychological measures was compared between treatment groups using analysis of covariance. Chi-squared tests of independence were used to compare the frequency of encoding, retrieval, and intact memory profiles between treatment groups. Associations between memory performance and other neurobehavioral measures were examined using Pearson correlation. RESULTS: Overall, patients receiving PRT demonstrated superior verbal learning and recall compared to those treated with XRT. Encoding and retrieval deficits were more common in the XRT group than the PRT group, with encoding problems being most prevalent. The PRT group was more likely to engage in semantic clustering strategies, which predicted better encoding and retrieval. Encoding ability was associated with higher intellectual and adaptive functioning, and fewer parent-reported concerns about day-to-day attention and cognitive regulation. CONCLUSION: Results suggest that PRT is associated with verbal memory sparing, driven by effective encoding and use of learning strategies. Future work may help to clarify underlying neural mechanisms associated with verbal memory decline, which will better inform treatment approaches. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Predicting neurocognitive function in pediatric brain tumor early survivorship: The neurological predictor scale and the incremental validity of tumor size.

BACKGROUND: The Neurological Predictor Scale (NPS) quantifies cumulative exposure to conventional treatment-related neurological risks but does not capture potential risks posed by tumors themselves. This study evaluated the predictive validity of the NPS, and the incremental value of tumor location and size, for neurocognitive outcomes in early survivorship following contemporary therapies for pediatric brain tumors. PROCEDURE: Survivors (N = 69) diagnosed from 2010 to 2016 were administered age-appropriate versions of the Wechsler Intelligence Scales. Hierarchical multiple regressions examined the predictive and incremental validity of NPS score, tumor location, and tumor size. RESULTS: Participants (51% female) aged 6-20 years (M = 13.22, SD = 4.09) completed neurocognitive evaluations 5.16 years (SD = 1.29) postdiagnosis. The NPS significantly predicted Full-Scale Intelligence Quotient (FSIQ; ΔR2  = .079), Verbal Comprehension Index (VCI; ΔR2  = 0.051), Perceptual Reasoning Index (PRI; ΔR2  = 0.065), and Processing Speed Index (PSI; ΔR2  = 0.049) performance after controlling for sex, age at diagnosis, and maternal education. Tumor size alone accounted for a significant amount of unique variance in FSIQ (ΔR2  = 0.065), PRI (ΔR2  = 0.076), and PSI (ΔR2  = 0.080), beyond that captured by the NPS and relevant covariates. Within the full model, the NPS remained a significant independent predictor of FSIQ (ß = -0.249, P = 0.016), VCI (ß = -0.223, P = 0.048), and PRI (ß = -0.229, P = 0.037). CONCLUSIONS: Tumor size emerged as an independent predictor of neurocognitive functioning and added incrementally to the predictive utility of the NPS. Pretreatment disease burden may provide one of the earliest markers of neurocognitive risk following contemporary treatments. With perpetual treatment advances, measures quantifying treatment-related risk may need to be updated and revalidated to maintain their clinical utility.

Diffusion Tensor Imaging Correlates of Resilience Following Adolescent Traumatic Brain Injury.

BACKGROUND: Traumatic brain injury (TBI) is associated with considerable mortality and morbidity in adolescents, but positive outcomes are possible. Resilience is the concept that some individuals flourish despite significant adversity. OBJECTIVE: To determine if there is a relationship between resilience-promoting factors that are known to promote resilience and white matter (WM) microstructure 1 year after complicated mild TBI or moderate or severe TBI that is sustained by adolescents. METHOD: We examined the relationship between performance on a self-report measure of resilience-promoting factors and WM integrity assessed by diffusion tensor imaging in a group of adolescents who had sustained either a TBI (n = 38) or an orthopedic injury (OI) (n = 23). RESULTS: Immediately following injury, the individuals with TBI and the OI controls had comparable levels of resilience-promoting factors; however, at 1 year post injury, the TBI group endorsed fewer resilience-promoting factors and exhibited WM disruption compared with the OI controls. The individuals with TBI who had more resilience-promoting factors at 1 year post injury exhibited increased WM integrity, but the OI controls did not. Findings were particularly strong for the following structures: anterior corona radiata, anterior limb of the internal capsule, and genu of the corpus callosum-structures that are implicated in social cognition and are frequently disrupted after TBI. Relationships were notable for caregiver and community-level resilience-promoting factors. CONCLUSION: The current findings are some of the first to indicate neurobiological evidence of previously noted buffering effects of resilience-promoting factors in individuals with TBI.

A Preliminary DTI Tractography Study of Developmental Neuroplasticity 5-15 Years After Early Childhood Traumatic Brain Injury.

Plasticity is often implicated as a reparative mechanism when addressing structural and functional brain development in young children following traumatic brain injury (TBI); however, conventional imaging methods may not capture the complexities of post-trauma development. The present study examined the cingulum bundles and perforant pathways using diffusion tensor imaging (DTI) in 21 children and adolescents (ages 10-18 years) 5-15 years after sustaining early childhood TBI in comparison with 19 demographically-matched typically-developing children. Verbal memory and executive functioning were also evaluated and analyzed in relation to DTI metrics. Beyond the expected direction of quantitative DTI metrics in the TBI group, we also found qualitative differences in the streamline density of both pathways generated from DTI tractography in over half of those with early TBI. These children exhibited hypertrophic cingulum bundles relative to the comparison group, and the number of tract streamlines negatively correlated with age at injury, particularly in the late-developing anterior regions of the cingulum; however, streamline density did not relate to executive functioning. Although streamline density of the perforant pathway was not related to age at injury, streamline density of the left perforant pathway was significantly and positively related to verbal memory scores in those with TBI, and a moderate effect size was found in the right hemisphere. DTI tractography may provide insight into developmental plasticity in children post-injury. While traditional DTI metrics demonstrate expected relations to cognitive performance in group-based analyses, altered growth is reflected in the white matter structures themselves in some children several years post-injury. Whether this plasticity is adaptive or maladaptive, and whether the alterations are structure-specific, warrants further investigation.

Developmental Alterations in Cortical Organization and Socialization in Adolescents Who Sustained a Traumatic Brain Injury in Early Childhood.

This study investigated patterns of cortical organization in adolescents who had sustained a traumatic brain injury (TBI) during early childhood to determine ways in which early head injury may alter typical brain development. Increased gyrification in other patient populations is associated with polymicrogyria and aberrant development, but this has not been investigated in TBI. Seventeen adolescents (mean age = 14.1 ± 2.4) who sustained a TBI between 1-8 years of age, and 17 demographically-matched typically developing children (TDC) underwent a high-resolution, T1-weighted 3-Tesla magnetic resonance imaging (MRI) at 6-15 years post-injury. Cortical white matter volume and organization was measured using FreeSurfer's Local Gyrification Index (LGI). Despite a lack of significant difference in white matter volume, participants with TBI demonstrated significantly increased LGI in several cortical regions that are among those latest to mature in normal development, including left parietal association areas, bilateral dorsolateral and medial frontal areas, and the right posterior temporal gyrus, relative to the TDC group. Additionally, there was no evidence of increased surface area in the regions that demonstrated increased LGI. Higher Vineland-II Socialization scores were associated with decreased LGI in right frontal and temporal regions. The present results suggest an altered pattern of expected development in cortical gyrification in the TBI group, with changes in late-developing frontal and parietal association areas. Such changes in brain structure may underlie cognitive and behavioral deficits associated with pediatric TBI. Alternatively, increased gyrification following TBI may represent a compensatory mechanism that allows for typical development of cortical surface area, despite reduced brain volume.

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.

Acute pediatric traumatic brain injury severity predicts long-term verbal memory performance through suppression by white matter integrity on diffusion tensor imaging.

Mediation analysis was used to investigate the role of white matter integrity in the relationship between injury severity and verbal memory performance in participants with chronic pediatric traumatic brain injury (TBI). DTI tractography was used to measure fractional anisotropy (FA) within the corpus callosum, fornix, cingulum bundles, perforant pathways, and uncinate fasciculi. Injury severity was indexed using Glasgow Coma Scale (GCS) scores obtained at the time of the injury. Verbal memory was measured by performance on the long-delay free recall (LDFR) trial of the California Verbal Learning Test-Children's version. Participants were between the ages of 10-18 and included 21 children with TBI (injured before age 9) and 19 typically-developing children (TDC). Children with TBI showed lower FA across all pathways and poorer LDFR performance relative to TDC. Within the TBI group, mediation analysis revealed neither a significant total effect of GCS on LDFR nor significant direct effects of GCS on LDFR across pathways; however, the indirect effects of GCS on LDFR through FA of the corpus callosum, left perforant pathway, and left uncinate fasciculus were significant and opposite in sign to their respective direct effects. These results suggests that the predictive validity of GCS for LDFR is initially suppressed by the substantial variance accounted for by FA, which is uncorrelated with GCS, and the predictive validity of GCS increases only when FA is considered, and the opposing path is controlled. These findings illustrate the complex associations between acute injury severity, white matter pathways, and verbal memory several years following pediatric TBI.

A preliminary investigation of corpus callosum subregion white matter vulnerability and relation to chronic outcome in boxers.

Microstructural neuropathology occurs in the corpus callosum (CC) after repetitive sports concussion in boxers and can be dose-dependent. However, the specificity and relation of CC changes to boxing exposure extent and post-career psychiatric and neuropsychological outcomes are largely unknown. Using deterministic diffusion tensor imaging (DTI) techniques, boxers and demographically-matched, noncontact sport athletes were compared to address literature gaps. Ten boxers and 9 comparison athletes between 26 and 59 years old (M = 44.63, SD = 9.24) completed neuropsychological testing and MRI. Quantitative DTI metrics were estimated for CC subregions. Group×Region interaction effects were observed on fractional anisotropy (FA; η2p ≥ .21). Follow-up indicated large effects of group (η2p ≥ .26) on splenium FA (boxerscomparisons), but not radial diffusivity (RD). The group of boxers had moderately elevated number of psychiatric symptoms and reduced neuropsychological scores relative to the comparison group. In boxers, years sparring, professional bouts, and knockout history correlated strongly (r > |.40|) with DTI metrics and fine motor dexterity. In the comparison group, splenium FA correlated positively with psychiatric symptoms. In the boxer group, neuropsychological scores correlated with DTI metrics in all CC subregions. Results suggested relative vulnerability of the splenium and, to a lesser extent, the genu to chronic, repetitive head injury from boxing. Dose-dependent associations of professional boxing history extent with DTI white matter structure indices as well as fine motor dexterity were supported. Results indicated that symptoms of depression and executive dysfunction may provide the strongest indicators of global CC disruption from boxing.

Persistent Disruption of Brain Connectivity after Sports-Related Concussion in a Female Athlete.

Structural and functional connectivity (FC) after sports-related concussion (SRC) may remain altered in adolescent athletes despite symptom resolution. Little is known, however, about how alterations in structural connectivity and FC co-present in female athletes whose symptom recovery tends to be prolonged. Despite resolution of symptoms, one month after her second SRC, an 18-year-old female athlete had decreased structural connectivity in the corpus callosum and cingulum, with altered FC near those regions, compared with other SRC and orthopedically injured athletes. Findings show persistent effects of SRC on advanced brain imaging and the possibility of greater vulnerability of white matter tracts in females.

Early proton magnetic resonance spectroscopy during and after therapeutic hypothermia in perinatal hypoxic-ischemic encephalopathy.

BACKGROUND: Hypoxic-ischemic encephalopathy (HIE) remains a significant cause of mortality and neurodevelopmental impairment despite treatment with therapeutic hypothermia. Magnetic resonance H1-spectroscopy measures concentrations of cerebral metabolites to detect derangements in aerobic metabolism. OBJECTIVE: We assessed MR spectroscopy in neonates with HIE within 18-24 h of initiating therapeutic hypothermia and at 5-6 days post therapeutic hypothermia. MATERIALS AND METHODS: Eleven neonates with HIE underwent MR spectroscopy of the basal ganglia and white matter. We compared metabolite concentrations during therapeutic hypothermia and post-therapeutic hypothermia and between moderate and severe HIE. RESULTS: During therapeutic hypothermia, neonates with severe HIE had decreased basal ganglia N-acetylaspartate (NAA; 0.62±0.08 vs. 0.72±0.05; P=0.02), NAA + N-acetylaspartylglutamate (NAAG; 0.66±0.11 vs. 0.77±0.06; P=0.05), glycerophosphorylcholine + phosphatidylcholine (GPC+PCh; 0.28±0.05 vs. 0.38±0.06; P=0.02) and decreased white matter GPC+PCh (0.35±0.13 vs. 0.48±0.04; P=0.02) compared to neonates with moderate HIE. For all subjects, basal ganglia NAA decreased (-0.08±0.07; P=0.01), whereas white matter GPC+PCh increased (0.03±0.04; P=0.04) from therapeutic hypothermia MRI to post-therapeutic-hypothermia MRI. All metabolite values are expressed in mmol/L. CONCLUSION: Decreased NAA and GPC+PCh were associated with greater HIE severity and could distinguish neonates who might benefit most from targeted additional neuroprotective therapies.

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.

Orthopedic Injured versus Uninjured Comparison Groups for Neuroimaging Research in Mild Traumatic Brain Injury.

To address controversy surrounding the most appropriate comparison group for mild traumatic brain injury (mTBI) research, mTBI patients 12-30 years of age were compared with an extracranial orthopedic injury (OI) patient group and an uninjured, typically developing (TD) participant group with comparable demographic backgrounds. Injured participants underwent subacute (within 96 h) and late (3 months) diffusion tensor imaging (DTI); TD controls underwent DTI once. Group differences in fractional anisotropy (FA) and mean diffusivity (MD) of commonly studied white matter tracts were assessed. For FA, subacute group differences occurred in the bilateral inferior frontal occipital fasciculus (IFOF) and right inferior longitudinal fasciculus (ILF), and for MD, differences were found in the total corpus callosum, right uncinate fasciculus, IFOF, ILF, and bilateral cingulum bundle (CB). In these analyses, differences (lower FA and higher MD) were generally observed between the mTBI and TD groups but not between the mTBI and OI groups. After a 3 month interval, groups significantly differed in left IFOF FA and in right IFOF and CB MD; the TD group had significantly higher FA and lower MD than both injury groups, which did not differ. There was one exception to this pattern, in which the OI group demonstrated significantly lower FA in the left ILF than the TD group, although neither group differed from the mTBI group. The mTBI and OI groups had generally similar longitudinal results. Findings suggest that different conclusions about group-level DTI analyses could be drawn, depending on the selected comparison group, highlighting the need for additional research in this area. Where possible, mTBI studies may benefit from the inclusion of both OI and TD controls.

Cerebral oxygen metabolism during and after therapeutic hypothermia in neonatal hypoxic-ischemic encephalopathy: a feasibility study using magnetic resonance imaging.

BACKGROUND: Therapeutic hypothermia is the standard-of-care treatment for infants diagnosed with moderate-to-severe hypoxic-ischemic encephalopathy (HIE). MRI for assessing brain injury is usually performed after hypothermia because of logistical challenges in bringing acutely sick infants receiving hypothermia from the neonatal intensive care unit (NICU) to the MRI suite. Perhaps examining and comparing early cerebral oxygen metabolism disturbances to those after rewarming will lead to a better understanding of the mechanisms of brain injury in HIE and the effects of therapeutic hypothermia. OBJECTIVE: The objectives were to assess the feasibility of performing a novel T2-relaxation under spin tagging (TRUST) MRI technique to measure venous oxygen saturation very early in the time course of treatment, 18-24 h after the initiation of therapeutic hypothermia, to provide a framework to measure neonatal cerebral oxygen metabolism noninvasively, and to compare parameters between early and post-hypothermia MRIs. MATERIALS AND METHODS: Early (18-24 h after initiating hypothermia) MRIs were performed during hypothermia treatment in nine infants with HIE (six with moderate and three with severe HIE). Six infants subsequently had an MRI after hypothermia. Mean values of cerebral blood flow, oxygen extraction fraction, and cerebral metabolic rate of oxygen from MRIs during hypothermia were compared between infants with moderate and severe HIE; and in those with moderate HIE, we compared cerebral oxygen metabolism parameters between MRIs performed during and after hypothermia. RESULTS: During the initial hypothermia MRI at 23.5±5.2 h after birth, infants with severe HIE had lower oxygen extraction fraction (P=0.04) and cerebral metabolic rate of oxygen (P=0.03) and a trend toward lower cerebral blood flow (P=0.33) compared to infants with moderate HIE. In infants with moderate HIE, cerebral blood flow decreased and oxygen extraction fraction increased between MRIs during and after hypothermia (although not significantly); cerebral metabolic rate of oxygen (P=0.93) was not different. CONCLUSION: Early MRIs were technically feasible while maintaining hypothermic goal temperatures in infants with HIE. Cerebral oxygen metabolism early during hypothermia is more disturbed in severe HIE. In infants with moderate HIE, cerebral blood flow decreased and oxygen extraction fraction increased between early and post-hypothermia scans. A comparison of cerebral oxygen metabolism parameters between early and post-hypothermia MRIs might improve our understanding of the evolution of HIE and the benefits of hypothermia. This approach could guide the use of adjunctive neuroprotective strategies in affected infants.

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.

Obesity-Related Metabolic Risk in Sedentary Hispanic Adolescent Girls with Normal BMI.

Hispanic adolescent girls with normal BMI frequently have high body fat %. Without knowledge of body fat content and distribution, their risk for metabolic complications is unknown. We measured metabolic risk indicators and abdominal fat distribution in post-pubertal Hispanic adolescent girls with Normal BMI (N-BMI: BMI < 85th percentile) and compared these indicators between girls with Normal BMI and High Fat content (N-BMI-HF: body fat ≥ 27%; n = 15) and Normal BMI and Normal Fat content (N-BMI-NF: body fat < 27%; n = 8). Plasma concentrations of glucose, insulin, adiponectin, leptin and Hs-CRP were determined. Insulin resistance was calculated using an oral glucose tolerance test. Body fat % was measured by DXA and subcutaneous, visceral and hepatic fat by MRI/MRS. The N-BMI-HF girls had increased abdominal and hepatic fat content and increased insulin resistance, plasma leptin and Hs-CRP concentrations (p < 0.05) as compared to their N-BMI-NF counterparts. In N-BMI girls, insulin resistance, plasma insulin and leptin correlated with BMI and body fat % (p < 0.05). This research confirms the necessity of the development of BMI and body fat % cut-off criteria per sex, age and racial/ethnic group based on metabolic risk factors to optimize the effectiveness of metabolic risk screening procedures.

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.

Quantitative structural neuroimaging of mild traumatic brain injury in the Chronic Effects of Neurotrauma Consortium (CENC): Comparison of volumetric data within and across scanners.

BACKGROUND: An important component of the multicentre Chronic Effects of Neurotrauma Consortium (CENC) project is the development of improved quantitative magnetic resonance imaging (MRI) methods, including volumetric analysis. Although many studies routinely employ quality assurance (QA) procedures including MR and human phantoms to promote accuracy and monitor site differences, few studies perform rigorous direct comparisons of these data nor report findings that enable inference regarding site-to-site comparability. These gaps in evaluating cross-site differences are concerning, especially given the well-established differences that can occur between data acquired on scanners with different manufacturer, hardware or software. METHODS: This study reports findings on (1) a series of studies utilizing two MR phantoms to interrogate machine-based variability using data collected on the same magnet, (2) a human phantom repeatedly imaged on the same scanner to investigate within-subject, within-site variability and (3) a human phantom imaged on three different scanners to examine within subject, between-site variability. RESULTS: Although variability is relatively minimal for the phantom scanned on the same magnet, significantly more variability is introduced in a human subject, particularly when regions are relatively small or multiple sites used. CONCLUSION: Vigilance when combining data from different sites is suggested and that future efforts address these issues.