Persistent MRI Findings Unique to Blast and Repetitive Mild TBI: Analysis of the CENC/LIMBIC Cohort Injury Characteristics.

INTRODUCTION: MRI represents one of the clinical tools at the forefront of research efforts aimed at identifying diagnostic and prognostic biomarkers following traumatic brain injury (TBI). Both volumetric and diffusion MRI findings in mild TBI (mTBI) are mixed, making the findings difficult to interpret. As such, additional research is needed to continue to elucidate the relationship between the clinical features of mTBI and quantitative MRI measurements. MATERIAL AND METHODS: Volumetric and diffusion imaging data in a sample of 976 veterans and service members from the Chronic Effects of Neurotrauma Consortium and now the Long-Term Impact of Military-Relevant Brain Injury Consortium observational study of the late effects of mTBI in combat with and without a history of mTBI were examined. A series of regression models with link functions appropriate for the model outcome were used to evaluate the relationships among imaging measures and clinical features of mTBI. Each model included acquisition site, participant sex, and age as covariates. Separate regression models were fit for each region of interest where said region was a predictor. RESULTS: After controlling for multiple comparisons, no significant main effect was noted for comparisons between veterans and service members with and without a history of mTBI. However, blast-related mTBI were associated with volumetric reductions of several subregions of the corpus callosum compared to non-blast-related mTBI. Several volumetric (i.e., hippocampal subfields, etc.) and diffusion (i.e., corona radiata, superior longitudinal fasciculus, etc.) MRI findings were noted to be associated with an increased number of repetitive mTBIs versus. CONCLUSIONS: In deployment-related mTBI, significant findings in this cohort were only observed when considering mTBI sub-groups (blast mechanism and total number/dose). Simply comparing healthy controls and those with a positive mTBI history is likely an oversimplification that may lead to non-significant findings, even in consortium analyses.

Microstructural Organization of Distributed White Matter Associated With Fine Motor Control in US Service Members With Mild Traumatic Brain Injury.

Mild traumatic brain injury (mTBI) is the most common form of brain injury. While most individuals recover from mTBI, roughly 20% experience persistent symptoms, potentially including reduced fine motor control. We investigate relationships between regional white matter organization and subcortical volumes associated with performance on the Grooved Pegboard (GPB) test in a large cohort of military Service Members and Veterans (SM&Vs) with and without a history of mTBI(s). Participants were enrolled in the Long-term Impact of Military-relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium. SM&Vs with a history of mTBI(s) (n = 847) and without mTBI (n = 190) underwent magnetic resonance imaging and the GPB test. We first examined between-group differences in GPB completion time. We then investigated associations between GPB performance and regional structural imaging measures (tractwise diffusivity, subcortical volumes, and cortical thickness) in SM&Vs with a history of mTBI(s). Lastly, we explored whether mTBI history moderated associations between imaging measures and GPB performance. SM&Vs with mTBI(s) performed worse than those without mTBI(s) on the non-dominant hand GPB test at a trend level (p < 0.1). Higher fractional anisotropy (FA) of tracts including the posterior corona radiata, superior longitudinal fasciculus, and uncinate fasciculus were associated with better GPB performance in the dominant hand in SM&Vs with mTBI(s). These findings support that the organization of several white matter bundles are associated with fine motor performance in SM&Vs. We did not observe that mTBI history moderated associations between regional FA and GPB test completion time, suggesting that chronic mTBI may not significantly influence fine motor control.

Subcortical functional connectivity and its association with walking performance following deployment related mild TBI.

Introduction: The relation between traumatic brain injury (TBI), its acute and chronic symptoms, and the potential for remote neurodegenerative disease is a priority for military research. Structural and functional connectivity (FC) of the basal ganglia, involved in motor tasks such as walking, are altered in some samples of Service Members and Veterans with TBI, but any behavioral implications are unclear and could further depend on the context in which the TBI occurred. Methods: In this study, FC from caudate and pallidum seeds was measured in Service Members and Veterans with a history of mild TBI that occurred during combat deployment, Service Members and Veterans whose mild TBI occurred outside of deployment, and Service Members and Veterans who had no lifetime history of TBI. Results: FC patterns differed for the two contextual types of mild TBI. Service Members and Veterans with deployment-related mild TBI demonstrated increased FC between the right caudate and lateral occipital regions relative to both the non-deployment mild TBI and TBI-negative groups. When evaluating the association between FC from the caudate and gait, the non-deployment mild TBI group showed a significant positive relationship between walking time and FC with the frontal pole, implicated in navigational planning, whereas the deployment-related mild TBI group trended towards a greater negative association between walking time and FC within the occipital lobes, associated with visuo-spatial processing during navigation. Discussion: These findings have implications for elucidating subtle motor disruption in Service Members and Veterans with deployment-related mild TBI. Possible implications for future walking performance are discussed.

Copper-Catalyzed Racemization-Recycle of a Quaternary Center and Optimization Using a Combined Kinetics-DoE/MLR Modeling Approach.

The copper-catalyzed racemization of a complex, quaternary center of a key intermediate on route to lanabecestat has been identified. Optimization and mechanistic understanding were achieved through the use of an efficient, combined kinetic-multiple linear regression approach to experimental design and modeling. The use of a definitive screening design with mechanistically relevant factors and a mixture of fitted kinetic descriptors and empirical measurements facilitated the generation of a model that accurately predicted complex reaction time course behavior. The synergistic model was used to minimize the formation of dimer byproducts, determine optimal conditions for batch operation, and highlight superheated conditions that could be accessed in flow, leading to a further increase in yield which was predicted by the original model.

A serotonergic biobehavioral signature differentiates cocaine use disorder participants administered mirtazapine.

Cocaine use disorder (CUD) patients display heterogenous symptoms and unforeseeable responses to available treatment approaches, highlighting the need to identify objective, accessible biobehavioral signatures to predict clinical trial success in this population. In the present experiments, we employed a task-based behavioral and pharmacogenetic-fMRI approach to address this gap. Craving, an intense desire to take cocaine, can be evoked by exposure to cocaine-associated stimuli which can trigger relapse during attempted recovery. Attentional bias towards cocaine-associated words is linked to enhanced effective connectivity (EC) from the anterior cingulate cortex (ACC) to hippocampus in CUD participants, an observation which was replicated in a new cohort of participants in the present studies. Serotonin regulates attentional bias to cocaine and the serotonergic antagonist mirtazapine decreased activated EC associated with attentional bias, with greater effectiveness in those CUD participants carrying the wild-type 5-HT2CR gene relative to a 5-HT2CR single nucleotide polymorphism (rs6318). These data suggest that the wild-type 5-HT2CR is necessary for the efficacy of mirtazapine to decrease activated EC in CUD participants and that mirtazapine may serve as an abstinence enhancer to mitigate brain substrates of craving in response to cocaine-associated stimuli in participants with this pharmacogenetic descriptor. These results are distinctive in outlining a richer "fingerprint" of the complex neurocircuitry, behavior and pharmacogenetics profile of CUD participants which may provide insight into success of future medications development projects.

Advanced brain age in deployment-related traumatic brain injury: A LIMBIC-CENC neuroimaging study.

OBJECTIVE: 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. METHODS: 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. RESULT: 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. CONCLUSION: 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.

An automated computational approach to kinetic model discrimination and parameter estimation.

We herein report experimental applications of a novel, automated computational approach to chemical reaction network (CRN) identification. This report shows the first chemical applications of an autonomous tool to identify the kinetic model and parameters of a process, when considering both catalytic species and various integer and non-integer orders in the model's rate laws. This kinetic analysis methodology requires only the input of the species within the chemical system (starting materials, intermediates, products, etc.) and corresponding time-series concentration data to determine the kinetic information of the chemistry of interest. This is performed with minimal human interaction and several case studies were performed to show the wide scope and applicability of this process development tool. The approach described herein can be employed using experimental data from any source and the code for this methodology is also provided open-source.

Coordinating Global Multi-Site Studies of Military-Relevant Traumatic Brain Injury: Opportunities, Challenges, and Harmonization Guidelines.

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

Diffusion Tensor Imaging Indicators of White Matter Injury Are Correlated with a Multimodal Electroencephalography-Based Biomarker in Slow Recovering, Concussed Collegiate Athletes.

There are no validated, objective diagnostic or prognostic biomarkers for sports-related concussion (SRC), which hinders evidence-based treatment for concussed athletes. While quantitative electrophysiology (EEG) and diffusion tensor imaging (DTI) are promising technologies for providing objective biomarkers for concussion, the degree to which they are related has not been systematically investigated in concussed athletes. This study examined whether diffusion metrics differentiated concussed athletes with prolonged recovery (n = 18) from non-conccused athletes (n = 13) and whether observed diffusion alterations related to EEG. Collegiate athletes (N = 31) completed EEG, neurocognitive, and magnetic resonance imaging. White matter diffusivity differed between the groups in multiple white matter tracts, including the corpus callosum, cingulum bundle, thalamic radiations, and inferior fronto-occipital, inferior longitudinal, and uncinate fasciculi, but not after correction for multiple comparisons. The enhanced Brain Function Index (eBFI), a measure that combines EEG and neurocognitive data, significantly correlated with altered diffusion in the concussed athletes. These preliminary findings suggest that the absolute deviation of diffusion metrics in concussed versus non-concussed athletes may have clinically utility. Results also suggested that the eBFI may be sensitive to early changes from sports-related concussion.

FreeSurfer 5.3 versus 6.0: are volumes comparable? A Chronic Effects of Neurotrauma Consortium study.

Automated neuroimaging methods like FreeSurfer ( https://surfer.nmr.mgh.harvard.edu/ ) have revolutionized quantitative neuroimaging analyses. Such analyses provide a variety of metrics used for image quantification, including magnetic resonance imaging (MRI) volumetrics. With the release of FreeSurfer version 6.0, it is important to assess its comparability to the widely-used previous version 5.3. The current study used data from the initial 249 participants in the ongoing Chronic Effects of Neurotrauma Consortium (CENC) multicenter observational study to compare the volumetric output of versions 5.3 and 6.0 across various regions of interest (ROI). In the current investigation, the following ROIs were examined: total intracranial volume, total white matter volume, total ventricular volume, total gray matter volume, and right and left volumes for the thalamus, pallidum, putamen, caudate, amygdala and hippocampus. Absolute ROI volumes derived from FreeSurfer 6.0 differed significantly from those obtained using version 5.3. We also employed a clinically-based evaluation strategy to compare both versions in their prediction of age-mediated volume reductions (or ventricular increase) in the aforementioned structures. Statistical comparison involved both general linear modeling (GLM) and random forest (RF) methods, where cross-validation error was significantly higher using segmentations from FreeSurfer version 5.3 versus version 6.0 (GLM: t = 4.97, df = 99, p value = 2.706e-06; RF: t = 4.85, df = 99, p value = 4.424e-06). Additionally, the relative importance of ROIs used to predict age using RFs differed between FreeSurfer versions, indicating substantial differences in the two versions. However, from the perspective of correlational analyses, fitted regression lines and their slopes were similar between the two versions, regardless of version used. While absolute volumes are not interchangeable between version 5.3 and 6.0, ROI correlational analyses appear to yield similar results, suggesting the interchangeability of ROI volume for correlational studies.

Structural neuroimaging in mild traumatic brain injury: A chronic effects of neurotrauma consortium study.

OBJECTIVES: The chronic effects of neurotrauma consortium (CENC) observational study is a multisite investigation designed to examine the long-term longitudinal effects of mild traumatic brain injury (mTBI). All participants in this initial CENC cohort had a history of deployment in Operation Enduring Freedom (Afghanistan), Operation Iraqi Freedom (Iraq), and/or their follow-on conflicts (Operation Freedom's Sentinel). All participants undergo extensive medical, neuropsychological, and neuroimaging assessments and either meet criteria for any lifetime mTBI or not. These assessments are integrated into six CENC core studies-Biorepository, Biostatistics, Data and Study Management, Neuroimaging, and Neuropathology. METHODS: The current study outlines the quantitative neuroimaging methods managed by the Neuroimaging Core using FreeSurfer automated software for image quantification. RESULTS: At this writing, 319 participants from the CENC observational study have completed all baseline assessments including the imaging protocol and tertiary data quality assurance procedures. CONCLUSIONS/DISCUSSION: The preliminary findings of this initial cohort are reported to describe how the Neuroimaging Core manages neuroimaging quantification for CENC studies.

Cingulo-hippocampal effective connectivity positively correlates with drug-cue attentional bias in opioid use disorder.

Individuals with opioid use disorder (OUD) often relapse when exposed to opioid-related cues. Previous functional magnetic resonance imaging (fMRI) studies have identified neuronal corticolimbic changes related to drug cue reactivity in OUD. However, the corresponding manner in which brain regions interact is still unclear. Effective (directional) connectivity was analyzed using dynamic causal modeling of fMRI data acquired from 27 OUD participants (13 with OUD and 14 with OUD and cocaine use disorder [OUD+CUD]), while performing an opioid-word Stroop task. Participants were shown opioid and neutral words presented in different colors and were instructed to indicate word color but ignore word meaning. The effects of opioid words relative to neutral words on effective connectivity and on behavioral reaction time were defined as modulatory change and attentional bias, respectively. For all the 27 participants, left anterior cingulate cortex (ACC) to right hippocampus effective connectivity exhibited the largest modulatory change, which was positively correlated with attentional bias. The findings for the ACC to hippocampus EC were consistent across OUD and CUD found in a previous study.

Process Design and Optimization in the Pharmaceutical Industry: A Suzuki-Miyaura Procedure for the Synthesis of Savolitinib.

A multidisciplinary approach covering synthetic, physical, and analytical chemistry, high-throughput experimentation and experimental design, process engineering, and solid-state chemistry is used to develop a large-scale (kilomole) Suzuki-Miyaura process. Working against clear criteria and targets, a full process investigation and optimization package is described highlighting how and why key decisions are made in the development of large-scale pharmaceutical processes.

Assessment of quantitative magnetic resonance imaging metrics in the brain through the use of a novel phantom.

OBJECTIVE: Multisite and longitudinal neuroimaging studies are important in uncovering trajectories of recovery and neurodegeneration following traumatic brain injury (TBI) and concussion through the use of diffusion tensor imaging (DTI) and other imaging modalities. This study assessed differences in anisotropic diffusion measurement across four scanners using a human and a novel phantom developed in conjunction with the Chronic Effects of Neurotrauma Consortium. METHOD: Human scans provided measurement within biological tissue, and the novel physical phantom provided measures of anisotropic intra-tubular diffusion to serve as a model for intra-axonal water diffusion. Intra- and inter-scanner measurement variances were compared, and the impact on effect size was calculated. RESULTS: Intra-scanner test-retest reliability estimates for fractional anisotropy (FA) demonstrated relative stability over testing intervals. The human tissue and phantom showed similar FA ranges, high linearity and large within-device effect sizes. However, inter-scanner measures of FA indicated substantial differences, some of which exceeded typical DTI effect sizes in mild TBI. CONCLUSION: The diffusion phantom may be used to better elucidate inter-scanner variability in DTI-based measurement and provides an opportunity to better calibrate results obtained from scanners used in multisite and longitudinal studies. Novel solutions are being evaluated to understand and potentially overcome these differences.

Analysis of variability of fractional anisotropy values at 3T using a novel diffusion tensor imaging phantom.

We employed a novel diffusion tensor imaging phantom to study intra- and interscanner reproducibility on two 3T magnetic resonance (MR) scanners. Using a phantom containing thousands of hollow micron-size tubes in complex arrays, we performed two experiments using a b value of 1000 s/ms2 on two Siemens 3T Trio scanners. First, we performed 12-direction scans. Second, on one scanner, we performed two 64-direction protocols with different repetition times (TRs). We used a one-way analysis of variance to calculate differences between scanners and the Mann-Whitney U test to assess differences between 12-direction and 64-direction data. We calculated the coefficient of variation (CoV) for intrascanner and interscanner data. For 12-direction protocols, mean fractional anisotropy (FA) was 0.3003 for Scanner 1 (four scans) and 0.3094 for Scanner 2 (three scans). Lowest FA value on Scanner 1 was 2.56 standard deviations below the mean of Scanner 2. For 64-direction scans, mean FA was 0.2640 for 4000 ms TR and 0.2582 for 13,200 ms TR scans. For 12-direction scans, within-scanner CoV was 0.0326 for Scanner 1 and 0.0240 for Scanner 2; between-scanner CoV was 0.032. For 64-direction scans, CoV was 0.056 for TR 4000 ms and 0.0533 for TR 13,200 ms. The difference between median FA values of 12-direction and 64-direction scans was statistically significant ( p < 0.001). We found relatively good reproducibility on any single MR scanner. FA values from one scanner were sometimes significantly below the mean FA of another scanner, which has important implications for clinical use of DTI.

Functional brain connectivity and cortical thickness in relation to chronic pain in post-911 veterans and service members with mTBI.

OBJECTIVES: Investigate the relation of chronic pain interference to functional connectivity (FC) of brain regions and to cortical thickness in post-911 Veterans and Service Members (SMs) who sustained a mild traumatic brain injury (mTBI). METHODS: This is an observational study with cross-sectional analyses. A sample of 65 enrollees completing initial evaluation at a single site of the Chronic Effects of Neurotrauma Consortium (CENC) reported pain interference ratings on the TBI QOL. Functional connectivity and cortical thickness were measured. RESULTS: Severity of pain interference was negatively related to FC of the default mode network (DMN), i.e., participants who reported more severe pain interference had less FC between mesial prefrontal cortex and posterior regions of the DMN including posterior cingulate cortex and precuneus. Cortical thickness of specific regions was positively related to severity of pain interference. CONCLUSION: The more that pain was perceived to interfere with daily life, the less the FC between regions in a network associated with self-referential thought and mind wandering. Although cortical thickness in specific brain regions was positively related to severity of pain interference, follow-up longitudinal data, control group data, and study of individual differences in this cohort will expand this initial report and replicate these findings.

ENIGMA MILITARY BRAIN INJURY: A COORDINATED META-ANALYSIS OF DIFFUSION MRI FROM MULTIPLE COHORTS.

Traumatic brain injury (TBI) is a significant cause of morbidity in military Veterans and Service Members. While most individuals recover fully from mild injuries within weeks, some continue to experience symptoms including headaches, disrupted sleep, and other cognitive, behavioral or physical symptoms. Diffusion magnetic resonance imaging (dMRI) shows promise in identifying areas of structural disruption and predicting outcomes. Although some studies suggest widespread structural disruption after brain injury, dMRI studies of military brain injury have yielded mixed results so far, perhaps due to the subtlety of mild injury, individual differences in injury location, severity and mechanism, and comorbidity with other disorders such as post-traumatic stress disorder (PTSD), depression, and substance abuse. We present preliminary dMRI results from the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) military brain injury working group. We found higher fractional anisotropy (FA) in participants with a history of TBI. Understanding the injury and recovery process, along with factors that influence these, will lead to improved diagnosis and treatment.

Accelerated Changes in Cortical Thickness Measurements with Age in Military Service Members with Traumatic Brain Injury.

Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.

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.

Supervised learning technique for the automated identification of white matter hyperintensities in traumatic brain injury.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: Paired with correlative outcome data, supervised learning methods may allow for identification of imaging features predictive of diagnosis and prognosis in individual TBI patients.