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To determine if history of mild traumatic brain injury (mTBI) is associated with advanced or accelerated brain aging among the United States (US) military Service Members and Veterans. Eight hundred and twenty-two participants (mean age = 40.4 years, 714 male/108 female) underwent MRI sessions at eight sites across the US. Two hundred and one participants completed a follow-up scan between five months and four years later. Predicted brain ages were calculated using T1-weighted MRIs and then compared with chronological ages to generate an Age Deviation Score for cross-sectional analyses and an Interval Deviation Score for longitudinal analyses. Participants also completed a neuropsychological battery, including measures of both cognitive functioning and psychological health. In cross-sectional analyses, males with a history of deployment-related mTBI showed advanced brain age compared to those without (t(884) = 2.1, p = .038), while this association was not significant in females. In follow-up analyses of the male participants, severity of posttraumatic stress disorder (PTSD), depression symptoms, and alcohol misuse were also associated with advanced brain age. History of deployment-related mTBI, severity of PTSD and depression symptoms, and alcohol misuse are associated with advanced brain aging in male US military Service Members and Veterans.

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.

BACKGROUND The learning slope is typically represented as the raw difference between the final score and the score of the first learning trial. A new method for calculating the learning slope, the learning ratio (LR), was recently developed; it is typically represented as the number of items that are learned after the first trial divided by the number of items that are yet to be learned. OBJECTIVE To evaluate the convergent and criterion validity of the LR in order to understand its sensitivity to Alzheimer disease (AD) pathology. METHOD Fifty-six patients from a memory clinic underwent standard neuropsychological assessment and quantitative brain imaging. LR scores were calculated from the Hopkins Verbal Learning Test-Revised and the Brief Visuospatial Memory Test-Revised and were compared with both standard memory measures and total hippocampal volumes, as well as between individuals with AD and those with mild cognitive impairment. RESULTS Lower LR scores were consistently associated with poorer performances on standard memory measures and smaller total hippocampal volumes, generally more so than traditional learning slope scores. The LR scores of the AD group were smaller than those of the group with mild cognitive impairment. Furthermore, the aggregation of LR scores into a single metric was partially supported. CONCLUSION The LR is sensitive to AD pathology along the AD continuum. This result supports previous claims that the LR score can reflect learning capacity better than traditional learning calculations can by considering the amount of information that is learned at trial 1.

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.

Studies of brain morphometry may illuminate the effects of pediatric mild traumatic brain injury (TBI; e.g., concussion). However, no published studies have examined cortical thickness in the early injury phases of pediatric mild TBI using an appropriate comparison group. The current study used an automated approach (i.e., FreeSurfer) to determine whether cortical thickness differed in children following a mild TBI or a mild orthopedic injury (OI), and to examine whether post-acute cortical thickness predicted post-acute and chronic post-concussive symptoms (PCS). Children ages 8.00-16.99 years with mild TBI (n = 136) or OI (n = 70) were recruited at emergency department visits to two children's hospitals, during which parents rated children's pre-injury symptoms retrospectively. Children completed a post-acute (3–24 days post-injury) assessment, which included a 3 Tesla MRI, and 3- and 6-month post-injury assessments. Parents and children rated PCS at each assessment. Cortical thickness was estimated using FreeSurfer. Linear mixed effects and multi-variable negative binomial regression models were used to test study aims, with false discovery rate (FDR) correction for multiple comparisons. Groups differed significantly on left parietal cortical thickness (TBI > OI) after FDR correction. Cortical thickness also varied by brain subregion and age, but not sex. Groups differed significantly on PCS post-acutely (TBI > OI), but not at 3 or 6 months. Right frontal thickness was positively related to post-acute PCS in both groups. Right cingulum thickness predicted chronic PCS in the OI group only. Results highlight the complexity of predicting outcomes of pediatric mild TBI from post-acute neuroimaging biomarkers.

This investigation explored whether differences in cortical thickness could be detected in children who sustained a mild traumatic brain injury (mTBI) compared to those with orthopedic injury (OI) and whether cortical thickness related parental reporting of symptoms. To achieve this objective, FreeSurfer®-based cortical thickness measures were obtained in 330 children, 8 to 15 years of age, with either a history of mTBI or OI. Imaging was performed in all participants with the same 3 Tesla MRI scanner at six-months post-injury, where a parent-rated Post-Concussion Symptom Inventory (PCSI) was also obtained. Robust age-mediated reductions in cortical thickness were observed, but no consistent group-based differences between the mTBI and OI groups were observed. Also, the relation between mechanism of injury (i.e., sports-related, recreational, fall, motor vehicle accident or other) and cortical thickness was examined. Injuries associated with any type of abuse were excluded and children with OI could not have experienced a MVA. Mechanism of injury did not differentially relate to cortical thickness, although in the fall group, parental rating using the PCSI showed increased symptom reporting to be associated with reduced cortical thickness in the left interior frontal, temporal pole and lateral temporal lobe as well as in the right temporal pole. Results from these preliminary findings are discussed in terms of injury variables and developmental factors associated with mTBI in childhood.

NeuroQuant® (NQ) and FreeSurfer (FS) are commonly used computer-automated programs for measuring MRI brain volume. Previously they were reported to have high intermethod reliabilities but often large intermethod effect size differences. We hypothesized that linear transformations could be used to reduce the large effect sizes. This study was an extension of our previously reported study. We performed NQ and FS brain volume measurements on 60 subjects (including normal controls, patients with traumatic brain injury, and patients with Alzheimer's disease). We used two statistical approaches in parallel to develop methods for transforming FS volumes into NQ volumes: traditional linear regression, and Bayesian linear regression. For both methods, we used regression analyses to develop linear transformations of the FS volumes to make them more similar to the NQ volumes. The FS-to-NQ transformations based on traditional linear regression resulted in effect sizes which were small to moderate. The transformations based on Bayesian linear regression resulted in all effect sizes being trivially small. To our knowledge, this is the first report describing a method for transforming FS to NQ data so as to achieve high reliability and low effect size differences. Machine learning methods like Bayesian regression may be more useful than traditional methods.

Although there are several techniques to analyze diffusion-weighted imaging, any technique must be sufficiently sensitive to detect clinical abnormalities. This is especially critical in disorders like mild traumatic brain injury (mTBI), where pathology is likely to be subtle. mTBI represents a major public health concern, especially for youth under 15 years of age. However, the developmental period from birth to 18 years is also a time of tremendous brain changes. Therefore, it is important to establish the degree of age- and sex-related differences. Participants were children aged 8–15 years with mTBI or mild orthopedic injuries (OI). Imaging was obtained within 10 days of injury. We performed tract-based spatial statistics (TBSS), deterministic tractography using AFQ (Automated Fiber Quantification), and probabilistic tractography using TRACULA (TRActs Constrained by UnderLying Anatomy) to evaluate whether any method provided improved sensitivity at identifying group, developmental, and/or sex-related differences. Although, there were no group differences from any of the three analyses, many of the tracts, but not all, revealed increases of fractional anisotropy (FA) and decreases of axial, radial, and mean diffusivity (AD, RD, and MD, respectively) with age. TBSS analyses resulted in age-related changes across all white matter tracts. AFQ and TRACULA revealed age-related changes within the corpus callosum, cingulum cingulate, corticospinal tract, inferior and superior longitudinal fasciculus, and uncinate fasciculus. The results are in many ways consistent across all three methods. However, results from the tractography methods provided improved sensitivity and better tract-specific results for identifying developmental and sex-related differences within the brain.

White matter hyperintensities (WMHs) are foci of abnormal signal intensity in white matter regions seen with magnetic resonance imaging (MRI). WMHs are associated with normal ageing and have shown prognostic value in neurological conditions such as traumatic brain injury (TBI). The impracticality of manually quantifying these lesions limits their clinical utility and motivates the utilization of machine learning techniques for automated segmentation workflows.This study develops a concatenated random forest framework with image features for segmenting WMHs in a TBI cohort. The framework is built upon the Advanced Normalization Tools (ANTs) and ANTsR toolkits. MR (3D FLAIR, T2- and T1-weighted) images from 24 service members and veterans scanned in the Chronic Effects of Neurotrauma Consortium's (CENC) observational study were acquired. Manual annotations were employed for both training and evaluation using a leave-one-out strategy. Performance measures include sensitivity, positive predictive value, [Formula: see text] score and relative volume difference.Final average results were: sensitivity = 0.68 ± 0.38, positive predictive value = 0.51 ± 0.40, [Formula: see text] = 0.52 ± 0.36, relative volume difference = 43 ± 26%. In addition, three lesion size ranges are selected to illustrate the variation in performance with lesion size.Paired with correlative outcome data, supervised learning methods may allow for identification of imaging features predictive of diagnosis and prognosis in individual TBI patients.

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.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.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.Vigilance when combining data from different sites is suggested and that future efforts address these issues.

In a sample of children with traumatic brain injury, this magnetic resonance imaging (MRI)–based investigation examined whether presence of a focal lesion uniquely influenced cortical thickness in any brain region. Specifically, the study explored the relation of cortical thickness to injury severity as measured by Glasgow Coma Scale score and length of stay, along with presence of encephalomalacia, focal white matter lesions or presence of hemosiderin deposition as a marker of shear injury. For comparison, a group of children without head injury but with orthopedic injury of similar age and sex were also examined. Both traumatic brain injury and orthopedic injury children had normally reduced cortical thickness with age, assumed to reflect neuronal pruning. However, the reductions observed within the traumatic brain injury sample were similar to those in the orthopedic injury group, suggesting that in this sample traumatic brain injury, per se, did not uniquely alter cortical thickness in any brain region at the group level. Injury severity in terms of Glasgow Coma Scale or longer length of stay was associated with greater reductions in frontal and occipitoparietal cortical thickness. However, presence of focal lesions were not related to unique changes in cortical thickness despite having a prominent distribution of lesions within frontotemporal regions among children with traumatic brain injury. Because focal lesions were highly heterogeneous, their association with cortical thickness and development appeared to be idiosyncratic, and not associated with group level effects.

PURPOSE To examine intermethod reliabilities and differences between FreeSurfer and the FDA-cleared congener, NeuroQuant®, both fully automated methods for structural brain MRI measurements. MATERIALS AND METHODS MRI scans from 20 normal control subjects, 20 Alzheimer's disease patients, and 20 mild traumatically brain-injured patients were analyzed with NeuroQuant® and with FreeSurfer. Intermethod reliability was evaluated. RESULTS Pairwise correlation coefficients, intraclass correlation coefficients, and effect size differences were computed. NeuroQuant® versus FreeSurfer measures showed excellent to good intermethod reliability for the 21 regions evaluated (r: .63 to .99/ICC: .62 to .99/ES: –.33 to 2.08) except for the pallidum (r/ICC/ES = .31/.29/–2.2) and cerebellar white matter (r/ICC/ES = .31/.31/.08). Volumes reported by NeuroQuant were generally larger than those reported by FreeSurfer with the whole brain parenchyma volume reported by NeuroQuant 6.50% larger than the volume reported by FreeSurfer. There was no systematic difference in results between the 3 subgroups. CONCLUSION NeuroQuant® and FreeSurfer showed good to excellent intermethod reliability in volumetric measurements for all brain regions examined with the only exceptions being the pallidum and cerebellar white matter. This finding was robust for normal individuals, patients with Alzheimer's disease, and patients with mild traumatic brain injury.

Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly below typical developing individuals on standardized measures of memory, even when not significantly different on measures of IQ. The current study sought to examine within ASD whether anatomical correlates of memory performance differed between those with average-to-above-average IQ (AIQ group) and those with low-average to borderline ability (LIQ group) as well as in relations to typically developing comparisons (TDC). Using automated volumetric analyses, we examined regional volume of classic memory areas including the hippocampus, parahippocampal gyrus, entorhinal cortex, and amygdala in an all-male sample AIQ (n = 38) and LIQ (n = 18) individuals with ASD along with 30 typically developing comparisons (TDC). Memory performance was assessed using the Test of Memory and Learning (TOMAL) compared among the groups and then correlated with regional brain volumes. Analyses revealed group differences on almost all facets of memory and learning as assessed by the various subtests of the TOMAL. The three groups did not differ on any region of interest (ROI) memory-related brain volumes. However, significant size-memory function interactions were observed. Negative correlations were found between the volume of the amygdala and composite, verbal, and delayed memory indices for the LIQ ASD group, indicating larger volume related to poorer performance. Implications for general memory functioning and dysfunctional neural connectivity in ASD are discussed.

Heightened auditory sensitivity and atypical auditory processing are common in autism. Functional studies suggest abnormal neural response and hemispheric activation to auditory stimuli, yet the neurodevelopment underlying atypical auditory function in autism is unknown. In this study, we model longitudinal volumetric growth of Heschl's gyrus gray matter and white matter during childhood and adolescence in 40 individuals with autism and 17 typically developing participants. Up to three time points of magnetic resonance imaging data, collected on average every 2.5 years, were examined from individuals 3-12 years of age at the time of their first scan. Consistent with previous cross-sectional studies, no group differences were found in Heschl's gyrus gray matter volume or asymmetry. However, reduced longitudinal gray matter volumetric growth was found in the right Heschl's gyrus in autism. Reduced longitudinal white matter growth in the left hemisphere was found in the right-handed autism participants. Atypical Heschl's gyrus white matter volumetric growth was found bilaterally in the autism individuals with a history of delayed onset of spoken language. Heightened auditory sensitivity, obtained from the Sensory Profile, was associated with reduced volumetric gray matter growth in the right hemisphere. Our longitudinal analyses revealed dynamic gray and white matter changes in Heschl's gyrus throughout childhood and adolescence in both typical development and autism.

Despite repeated findings of abnormal corpus callosum structure in autism, the developmental trajectories of corpus callosum growth in the disorder have not yet been reported. In this study, we examined corpus callosum size from a developmental perspective across a 30-year age range in a large cross-sectional sample of individuals with autism compared to a typically developing sample. Midsagittal corpus callosum area and the 7 Witelson subregions were examined in 68 males with autism (mean age 14.1 years; range 3–36 years) and 47 males with typical development (mean age 15.3 years; range 4–29 years). Controlling for total brain volume, increased variability in total corpus callosum area was found in autism. In autism, increased midsagittal areas were associated with reduced severity of autism behaviors, higher intelligence, and faster speed of processing (p=0.003, p=0.011, p=0.013, respectively). A trend toward group differences in isthmus development was found (p=0.029, uncorrected). These results suggest that individuals with autism benefit functionally from increased corpus callosum area. Our cross-sectional examination also shows potential maturational abnormalities in autism, a finding that should be examined further with longitudinal datasets.

This study examined peer relationships in children with traumatic brain injury (TBI) relative to children with orthopedic injuries (OI), and explored whether differences in peer relationships correlated with white matter volumes. Classroom procedures were used to elicit peer perceptions of social behavior, acceptance, and friendships for eighty-seven 8- to 13-year-old children, 15 with severe TBI, 40 with complicated mild/moderate TBI, and 32 with OI. Magnetic resonance imaging (MRI) and voxel-based morphometry (VBM) were used to investigate volumetric correlates of peer relationship measures. Children with severe TBI were rated higher in rejection-victimization than children with OI, and were less likely than children with OI to have a mutual friendship in their classroom (47% vs. 88%). Children with TBI without a mutual friend were rated lower than those with a mutual friend on sociability-popularity and prosocial behavior and higher on rejection-victimization, and had lower peer acceptance ratings. Mutual friendship ratings were related to white matter volumes in several posterior brain regions, but not to overall brain atrophy. Severe TBI in children is associated with detrimental peer relationships that are related to focal volumetric reductions in white matter within regions of the brain involved in social information-processing. (JINS, 2013, 19, 1–10)

Post-traumatic seizures affect 12-35% of children after traumatic brain injury (TBI) and are associated with worse cognitive and functional outcome, even after adjustment for severity of injury. Unfortunately, experimental models of pediatric post-traumatic epilepsy are lacking, and pathogenesis remains poorly understood. We have applied a standard model of TBI in immature rats to determine the effect of TBI on electroconvulsive seizure thresholds later in life. Male rats underwent controlled cortical impact to left parietal cortex on post-natal day (PND) 16-18. Hindbrain, forebrain, and limbic seizure thresholds were assessed, respectively, by tonic hindlimb extension (THE), minimal clonic, and partial psychomotor seizure responses during adolescence (PND 34-40) and at maturity (PND 60-63). Post-traumatic seizure thresholds were compared to those obtained in age- and litter-matched sham craniotomy and naive controls. TBI during immaturity had no clear effect on THE seizure thresholds. In contrast, TBI lowered minimal clonic seizure thresholds at maturity (p

Magnetic Resonance (MR) imaging allows volumetric quantification of a variety of neuroanatomical structures using two dimensional (2D) images as well as three-dimensional (3D) reconstruction of the brain and any of its constituent parts. Three-dimensional analysis permits integration of the neuroanatomical changes which occur in pathologic states, with the cognitive and behavioral changes elucidated through neuropsychological assessment. This paper describes uniform methods for 3D neuroanatomical isolation of the neocortex, ventricular system, and hippocampus in both normal and pathologic states. The 3D methods are described in detail using two different software programs, ANALYZE and IMAGE. Three-dimensional neuroanatomical reconstructions were carried out on a patient who sustained a very severe traumatic brain injury. The 3D image analysis in the patient with traumatic brain injury, revealed structural changes in frontal and temporal cortex, ventricular dilation, and hippocampal atropy. The neuropsychological impairments in this patient, were consistent with the observed neuroanatomical changes revealed on 3D image reconstruction. This technology permits precise determinations of the extent and severity of the neuroanatomical changes which follow neurological injury disease.