Increased gray matter diffusion anisotropy in patients with persistent post-concussive symptoms following mild traumatic brain injury

Subclinical brain manifestations of repeated mild traumatic brain injury are changed by chronic exposure to sleep loss, caffeine, and sleep aids

INTRODUCTION

After mild traumatic brain injury (mTBI), the brain is labile for weeks and months and vulnerable to repeated concussions. During this time, patients are exposed to everyday circumstances that, in themselves, affect brain metabolism and blood flow and neural processing. How commonplace activities interact with the injured brain is unknown. The present study in an animal model investigated the extent to which three commonly experienced exposures-daily caffeine usage, chronic sleep loss, and chronic sleep aid medication-affect the injured brain in the chronic phase.

METHODS

Subclinical trauma by repeated mTBIs was produced by our head rotational acceleration injury model, which causes brain injury consistent with the mechanism of concussion in humans. Forty-eight hours after a third mTBI, chronic administrations of caffeine, sleep restriction, or zolpidem (sedative hypnotic) began and were continued for 70 days. On Days 30 and 60 post injury, resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were performed.

RESULTS

Chronic caffeine, sleep restriction, and zolpidem each changed the subclinical brain characteristics of mTBI at both 30 and 60 days post injury, detected by different MRI modalities. Each treatment caused microstructural alterations in DTI metrics in the insular cortex and retrosplenial cortex compared with mTBI, but also uniquely affected other gray and white matter regions. Zolpidem administration affected the largest number of individual structures in mTBI at both 30 and 60 days, and not necessarily toward normalization (sham treatment). Chronic sleep restriction changed local functional connectivity at 30 days in diametrical opposition to chronic caffeine ingestion, and both treatment outcomes were different from sham, mTBI-only and zolpidem comparisons. The results indicate that commonly encountered exposures modify subclinical brain activity and structure long after healing is expected to be complete.

CONCLUSIONS

Changes in activity and structure detected by fMRI are widely understood to reflect changes in the functions of the affected region which conceivably underlie mTBI neuropathology and symptomatology in the chronic phase after injury.

Dose-dependent cranial irradiation associations with brain structures and neuropsychological outcomes in children with posterior fossa brain tumors

BACKGROUND

Posterior fossa irradiation with or without whole brain irradiation results in high doses of radiation to the thalamus, hippocampus, and putamen, structures critical to cognitive functioning. As a result, children with brain tumors treated with cranial irradiation (CRT) may experience significant cognitive late effects. We sought to determine the effect of radiation to those structures on neuropsychological outcome.

METHODS

Forty-seven children with a history of posterior fossa tumor (17 treated with surgery; 11 with surgery and chemotherapy; and 19 with surgery, chemotherapy, and CRT) underwent neuroimaging and neuropsychological assessment at a mean of 4.8 years after treatment, along with 17 healthy sibling controls. The putamen, thalamus, and hippocampus were segmented on each participant's magnetic resonance imaging for diffusion indices and volumes, and in the radiation treatment group, radiation dose to each structure was calculated.

RESULTS

Performance on visuoconstruction and spatial learning and memory was lower in patient groups than controls. Volume of the thalamus, when controlling for age, was smaller in the patient group treated with CRT than other groups. Higher radiation doses to the putamen correlated with higher fractional anisotropy in that structure. Higher radiation dose to the hippocampus correlated with lower spatial learning, and higher dose to thalami and putamina to lower verbal and nonverbal reasoning.

CONCLUSIONS

All children with posterior fossa tumors, regardless of treatment modality, had cognitive deficits compared to their sibling controls. Posterior fossa irradiation may affect thalamic volume and aspects of verbal and nonverbal cognitive functioning.

Hypothalamic MRI-derived microstructure is associated with neurocognitive aging in humans

The hypothalamus regulates homeostasis across the lifespan and is emerging as a regulator of aging. In murine models, aging-related changes in the hypothalamus, including microinflammation and gliosis, promote accelerated neurocognitive decline. We investigated relationships between hypothalamic microstructure and features of neurocognitive aging, including cortical thickness and cognition, in a cohort of community-dwelling older adults (age range 65-97 years, n=124). Hypothalamic microstructure was evaluated with two magnetic resonance imaging diffusion metrics: mean diffusivity (MD) and fractional anisotropy (FA), using a novel image processing pipeline. Hypothalamic MD was cross-sectionally positively associated with age and it was negatively associated with cortical thickness. Hypothalamic FA, independent of cortical thickness, was cross-sectionally positively associated with neurocognitive scores. An exploratory analysis of longitudinal neurocognitive performance suggested that lower hypothalamic FA may predict cognitive decline. No associations between hypothalamic MD, age, and cortical thickness were identified in a younger control cohort (age range 18-63 years, n=99). To our knowledge, this is the first study to demonstrate that hypothalamic microstructure is associated with features of neurocognitive aging in humans.

Executive functioning, behavior, and white matter microstructure in the chronic phase after pediatric mild traumatic brain injury: results from the adolescent brain cognitive development study

BACKGROUND

Mild traumatic brain injury (mTBI) is common in children. Long-term cognitive and behavioral outcomes as well as underlying structural brain alterations following pediatric mTBI have yet to be determined. In addition, the effect of age-at-injury on long-term outcomes is largely unknown.

METHODS

Children with a history of mTBI (n = 406; Mage = 10 years, SDage = 0.63 years) who participated in the Adolescent Brain Cognitive Development (ABCD) study were matched (1:2 ratio) with typically developing children (TDC; n = 812) and orthopedic injury (OI) controls (n = 812). Task-based executive functioning, parent-rated executive functioning and emotion-regulation, and self-reported impulsivity were assessed cross-sectionally. Regression models were used to examine the effect of mTBI on these domains. The effect of age-at-injury was assessed by comparing children with their first mTBI at either 0-3, 4-7, or 8-10 years to the respective matched TDC controls. Fractional anisotropy (FA) and mean diffusivity (MD), both MRI-based measures of white matter microstructure, were compared between children with mTBI and controls.

RESULTS

Children with a history of mTBI displayed higher parent-rated executive dysfunction, higher impulsivity, and poorer self-regulation compared to both control groups. At closer investigation, these differences to TDC were only present in one respective age-at-injury group. No alterations were found in task-based executive functioning or white matter microstructure.

CONCLUSIONS

Findings suggest that everyday executive function, impulsivity, and emotion-regulation are affected years after pediatric mTBI. Outcomes were specific to the age at which the injury occurred, suggesting that functioning is differently affected by pediatric mTBI during vulnerable periods. Groups did not differ in white matter microstructure.

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes

BACKGROUND AND OBJECTIVES

Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties.

METHODS

We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time.

RESULTS

Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes.

DISCUSSION

Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

Intimate partner violence perpetration among veterans: associations with neuropsychiatric symptoms and limbic microstructure

Background

Intimate partner violence (IPV) perpetration is highly prevalent among veterans. Suggested risk factors of IPV perpetration include combat exposure, post-traumatic stress disorder (PTSD), depression, alcohol use, and mild traumatic brain injury (mTBI). While the underlying brain pathophysiological characteristics associated with IPV perpetration remain largely unknown, previous studies have linked aggression and violence to alterations of the limbic system. Here, we investigate whether IPV perpetration is associated with limbic microstructural abnormalities in military veterans. Further, we test the effect of potential risk factors (i.e., PTSD, depression, substance use disorder, mTBI, and war zone-related stress) on the prevalence of IPV perpetration.

Methods

Structural and diffusion-weighted magnetic resonance imaging (dMRI) data were acquired from 49 male veterans of the Iraq and Afghanistan wars (Operation Enduring Freedom/Operation Iraqi Freedom; OEF/OIF) of the Translational Research Center for TBI and Stress Disorders (TRACTS) study. IPV perpetration was assessed using the psychological aggression and physical assault sub-scales of the Revised Conflict Tactics Scales (CTS2). Odds ratios were calculated to assess the likelihood of IPV perpetration in veterans with either of the following diagnoses: PTSD, depression, substance use disorder, or mTBI. Fractional anisotropy tissue (FA) measures were calculated for limbic gray matter structures (amygdala-hippocampus complex, cingulate, parahippocampal gyrus, entorhinal cortex). Partial correlations were calculated between IPV perpetration, neuropsychiatric symptoms, and FA.

Results

Veterans with a diagnosis of PTSD, depression, substance use disorder, or mTBI had higher odds of perpetrating IPV. Greater war zone-related stress, and symptom severity of PTSD, depression, and mTBI were significantly associated with IPV perpetration. CTS2 (psychological aggression), a measure of IPV perpetration, was associated with higher FA in the right amygdala-hippocampus complex (r = 0.400, p = 0.005).

Conclusion

Veterans with psychiatric disorders and/or mTBI exhibit higher odds of engaging in IPV perpetration. Further, the more severe the symptoms of PTSD, depression, or TBI, and the greater the war zone-related stress, the greater the frequency of IPV perpetration. Moreover, we report a significant association between psychological aggression against an intimate partner and microstructural alterations in the right amygdala-hippocampus complex. These findings suggest the possibility of a structural brain correlate underlying IPV perpetration that requires further research.

Spatial lipidomics maps brain alterations associated with mild traumatic brain injury

Traumatic brain injury (TBI) is a global public health problem with 50-60 million incidents per year, most of which are considered mild (mTBI) and many of these repetitive (rmTBI). Despite their massive implications, the pathologies of mTBI and rmTBI are not fully understood, with a paucity of information on brain lipid dysregulation following mild injury event(s). To gain more insight on mTBI and rmTBI pathology, a non-targeted spatial lipidomics workflow utilizing high resolution mass spectrometry imaging was developed to map brain region-specific lipid alterations in rats following injury. Discriminant multivariate models were created for regions of interest including the hippocampus, cortex, and corpus callosum to pinpoint lipid species that differentiated between injured and sham animals. A multivariate model focused on the hippocampus region differentiated injured brain tissues with an area under the curve of 0.99 using only four lipid species. Lipid classes that were consistently discriminant included polyunsaturated fatty acid-containing phosphatidylcholines (PC), lysophosphatidylcholines (LPC), LPC-plasmalogens (LPC-P) and PC potassium adducts. Many of the polyunsaturated fatty acid-containing PC and LPC-P selected have never been previously reported as altered in mTBI. The observed lipid alterations indicate that neuroinflammation and oxidative stress are important pathologies that could serve to explain cognitive deficits associated with rmTBI. Therapeutics which target or attenuate these pathologies may be beneficial to limit persistent damage following a mild brain injury event.

Spatial Lipidomics Maps Brain Alterations Associated with Mild Traumatic Brain Injury

Traumatic brain injury (TBI) is a global public health problem with 50-60 million incidents per year, most of which are considered mild (mTBI) and many of these repetitive (rmTBI). Despite their massive implications, the pathologies of mTBI and rmTBI are not fully understood, with a paucity of information on brain lipid dysregulation following mild injury event(s). To gain more insight on mTBI and rmTBI pathology, a non-targeted spatial lipidomics workflow utilizing ultrahigh resolution mass spectrometry imaging was developed to map brain region-specific lipid alterations in rats following injury. Discriminant multivariate models were created for regions of interest including the hippocampus, cortex, and corpus callosum to pinpoint lipid species that differentiated between injured and sham animals. A multivariate model focused on the hippocampus region differentiated injured brain tissues with an area under the curve of 0.994 using only four lipid species. Lipid classes that were consistently discriminant included polyunsaturated fatty acid-containing phosphatidylcholines (PC), lysophosphatidylcholines (LPC), LPC-plasmalogens (LPC-P) and PC potassium adducts. Many of the polyunsaturated fatty acid-containing PC and LPC-P selected have never been previously reported as altered in mTBI. The observed lipid alterations indicate that neuroinflammation, oxidative stress and disrupted sodium-potassium pumps are important pathologies that could serve to explain cognitive deficits associated with rmTBI. Therapeutics which target or attenuate these pathologies may be beneficial to limit persistent damage following a mild brain injury event.

A cross-comparative analysis of in vivo versus ex vivo MRI indices in a mouse model of concussion

BACKGROUND

We present a cross-sectional, case-matched, and pair-wise comparison of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) measures in vivo and ex vivo in a mouse model of concussion, thus aiming to establish the concordance of structural and diffusion imaging findings in living brain and after fixation.

METHODS

We allocated 28 male mice aged 3-4 months to sham injury and concussion (CON) groups. CON mice had received a single concussive impact on day 0 and underwent MRI at day 2 (n = 9) or 7 (n = 10) post-impact, and sham control mice likewise underwent imaging at day 2 (n = 5) or 7 (n = 4). Immediately after the final scanning, we collected the perfusion-fixed brains, which were stored for imaging ex vivo 6-12 months later. We then compared the structural imaging, DTI, and NODDI results between different methods.

RESULTS

In vivo to ex vivo structural and DTI/NODDI findings were in notably poor agreement regarding the effects of concussion on structural integrity of the brain.

COMPARISON WITH EXISTING METHODS

ex vivo imaging was frequently done to study the effects of diseases and treatments, but our results showed that ex vivo and in vivo imaging can detect completely opposite and contradictory results. This is also the first study that compares in vivo and ex vivo NODDI.

CONCLUSION

Our findings call for caution in extrapolating translational capabilities obtained ex vivo to physiological measurements in vivo. The divergent findings may reflect fixation artefacts and the contribution of the glymphatic system changes.

Sleep deprivation aggravated amyloid β oligomers-induced damage to the cerebellum of rats: Evidence from magnetic resonance imaging

For quite a long time, researches on Alzheimer's disease (AD) primarily focused on the cortex and hippocampus, while the cerebellum has been ignored because of its abnormalities considered to appear in the late stage of AD. In recent years, increasing evidence suggest that the cerebellar pathological changes possibly occur in the preclinical phase of AD, which is also associated with sleep disorder. Sleep disturbance is a high risk factor of AD. However, the changes and roles of cerebellum has rarely been reported under conditions of AD accompanied with sleep disorders. In this study, using an amyloid-β oligomers (AβO)-induced rat model of AD subjected to sleep deprivation, combining with a 7.0 T animals structural magnetic resonance imaging (MRI), we assessed structural changes of cerebellum in MRI. Our results showed that sleep deprivation combined with AβO led to an increased FA value in the anterior lobe of cerebellum, decreased ADC value in the cerebellar lobes and cerebellar nuclei, and increased cerebellum volume. Besides that, sleep deprivation exacerbated the damage of AβO to the cerebellar structural network. This study demonstrated that sleep deprivation could aggravate the damage to cerebellum induced by AβO. The present findings provide supporting evidence for the involvement of cerebellum in the early pathology of AD and sleep loss. Our data would contribute to advancing the understanding of the mysterious role of cerebellum in AD and sleep disorders, as well as would be helpful for developing non-invasive MRI biomarkers for screening early AD patients with self-reported sleep disturbances.

Current and Emerging Techniques in Neuroimaging of Sport-Related Concussion

SUMMARY

Sport-related concussion (SRC) affects an estimated 1.6 to 3.8 million Americans each year. Sport-related concussion results from biomechanical forces to the head or neck that lead to a broad range of neurologic symptoms and impaired cognitive function. Although most individuals recover within weeks, some develop chronic symptoms. The heterogeneity of both the clinical presentation and the underlying brain injury profile make SRC a challenging condition. Adding to this challenge, there is also a lack of objective and reliable biomarkers to support diagnosis, to inform clinical decision making, and to monitor recovery after SRC. In this review, the authors provide an overview of advanced neuroimaging techniques that provide the sensitivity needed to capture subtle changes in brain structure, metabolism, function, and perfusion after SRC. This is followed by a discussion of emerging neuroimaging techniques, as well as current efforts of international research consortia committed to the study of SRC. Finally, the authors emphasize the need for advanced multimodal neuroimaging to develop objective biomarkers that will inform targeted treatment strategies after SRC.

White Matter Microstructure Is Associated with Serum Neuroactive Steroids and Psychological Functioning

Military service members are at increased risk for mental health issues, and comorbidity with mild traumatic brain injury (mTBI) is common. Largely overlapping symptoms between conditions suggest a shared pathophysiology. The present work investigates the associations among white matter microstructure, psychological functioning, and serum neuroactive steroids that are part of the stress-response system. Diffusion-weighted brain imaging was acquired from 163 participants (with and without military affiliation) and free-water-corrected fractional anisotropy (FAT) was extracted. Associations between serum neurosteroid levels of allopregnanolone (ALLO) and pregnenolone (PREGNE), psychological functioning, and whole-brain white matter microstructure were assessed using regression models. Moderation models tested the effect of mTBI and comorbid post-traumatic stress disorder (PTSD) and mTBI on these associations. ALLO is associated with whole-brain white matter FAT (β = 0.24, t = 3.05, p = 0.006). This association is significantly modulated by PTSD+mTBI comorbidity (β = 0.00, t = 2.50, p = 0.027), although an mTBI diagnosis alone did not significantly impact this association (p = 0.088). There was no significant association between PREGNE and FAT (p = 0.380). Importantly, lower FAT is associated with poor psychological functioning (β = -0.19, t = -2.35, p = 0.020). This study provides novel insight into a potential common pathophysiological mechanism of neurosteroid dysregulation underlying the high risk for mental health issues in military service members. Further, comorbidity of PTSD and mTBI may bring the compensatory effects of the brain's stress response to their limit. Future research is needed to investigate whether neurosteroid regulation may be a promising tool for restoring brain health and improving psychological functioning.

Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature

There is evidence that diffusion-weighted imaging (DWI) is able to detect tissue alterations following mild traumatic brain injury (mTBI) that may not be observed on conventional neuroimaging; however, findings are often inconsistent between studies. This systematic review assesses patterns of differences in DWI metrics between those with and without a history of mTBI. A PubMed literature search was performed using relevant indexing terms for articles published prior to May 14, 2020. Findings were limited to human studies using DWI in mTBI. Articles were excluded if they were not full-length, did not contain original data, if they were case studies, pertained to military populations, had inadequate injury severity classification, or did not report post-injury interval. Findings were reported independently for four subgroups: acute/subacute pediatric mTBI, acute/subacute adult mTBI, chronic adult mTBI, and sport-related concussion, and all DWI acquisition and analysis methods used were included. Patterns of findings between studies were reported, along with strengths and weaknesses of the current state of the literature. Although heterogeneity of sample characteristics and study methods limited the consistency of findings, alterations in DWI metrics were most commonly reported in the corpus callosum, corona radiata, internal capsule, and long association pathways. Many acute/subacute pediatric studies reported higher FA and lower ADC or MD in various regions. In contrast, acute/subacute adult studies most commonly indicate lower FA within the context of higher MD and RD. In the chronic phase of recovery, FA may remain low, possibly indicating overall demyelination or Wallerian degeneration over time. Longitudinal studies, though limited, generally indicate at least a partial normalization of DWI metrics over time, which is often associated with functional improvement. We conclude that DWI is able to detect structural mTBI-related abnormalities that may persist over time, although future DWI research will benefit from larger samples, improved data analysis methods, standardized reporting, and increasing transparency.

Chronic traumatic encephalopathy: Diagnostic updates and advances

Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease that occurs secondary to repetitive mild traumatic brain injury. Current clinical diagnosis relies on symptomatology and structural imaging findings which often vary widely among those with the disease. The gold standard of diagnosis is post-mortem pathological examination. In this review article, we provide a brief introduction to CTE, current diagnostic workup and the promising research on imaging and fluid biomarker diagnostic techniques. For imaging, we discuss quantitative structural analyses, DTI, fMRI, MRS, SWI and PET CT. For fluid biomarkers, we discuss p-tau, TREM2, CCL11, NfL and GFAP.

Longitudinal changes of white matter microstructure following traumatic brain injury in U.S. military service members

The purpose of this study was to analyze quantitative diffusion tensor imaging measures across the spectrum of traumatic brain injury severity and evaluate their trajectories in military service members. Participants were 96 U.S. military service members and veterans who had sustained a mild traumatic brain injury [including complicated mild traumatic brain injury (n = 16) and uncomplicated mild traumatic brain injury (n = 68)], moderate-severe traumatic brain injury (n = 12), and controls (with or without orthopaedic injury, n = 39). All participants had been scanned at least twice, with some receiving up to five scans. Both whole brain voxel-wise analysis and tract-of-interest analysis were applied to assess the group differences of diffusion tensor imaging metrics, and their trajectories between time points of scans and days since injury. Linear mixed modelling was applied to evaluate cross-sectional and longitudinal diffusion tensor imaging metrics changes within and between groups using both tract-of-interest and voxel-wise analyses. Participants with moderate to severe traumatic brain injury had larger white matter disruption both in superficial subcortical and deep white matter, mainly over the anterior part of cerebrum, than those with mild traumatic brain injury, both complicated and uncomplicated, and there was no evidence of recovery over the period of follow-ups in moderate-severe traumatic brain injury, but deterioration was possible. Participants with mild traumatic brain injury had white matter microstructural changes, mainly in deep central white matter over the posterior part of cerebrum, with more spatial involvement in complicated mild traumatic brain injury than in uncomplicated mild traumatic brain injury and possible brain repair through neuroplasticity, e.g. astrocytosis with glial processes and glial scaring. Our results did not replicate 'V-shaped' trajectories in diffusion tensor imaging metrics, which were revealed in a previous study assessing the sub-acute stage of brain injury in service members and veterans following military combat concussion. In addition, non-traumatic brain injury controls, though not demonstrating any evidence of sustaining a traumatic brain injury, might have transient white matter changes with recovery afterward. Our results suggest that white matter integrity following a remote traumatic brain injury may change as a result of different underlying mechanisms at the microstructural level, which can have a significant consequence on the long-term well beings of service members and veterans. In conclusion, longitudinal diffusion tensor imaging improves our understanding of the mechanisms of white matter microstructural changes across the spectrum of traumatic brain injury severity. The quantitative metrics can be useful as guidelines in monitoring the long-term recovery.

Diffusion and functional MRI findings and their relationship to behaviour in postconcussion syndrome: a scoping review

Postconcussion syndrome (PCS) is a term attributed to the constellation of symptoms that fail to recover after a concussion. PCS is associated with a variety of symptoms such as headaches, concentration deficits, fatigue, depression and anxiety that have an enormous impact on patients' lives. There is currently no diagnostic biomarker for PCS. There have been attempts at identifying structural and functional brain changes in patients with PCS, using diffusion tensor imaging (DTI) and functional MRI (fMRI), respectively, and relate them to specific PCS symptoms. In this scoping review, we appraised, synthesised and summarised all empirical studies that (1) investigated structural or functional brain changes in PCS using DTI or fMRI, respectively, and (2) assessed behavioural alterations in patients with PCS. We performed a literature search in MEDLINE (Ovid), Embase (Ovid) and PsycINFO (Ovid) for primary research articles published up to February 2020. We identified 8306 articles and included 45 articles that investigated the relationship between DTI and fMRI parameters and behavioural changes in patients with PCS: 20 diffusion, 20 fMRI studies and 5 papers with both modalities. Most frequently studied structures were the corpus callosum, superior longitudinal fasciculus in diffusion and the dorsolateral prefrontal cortex and default mode network in the fMRI literature. Although some white matter and fMRI changes were correlated with cognitive or neuropsychiatric symptoms, there were no consistent, converging findings on the relationship between neuroimaging abnormalities and behavioural changes which could be largely due to the complex and heterogeneous presentation of PCS. Furthermore, the heterogeneity of symptoms in PCS may preclude discovery of one biomarker for all patients. Further research should take advantage of multimodal neuroimaging to better understand the brain-behaviour relationship, with a focus on individual differences rather than on group comparisons.

Structural and functional connectivity of the ascending arousal network for prediction of outcome in patients with acute disorders of consciousness

To determine the role of early acquisition of blood oxygen level-dependent (BOLD) signals and diffusion tensor imaging (DTI) for analysis of the connectivity of the ascending arousal network (AAN) in predicting neurological outcomes after acute traumatic brain injury (TBI), cardiopulmonary arrest (CPA), or stroke. A prospective analysis of 50 comatose patients was performed during their ICU stay. Image processing was conducted to assess structural and functional connectivity of the AAN. Outcomes were evaluated after 3 and 6 months. Nineteen patients (38%) had stroke, 18 (36%) CPA, and 13 (26%) TBI. Twenty-three patients were comatose (44%), 11 were in a minimally conscious state (20%), and 16 had unresponsive wakefulness syndrome (32%). Univariate analysis demonstrated that measurements of diffusivity, functional connectivity, and numbers of fibers in the gray matter, white matter, whole brain, midbrain reticular formation, and pontis oralis nucleus may serve as predictive biomarkers of outcome depending on the diagnosis. Multivariate analysis demonstrated a correlation of the predicted value and the real outcome for each separate diagnosis and for all the etiologies together. Findings suggest that the above imaging biomarkers may have a predictive role for the outcome of comatose patients after acute TBI, CPA, or stroke.

Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification

Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level. Among the different approaches aiming to study white matter abnormalities at the subject level, normative modeling analysis takes a step towards subject-level predictions by identifying affected brain locations in individual subjects based on extreme deviations from a normative range. Here, we leveraged a large harmonized diffusion MRI dataset from 512 healthy controls and 601 individuals diagnosed with schizophrenia, to study whether normative modeling can improve subject-level predictions from a binary classifier. To this aim, individual deviations from a normative model of standard (fractional anisotropy) and advanced (free-water) dMRI measures, were calculated by means of age and sex-adjusted z-scores relative to control data, in 18 white matter regions. Even though larger effect sizes are found when testing for group differences in z-scores than are found with raw values (p < .001), predictions based on summary z-score measures achieved low predictive power (AUC < 0.63). Instead, we find that combining information from the different white matter tracts, while using multiple imaging measures simultaneously, improves prediction performance (the best predictor achieved AUC = 0.726). Our findings suggest that extreme deviations from a normative model are not optimal features for prediction. However, including the complete distribution of deviations across multiple imaging measures improves prediction, and could aid in subject-level classification.

Diffusion Tensor Imaging Correlates of Concussion Related Cognitive Impairment

Introduction: Cognitive impairment after concussion has been widely reported, but there is no reliable imaging biomarker that predicts the severity of cognitive decline post-concussion. This study tests the hypothesis that patients with a history of concussion and persistent cognitive impairment have fractional anisotropy (FA) and mean diffusivity (MD) values from diffusion tensor imaging (DTI) that are specifically associated with poor performance on the Montreal Cognitive Assessment (MoCA). Methods: Fifty-three subjects (19 females) with concussions and persistent cognitive symptoms had MR imaging and the MoCA. Imaging was analyzed by atlas-based, whole-brain DTI segmentation and FLAIR lesion segmentation. Then, we conducted a random forest-based recursive feature elimination (RFE) with 10-fold cross-validation on the entire dataset, and with partial correlation adjustment for age and lesion load. Results: RFE showed that 11 DTI variables were found to be important predictors of MoCA scores. Partial correlation analyses, corrected for age and lesion load, showed significant correlations between MoCA scores and right fronto-temporal regions: inferior temporal gyrus MD (r = -0.62, p = 0.00001), middle temporal gyrus MD (r = -0.54, p = 0.0001), angular gyrus MD (r = -0.48, p = 0.0008), and inferior frontal gyrus FA (r = 0.44, p = 0.002). Discussion: This is the first study to demonstrate a correlation between MoCA scores and DTI variables in patients with a history of concussion and persistent cognitive impairment. This kind of research will significantly increase our understanding of why certain persons have persistent cognitive changes after concussion which, in turn, may allow us to predict persistent impairment after concussion and suggest new interventions.

Repetitive mTBI is associated with age-related reductions in cerebral blood flow but not cortical thickness

Mild traumatic brain injury (mTBI) is a risk factor for Alzheimer's disease (AD), and evidence suggests cerebrovascular dysregulation initiates deleterious neurodegenerative cascades. We examined whether mTBI history alters cerebral blood flow (CBF) and cortical thickness in regions vulnerable to early AD-related changes. Seventy-four young to middle-aged Veterans (mean age = 34, range = 23-48) underwent brain scans. Participants were divided into: (1) Veteran Controls (n = 27), (2) 1-2 mTBIs (n = 26), and (2) 3+ mTBIs (n = 21) groups. Resting CBF was measured using MP-PCASL. T1 structural scans were processed with FreeSurfer. CBF and cortical thickness estimates were extracted from nine AD-vulnerable regions. Regression analyses examined whether mTBI moderated the association between age, CBF, and cortical thickness. Regressions adjusting for sex and posttraumatic stress revealed mTBI moderated the association between age and CBF of the precuneus as well as superior and inferior parietal cortices (p's < .05); increasing age was associated with lower CBF in the 3+ mTBIs group, but not in the VCs or 1-2 mTBIs groups. mTBI did not moderate associations between age and cortical thickness (p's >.05). Repetitive mTBI is associated with cerebrovascular dysfunction in AD-vulnerable regions and may accelerate pathological aging trajectories.

A roadmap of brain recovery in a mouse model of concussion: insights from neuroimaging

Concussion or mild traumatic brain injury is the most common form of traumatic brain injury with potentially long-term consequences. Current objective diagnosis and treatment options are limited to clinical assessment, cognitive rest, and symptom management, which raises the real danger of concussed patients being released back into activities where subsequent and cumulative injuries may cause disproportionate damages. This study conducted a cross-sectional multi-modal examination investigation of the temporal changes in behavioural and brain changes in a mouse model of concussion using magnetic resonance imaging. Sham and concussed mice were assessed at day 2, day 7, and day 14 post-sham or injury procedures following a single concussion event for motor deficits, psychological symptoms with open field assessment, T2-weighted structural imaging, diffusion tensor imaging (DTI), neurite orientation density dispersion imaging (NODDI), stimulus-evoked and resting-state functional magnetic resonance imaging (fMRI). Overall, a mismatch in the temporal onsets and durations of the behavioural symptoms and structural/functional changes in the brain was seen. Deficits in behaviour persisted until day 7 post-concussion but recovered at day 14 post-concussion. DTI and NODDI changes were most extensive at day 7 and persisted in some regions at day 14 post-concussion. A persistent increase in connectivity was seen at day 2 and day 14 on rsfMRI. Stimulus-invoked fMRI detected increased cortical activation at day 7 and 14 post-concussion. Our results demonstrate the capabilities of advanced MRI in detecting the effects of a single concussive impact in the brain, and highlight a mismatch in the onset and temporal evolution of behaviour, structure, and function after a concussion. These results have significant translational impact in developing methods for the detection of human concussion and the time course of brain recovery.

Evaluation of diffusion measurements reveals radial diffusivity indicative of microstructural damage following acute, mild traumatic brain injury

PURPOSE

Mild TBI, characterized by microstructural damage, often undetectable on conventional imaging techniques, is a pervasive condition that disturbs brain function and can potentially result in long-term deficits. Deciphering the underlying microstructural damage in mild TBI is crucial for establishing a reliable diagnosis and enabling effective therapeutics. Efforts to capture this damage have been extensive, but results have been inconsistent and incomplete.

METHODS

To that effect, we set out to examine the shape of the diffusion tensor in mild TBI during the acute phase of injury. We inspected diffusivity and geometric measurements describing the diffusion tensor's shape and compared mild TBI (N = 34, 20.4-66.6 yo) measurements with those from healthy control (N = 42, 20.7-67.2 yo) participants using voxelwise tract-based spatial statistics. Subsequently, to explore associations between the diffusion measurements in mild TBI, we performed nonparametric statistics and machine learning techniques.

RESULTS

Overall, mild TBI displayed a diffuse increase in D_λ2, D_λ3, D_radial, D_mean, and C_spherical, with a diffuse decrease in A_fractional, A_mode, and C_linear, in addition to no change in D_axial or C_planar. Most notably, our results provide evidence for D_radial as a potential biomarker for microstructural damage, specifically its main component D_λ2, based on their performance in discriminating between mild TBI and control groups. A_fractional was also found to be important for discriminating between groups.

CONCLUSION

Our results revealed the importance of a diffusion measurement often overlooked, D_radial, in assessing TBI and suggest differentiating diffusion measurements has the potential utility to detect variations in the underlying pathophysiology after injury.

Customizing TMS Applications in Traumatic Brain Injury Using Neuroimaging

Optimizing transcranial magnetic stimulation (TMS) treatments in traumatic brain injury (TBI) and co-occurring conditions may benefit from neuroimaging-based customization.

PARTICIPANTS

Our total sample (N = 97) included 58 individuals with TBI (49 mild, 8 moderate, and 1 severe in a state of disordered consciousness), of which 24 had co-occurring conditions (depression in 14 and alcohol use disorder in 10). Of those without TBI, 6 individuals had alcohol use disorder and 33 were healthy controls. Of our total sample, 54 were veterans and 43 were civilians.

DESIGN

Proof-of-concept study incorporating data from 5 analyses/studies that used multimodal approaches to integrate neuroimaging with TMS.

MAIN MEASURES

Multimodal neuroimaging methods including structural magnetic resonance imaging (MRI), MRI-guided TMS navigation, functional MRI, diffusion MRI, and TMS-induced electric fields. Outcomes included symptom scales, neuropsychological tests, and physiological measures.

RESULTS

It is feasible to use multimodal neuroimaging data to customize TMS targets and understand brain-based changes in targeted networks among people with TBI.

CONCLUSIONS

TBI is an anatomically heterogeneous disorder. Preliminary evidence from the 5 studies suggests that using multimodal neuroimaging approaches to customize TMS treatment is feasible. To test whether this will lead to increased clinical efficacy, studies that integrate neuroimaging and TMS targeting data with outcomes are needed.

Blood-Brain Barrier Disruption in Mild Traumatic Brain Injury Patients with Post-Concussion Syndrome: Evaluation with Region-Based Quantification of Dynamic Contrast-Enhanced MR Imaging Parameters Using Automatic Whole-Brain Segmentation

Objective

This study aimed to investigate the blood-brain barrier (BBB) disruption in mild traumatic brain injury (mTBI) patients with post-concussion syndrome (PCS) using dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging and automatic whole brain segmentation.

Materials and Methods

Forty-two consecutive mTBI patients with PCS who had undergone post-traumatic MR imaging, including DCE MR imaging, between October 2016 and April 2018, and 29 controls with DCE MR imaging were included in this retrospective study. After performing three-dimensional T1-based brain segmentation with FreeSurfer software (Laboratory for Computational Neuroimaging), the mean K^trans and v_p from DCE MR imaging (derived using the Patlak model and extended Tofts and Kermode model) were analyzed in the bilateral cerebral/cerebellar cortex, bilateral cerebral/cerebellar white matter (WM), and brainstem. K^trans values of the mTBI patients and controls were calculated using both models to identify the model that better reflected the increased permeability owing to mTBI (tendency toward higher K^trans values in mTBI patients than in controls). The Mann-Whitney U test and Spearman rank correlation test were performed to compare the mean K^trans and v_p between the two groups and correlate K^trans and v_p with neuropsychological tests for mTBI patients.

Results

Increased permeability owing to mTBI was observed in the Patlak model but not in the extended Tofts and Kermode model. In the Patlak model, the mean K^trans in the bilateral cerebral cortex was significantly higher in mTBI patients than in controls (p = 0.042). The mean v_p values in the bilateral cerebellar WM and brainstem were significantly lower in mTBI patients than in controls (p = 0.009 and p = 0.011, respectively). The mean K^trans of the bilateral cerebral cortex was significantly higher in patients with atypical performance in the auditory continuous performance test (commission errors) than in average or good performers (p = 0.041).

Conclusion

BBB disruption, as reflected by the increased K^trans and decreased v_p values from the Patlak model, was observed throughout the bilateral cerebral cortex, bilateral cerebellar WM, and brainstem in mTBI patients with PCS.

Ultra-High-Field Diffusion Tensor Imaging Identifies Discrete Patterns of Concussive Injury in the Rodent Brain

Although concussions can result in persistent neurological post-concussion symptoms, they are typically invisible on routine magnetic resonance imaging (MRI) scans. Our study aimed to investigate the use of ultra-high-field diffusion tensor imaging (UHF-DTI) in discerning severity-dependent microstructural changes in the mouse brain following a concussion. Twenty-three C57BL/6 mice were randomly allocated into three groups: the low concussive (LC, n = 9) injury group, the high concussive (HC, n = 6) injury group, and the sham control (SC, n = 7) group. Mice were perfused on day 2 post-injury, and the brains were scanned on a 16.4T MRI scanner with UHF-DTI and neurite orientation dispersion imaging (NODDI). Finite element analysis (FEA) was performed to determine the pattern and extent of the physical impact on the brain tissue. MRI findings were correlated with histopathological analysis in a subset of mice. In the LC group, increased fractional anisotropy (FA) and decreased orientation dispersion index (ODI) but limited neurite density index (NDI) changes were found in the gray matter, and minimal changes to white matter (WM) were observed. The HC group presented increased mean diffusivity (MD), decreased NDI, and decreased ODI in the WM and gray matter (GM); decreased FA was also found in a small area of the WM. WM changes were associated with WM degeneration and neuroinflammation. FEA showed varying region-dependent degrees of stress, in line with the different imaging findings. This study provides evidence that UHF-DTI combined with NODDI can detect concussions of variable intensities. This has significant implications for the diagnosis of concussion in humans.

Alterations in Network Connectivity after Traumatic Brain Injury in Mice

Victims of mild traumatic brain injury (mTBI) usually do not display clear morphological brain defects, but frequently have long-lasting cognitive deficits, emotional difficulties, and behavioral disturbances. In the present study we used diffusion magnetic resonance imaging (dMRI) combined with graph theory measurements to investigate the effects of mTBI on brain network connectivity. We employed a non-invasive closed-head weight-drop mouse model to produce mTBI. Mice were scanned at two time points, 24 h before the injury and either 7 or 30 days following the injury. Connectivity matrices were computed for each animal at each time point, and these were subsequently used to extract graph theory measures reflecting network integration and segregation, on both the global (i.e., whole brain) and local (i.e., single regions) levels. We found that cluster coefficient, reflecting network segregation, decreased 7 days post-injury and then returned to baseline level 30 days following the injury. Global efficiency, reflecting network integration, demonstrated opposite patterns in the left and right hemispheres, with an increase of right hemisphere efficiency at 7 days and then a decrease in efficiency following 30 days, and vice versa in the left hemisphere. These findings suggest a possible compensation mechanism acting to moderate the influence of mTBI on the global network. Moreover, these results highlight the importance of tracking the dynamic changes in mTBI over time, and the potential of structural connectivity as a promising approach for studying network integrity and pathology progression in mTBI.

Degradation of Praxis Brain Networks and Impaired Comprehension of Manipulable Nouns in Stroke

Distributed brain systems contribute to representation of semantic knowledge. Whether sensory and motor systems of the brain are causally involved in representing conceptual knowledge is an especially controversial question. Here, we tested 57 chronic left-hemisphere stroke patients using a semantic similarity judgment task consisting of manipulable and nonmanipulable nouns. Three complementary methods were used to assess the neuroanatomical correlates of semantic processing: voxel-based lesion-symptom mapping, resting-state functional connectivity, and gray matter fractional anisotropy. The three measures provided converging evidence that injury to the brain networks required for action observation, execution, planning, and visuomotor coordination are associated with specific deficits in manipulable noun comprehension relative to nonmanipulable items. Damage or disrupted connectivity of areas such as the middle posterior temporal gyrus, anterior inferior parietal lobe, and premotor cortex was related specifically to the impairment of manipulable noun comprehension. These results suggest that praxis brain networks contribute especially to the comprehension of manipulable object nouns.

Baseline vs. cross-sectional MRI of concussion: distinct brain patterns in white matter and cerebral blood flow

Neuroimaging has been used to describe the pathophysiology of sport-related concussion during early injury, with effects that may persist beyond medical clearance to return-to-play (RTP). However, studies are typically cross-sectional, comparing groups of concussed and uninjured athletes. It is important to determine whether these findings are consistent with longitudinal change at the individual level, relative to their own pre-injury baseline. A cohort of N = 123 university-level athletes were scanned with magnetic resonance imaging (MRI). Of this group, N = 12 acquired a concussion and were re-scanned at early symptomatic injury and at RTP. A sub-group of N = 44 uninjured athletes were also re-imaged, providing a normative reference group. Among concussed athletes, abnormalities were identified for white matter fractional anisotropy and mean diffusivity, along with grey matter cerebral blood flow, using both cross-sectional (CS) and longitudinal (LNG) approaches. The spatial patterns of abnormality for CS and LNG were distinct, with median fractional overlap below 0.10 and significant differences in the percentage of abnormal voxels. However, the analysis methods did not differ in the amount of change from symptomatic injury to RTP and in the direction of observed abnormalities. These results highlight the impact of using pre-injury baseline data when evaluating concussion-related brain abnormalities at the individual level.

Mild traumatic brain injury impacts associations between limbic system microstructure and post-traumatic stress disorder symptomatology

BACKGROUND

Post-traumatic stress disorder (PTSD) is a psychiatric disorder that afflicts many individuals, yet the neuropathological mechanisms that contribute to this disorder remain to be fully determined. Moreover, it is unclear how exposure to mild traumatic brain injury (mTBI), a condition that is often comorbid with PTSD, particularly among military personnel, affects the clinical and neurological presentation of PTSD. To address these issues, the present study explores relationships between PTSD symptom severity and the microstructure of limbic and paralimbic gray matter brain regions, as well as the impact of mTBI comorbidity on these relationships.

METHODS

Structural and diffusion MRI data were acquired from 102 male veterans who were diagnosed with current PTSD. Diffusion data were analyzed with free-water imaging to quantify average CSF-corrected fractional anisotropy (FA) and mean diffusivity (MD) in 18 limbic and paralimbic gray matter regions. Associations between PTSD symptom severity and regional average dMRI measures were examined with repeated measures linear mixed models. Associations were studied separately in veterans with PTSD only, and in veterans with PTSD and a history of military mTBI.

RESULTS

Analyses revealed that in the PTSD only cohort, more severe symptoms were associated with higher FA in the right amygdala-hippocampus complex, lower FA in the right cingulate cortex, and lower MD in the left medial orbitofrontal cortex. In the PTSD and mTBI cohort, more severe PTSD symptoms were associated with higher FA bilaterally in the amygdala-hippocampus complex, with higher FA bilaterally in the nucleus accumbens, with lower FA bilaterally in the cingulate cortex, and with higher MD in the right amygdala-hippocampus complex.

CONCLUSIONS

These findings suggest that the microstructure of limbic and paralimbic brain regions may influence PTSD symptomatology. Further, given the additional associations observed between microstructure and symptom severity in veterans with head trauma, we speculate that mTBI may exacerbate the impact of brain microstructure on PTSD symptoms, especially within regions of the brain known to be vulnerable to chronic stress. A heightened sensitivity to the microstructural environment of the brain could partially explain why individuals with PTSD and mTBI comorbidity experience more severe symptoms and poorer illness prognoses than those without a history of brain injury. The relevance of these microstructural findings to the conceptualization of PTSD as being a disorder of stress-induced neuronal connectivity loss is discussed.

Evaluating spatiotemporal microstructural alterations following diffuse traumatic brain injury

BACKGROUND

Diffuse traumatic brain injury (TBI) is known to lead to microstructural changes within both white and grey matter detected in vivo with diffusion tensor imaging (DTI). Numerous studies have shown alterations in fractional anisotropy (FA) and mean diffusivity (MD) within prominent white matter tracts, but few have linked these to changes within the grey matter with confirmation via histological assessment. This is especially important as alterations in the grey matter may be predictive of long-term functional deficits.

METHODS

A total of 33 male Sprague Dawley rats underwent severe closed-head TBI. Eight animals underwent tensor-based morphometry (TBM) and DTI at baseline (pre-TBI), 24 hours (24 h), 7, 14, and 30 days post-TBI. Immunohistochemical analysis for the detection of ionised calcium-binding adaptor molecule 1 (IBA1) to assess microglia number and percentage of activated cells, β-amyloid precursor protein (APP) as a marker of axonal injury, and myelin basic protein (MBP) to investigate myelination was performed at each time-point.

RESULTS

DTI showed significant alterations in FA and RD in numerous white matter tracts including the corpus callosum, internal and external capsule, and optic tract and in the grey-matter in the cortex, thalamus, and hippocampus, with the most significant effects observed at 14 D post-TBI. TBM confirmed volumetric changes within the hippocampus and thalamus. Changes in DTI were in line with significant axonal injury noted at 24 h post-injury via immunohistochemical analysis of APP, with widespread microglial activation seen within prominent white matter tracts and the grey matter, which persisted to 30 D within the hippocampus and thalamus. Microstructural alterations in MBP+ve fibres were also noted within the hippocampus and thalamus, as well as the cortex.

CONCLUSION

This study confirms the widespread effects of diffuse TBI on white matter tracts which could be detected via DTI and extends these findings to key grey matter regions, with a comprehensive investigation of the whole brain. In particular, the hippocampus and thalamus appear to be vulnerable to ongoing pathology post-TBI, with DTI able to detect these alterations supporting the clinical utility in evaluating these regions post-TBI.

Mapping brain recovery after concussion: From acute injury to 1 year after medical clearance

OBJECTIVE

To test the hypothesis that concussion-related brain alterations seen at symptomatic injury and medical clearance to return to play (RTP) will have dissipated by 1 year after RTP.

METHODS

For this observational study, 24 athletes with concussion were scanned longitudinally within 1 week after injury, at RTP, and 1 year after RTP. A large control cohort of 122 athletes were also scanned before the season. Each imaging session assessed global functional connectivity (Gconn) and cerebral blood flow (CBF), along with white matter fractional anisotropy (FA) and mean diffusivity (MD). The main effects of concussion on MRI parameters were evaluated at each postinjury time point. In addition, covariation was assessed between MRI parameters and clinical measures of acute symptom severity and time to RTP.

RESULTS

Different aspects of brain physiology showed different patterns of recovery over time. Both Gconn and FA displayed no significant effects at 1 year after RTP, whereas CBF and MD exhibited persistent long-term effects. The effects of concussion on MRI parameters were also dependent on acute symptom severity and time to RTP for all postinjury time points.

CONCLUSION

This study provides the first longitudinal evaluation of concussion focused on time of RTP and 1 year after medical clearance, using multiple different MRI measures to assess brain structure and function. These findings significantly enhance our understanding of the natural course of brain recovery after a concussion.

Relationships Between Subcortical Shape Measures and Subjective Symptom Reporting in US Service Members With Mild Traumatic Brain Injury

OBJECTIVE

To assess interactions of subcortical structure with subjective symptom reporting associated with mild traumatic brain injury (mTBI), using advanced shape analysis derived from volumetric MRI.

PARTICIPANTS

Seventy-six cognitively symptomatic individuals with mTBI and 59 service members sustaining only orthopedic injury.

DESIGN

Descriptive cross-sectional study.

MAIN MEASURES

Self-report symptom measures included the PTSD Checklist-Military, Neurobehavioral Symptom Inventory, and Symptom Checklist-90-Revised. High-dimensional measures of shape characteristics were generated from volumetric MRI for 7 subcortical structures in addition to standard volume measures.

RESULTS

Several significant interactions between group status and symptom measures were observed across the various shape measures. These interactions were revealed in the right thalamus and globus pallidus for each of the shape measures, indicating differences in structure thickness and expansion/contraction for these regions. No relationships with volume were observed.

CONCLUSION

Results provide evidence for the sensitivity of shape measures in differentiating symptomatic mTBI individuals from controls, while volumetric measures did not exhibit this same sensitivity. Disruptions to thalamic nuclei identified here highlight the role of the thalamus in the spectrum of symptoms associated with mTBI. Additional work is needed to prospectively, and longitudinally, assess these measures along with cognitive performance and advanced multimodal imaging methods to extend the utility of shape analysis in relation to functional outcomes in this population.

Combining white matter diffusion and geometry for tract-specific alignment and variability analysis

We present a framework for along-tract analysis of white matter (WM) fiber bundles based on diffusion tensor imaging (DTI) and tractography. We introduce the novel concept of fiber-flux density for modeling fiber tracts' geometry, and combine it with diffusion-based measures to define vector descriptors called Fiber-Flux Diffusion Density (FFDD). The proposed model captures informative features of WM tracts at both the microscopic (diffusion-related) and macroscopic (geometry-related) scales, thus enabling improved sensitivity to subtle structural abnormalities that are not reflected by either diffusion or geometrical properties alone. A key step in this framework is the construction of an FFDD dissimilarity measure for sub-voxel alignment of fiber bundles, based on the fast marching method (FMM). The obtained aligned WM tracts enable meaningful inter-subject comparisons and group-wise statistical analysis. Moreover, we show that the FMM alignment can be generalized in a straight forward manner to a single-shot co-alignment of multiple fiber bundles. The proposed alignment technique is shown to outperform a well-established, commonly used DTI registration algorithm. We demonstrate the FFDD framework on the Human Connectome Project (HCP) diffusion MRI dataset, as well as on two different datasets of contact sports players. We test our method using longitudinal scans of a basketball player diagnosed with a traumatic brain injury, showing compatibility with structural MRI findings. We further perform a group study comparing mid- and post-season scans of 13 active football players exposed to repetitive head trauma, to 17 non-player control (NPC) subjects. Results reveal statistically significant FFDD differences (p-values<0.05) between the groups, as well as increased abnormalities over time at spatially-consistent locations within several major fiber tracts of football players.

Plasma Tau and Amyloid Are Not Reliably Related to Injury Characteristics, Neuropsychological Performance, or White Matter Integrity in Service Members with a History of Traumatic Brain Injury

The aim of this study was to examine the relationship between plasma tau and amyloid beta-42 (Aβ42), neuropsychological functioning, and white matter integrity in U.S. military service members with (n = 155) and without (n = 42) a history of uncomplicated mild (n = 83), complicated mild (n = 26), or moderate, severe, or penetrating (n = 46) traumatic brain injury (TBI). We hypothesized that higher levels of tau and Aβ42 would be related to reduced neurocognitive performance and white matter integrity. Participants were enrolled prospectively from Walter Reed National Military Medical Center. Participants completed a blood draw, neuropsychological assessment, and diffusion tensor imaging (General Electric 3T) of the whole brain. From 20 neuropsychological test scores, five cognitive domain scores were computed. Measures of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were generated for 18 regions of interest (ROIs). There was no relationship found between the plasma biomarkers and neurocognitive performance in any of the three TBI groups (all ps >0.05; all R² changes <0.146). Although not reaching statistical significance after correction for multiple comparisons, higher tau and Aβ42 tended to be related to higher FA and lower MD, RD, and AD in patients with a history of moderate, severe, or penetrating TBI. There was no consistent relationship between either of the biomarkers and white matter integrity in the complicated and uncomplicated mild TBI groups. In addition, there was no significant relationship between the biomarkers and age, education, sex, race, bodily injury severity, time since injury, TBI severity, or number of TBIs (all ps >0.15). Future investigation in larger samples of moderate, severe, and penetrating TBI are needed. Other plasma biomarkers, including phosphorylated tau, exosomal tau, and interleukin-10, may be more promising measures to use in the diagnosis, management, and treatment of TBI.

Spatial distribution bias in subject-specific abnormalities analyses

The neuroimaging community has seen a renewed interest in algorithms that provide a location-independent summary of subject-specific abnormalities (SSA) to assess individual lesion load. More recently, these methods have been extended to assess whether multiple individuals within the same cohort exhibit extrema in the same spatial location (e.g., voxel or region of interest). However, the statistical validity of this approach has not been rigorously established. The current study evaluated the potential for a spatial bias in the distribution of SSA using several common z-transformation algorithms (leave-one-out [LOO]; independent sample [IDS]; Enhanced Z-Score Microstructural Assessment of Pathology [EZ-MAP]; distribution-corrected z-scores [DisCo-Z]) using both simulated data and DTI data from 50 healthy controls. Results indicated that methods which z-transformed data based on statistical moments from a reference group (LOO, DisCo-Z) led to bias in the spatial location of extrema for the comparison group. In contrast, methods that z-transformed data using an independent third group (EZ-MAP, IDS) resulted in no spatial bias. Importantly, none of the methods exhibited bias when results were summed across all individual elements. The spatial bias is primarily driven by sampling error, in which differences in the mean and standard deviation of the untransformed data have a higher probability of producing extrema in the same spatial location for the comparison but not reference group. In conclusion, evaluating SSA overlap within cohorts should be either be avoided in deference to established group-wise comparisons or performed only when data is available from an independent third group.

An evaluation of Z-transform algorithms for identifying subject-specific abnormalities in neuroimaging data

The need for algorithms that capture subject-specific abnormalities (SSA) in neuroimaging data is increasingly recognized across many neuropsychiatric disorders. However, the effects of initial distributional properties (e.g., normal versus non-normally distributed data), sample size, and typical preprocessing steps (spatial normalization, blurring kernel and minimal cluster requirements) on SSA remain poorly understood. The current study evaluated the performance of several commonly used z-transform algorithms [leave-one-out (LOO); independent sample (IDS); Enhanced Z-score Microstructural Assessment of Pathology (EZ-MAP); distribution-corrected z-scores (DisCo-Z); and robust z-scores (ROB-Z)] for identifying SSA using simulated and diffusion tensor imaging data from healthy controls (N = 50). Results indicated that all methods (LOO, IDS, EZ-MAP and DisCo-Z) with the exception of the ROB-Z eliminated spurious differences that are present across artificially created groups following a standard z-transform. However, LOO and IDS consistently overestimated the true number of extrema (i.e., SSA) across all sample sizes and distributions. The EZ-MAP and DisCo-Z algorithms more accurately estimated extrema across most distributions and sample sizes, with the exception of skewed distributions. DTI results indicated that registration algorithm (linear versus non-linear) and blurring kernel size differentially affected the number of extrema in positive versus negative tails. Increasing the blurring kernel size increased the number of extrema, although this effect was much more prominent when a minimum cluster volume was applied to the data. In summary, current results highlight the need to statistically compare the frequency of SSA in control samples or to develop appropriate confidence intervals for patient data.

Utilizing Mutual Information Analysis to Explore the Relationship Between Gray and White Matter Structural Pathologies in Schizophrenia

Schizophrenia has been characterized as a neurodevelopmental disorder, with structural brain abnormalities reported at all stages. However, at present, it remains unclear whether gray and white matter abnormalities represent related or independent pathologies in schizophrenia. In this study, we present findings from an integrative analysis exploring the morphological relationship between gray and white matter in 45 schizophrenia participants and 49 healthy controls. We utilized mutual information (MI), a measure of how much information two variables share, to assess the morphological dependence between gray and white matter in three segments of the corpus callsoum, and the gray matter regions these segments connect: (1) the genu and the left and right rostral middle frontal gyrus (rMFG), (2) the isthmus and the left and right superior temporal gyrus (STG), (3) the splenium and the left and right lateral occipital gyrus (LOG). We report significantly reduced MI between white matter tract dispersion of the right hemispheric callosal connections to the STG and both cortical thickness and area in the right STG in schizophrenia patients, despite a lack of group differences in cortical thickness, surface area, or dispersion. We believe that this reduction in morphological dependence between gray and white matter may reflect a possible decoupling of the developmental processes that shape morphological features of white and gray matter early in life. The present study also demonstrates the importance of studying the relationship between gray and white matter measures, as opposed to restricting analyses to gray and white matter measures independently.

Diffusion kurtosis imaging in mild traumatic brain injury and postconcussional syndrome

Aims of this study were to investigate white matter (WM) and thalamus microstructure 72 hr and 3 months after mild traumatic brain injury (TBI) with diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI), and to relate DKI and DTI findings to postconcussional syndrome (PCS). Twenty-five patients (72 hr = 24; 3 months = 23) and 22 healthy controls were recruited, and DKI and DTI data were analyzed with Tract-Based Spatial Statistics (TBSS) and a region-of-interest (ROI) approach. Patients were categorized into PCS or non-PCS 3 months after injury according to the ICD-10 research criteria for PCS. In TBSS analysis, significant differences between patients and controls were seen in WM, both in the acute stage and 3 months after injury. Fractional anisotropy (FA) reductions were more widespread than kurtosis fractional anisotropy (KFA) reductions in the acute stage, while KFA reductions were more widespread than the FA reductions at 3 months, indicating the complementary roles of DKI and DTI. When comparing patients with PCS (n = 9), without PCS (n = 16), and healthy controls, in the ROI analyses, no differences were found in the acute DKI and DTI metrics. However, near-significant differences were observed for several DKI metrics obtained in WM and thalamus concurrently with symptom assessment (3 months after injury). Our findings indicate a combined utility of DKI and DTI in detecting WM microstructural alterations after mild TBI. Moreover, PCS may be associated with evolving alterations in brain microstructure, and DKI may be a promising tool to detect such changes.

Imaging of Concussion in Young Athletes

Conventional neuroimaging examinations are typically normal in concussed young athletes. A current focus of research is the characterization of subtle abnormalities after concussion using advanced neuroimaging techniques. These techniques have the potential to identify biomarkers of concussion. In the future, such biomarkers will likely provide important clinical information regarding the appropriate time interval before return to play, as well as the risk for prolonged postconcussive symptoms and long-term cognitive impairment. This article discusses results from advanced imaging techniques and emphasizes imaging modalities that will likely become available in the near future for the clinical evaluation of concussed young athletes.

White matter abnormalities in mild traumatic brain injury with and without post-traumatic stress disorder: a subject-specific diffusion tensor imaging study

Mild traumatic brain injuries (mTBIs) are often associated with posttraumatic stress disorder (PTSD). In cases of chronic mTBI, accurate diagnosis can be challenging due to the overlapping symptoms this condition shares with PTSD. Furthermore, mTBIs are heterogeneous and not easily observed using conventional neuroimaging tools, despite the fact that diffuse axonal injuries are the most common injury. Diffusion tensor imaging (DTI) is sensitive to diffuse axonal injuries and is thus more likely to detect mTBIs, especially when analyses account for the inter-individual variability of these injuries. Using a subject-specific approach, we compared fractional anisotropy (FA) abnormalities between groups with a history of mTBI (n = 35), comorbid mTBI and PTSD (mTBI + PTSD; n = 22), and healthy controls (n = 37). We compared all three groups on the number of abnormal FA clusters derived from subject-specific injury profiles (i.e., individual z-score maps) along a common white matter skeleton. The mTBI + PTSD group evinced a greater number of abnormally low FA clusters relative to both the healthy controls and the mTBI group without PTSD (p < .05). Across the groups with a history of mTBI, increased numbers of abnormally low FA clusters were significantly associated with PTSD symptom severity, depression, post-concussion symptoms, and reduced information processing speed (p < .05). These findings highlight the utility of subject-specific microstructural analyses when searching for mTBI-related brain abnormalities, particularly in patients with PTSD. This study also suggests that patients with a history of mTBI and comorbid PTSD, relative to those without PTSD, are at increased risk of FA abnormalities.

Mild Traumatic Brain Injury Induces Structural and Functional Disconnection of Local Neocortical Inhibitory Networks via Parvalbumin Interneuron Diffuse Axonal Injury

Diffuse axonal injury (DAI) plays a major role in cortical network dysfunction posited to cause excitatory/inhibitory imbalance after mild traumatic brain injury (mTBI). Current thought holds that white matter (WM) is uniquely vulnerable to DAI. However, clinically diagnosed mTBI is not always associated with WM DAI. This suggests an undetected neocortical pathophysiology, implicating GABAergic interneurons. To evaluate this possibility, we used mild central fluid percussion injury to generate DAI in mice with Cre-driven tdTomato labeling of parvalbumin (PV) interneurons. We followed tdTomato+ profiles using confocal and electron microscopy, together with patch-clamp analysis to probe for DAI-mediated neocortical GABAergic interneuron disruption. Within 3 h post-mTBI tdTomato+ perisomatic axonal injury (PSAI) was found across somatosensory layers 2-6. The DAI marker amyloid precursor protein colocalized with GAD67 immunoreactivity within tdTomato+ PSAI, representing the majority of GABAergic interneuron DAI. At 24 h post-mTBI, we used phospho-c-Jun, a surrogate DAI marker, for retrograde assessments of sustaining somas. Via this approach, we estimated DAI occurs in ~9% of total tdTomato+ interneurons, representing ~14% of pan-neuronal DAI. Patch-clamp recordings of tdTomato+ interneurons revealed decreased inhibitory transmission. Overall, these data show that PV interneuron DAI is a consistent and significant feature of experimental mTBI with important implications for cortical network dysfunction.

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI) in revealing white matter (WM) plasticity. In this work, we focused on the main open issues left: (1) the comparative analysis with respect to classical tensor-derived indices, i.e., Fractional Anisotropy (FA) and Mean Diffusivity (MD); and (2) the ability to detect plasticity processes in gray matter (GM). Although signal modeling in GM is still largely unexplored, we investigated their sensibility to stroke-induced microstructural modifications occurring in the contralateral hemisphere. A more complete picture could provide hints for investigating the interplay of GM and WM modulations. Ten stroke patients and ten age/gender-matched healthy controls were enrolled in the study and underwent diffusion spectrum imaging (DSI). Acquisitions at three and two time points (tp) were performed on patients and controls, respectively. For all subjects and acquisitions, FA and MD were computed along with 3D-SHORE-based indices [Generalized Fractional Anisotropy (GFA), Propagator Anisotropy (PA), Return To the Axis Probability (RTAP), Return To the Plane Probability (RTPP), and Mean Square Displacement (MSD)]. Tract-based analysis involving the cortical, subcortical and transcallosal motor networks and region-based analysis in GM were successively performed, focusing on the contralateral hemisphere to the stroke. Reproducibility of all the indices on both WM and GM was quantitatively proved on controls. For tract-based, longitudinal group analyses revealed the highest significant differences across the subcortical and transcallosal networks for all the indices. The optimal regression model for predicting the clinical motor outcome at tp3 included GFA, PA, RTPP, and MSD in the subcortical network in combination with the main clinical information at baseline. Region-based analysis in the contralateral GM highlighted the ability of anisotropy indices in discriminating between groups mainly at tp1, while diffusivity indices appeared to be altered at tp2. 3D-SHORE indices proved to be suitable in probing plasticity in both WM and GM, further confirming their viability as a novel family of biomarkers in ischemic stroke in WM and revealing their potential exploitability in GM. Their combination with tensor-derived indices can provide more detailed insights of the different tissue modulations related to stroke pathology.

Pairwise, Ordinal Outlier Detection of Traumatic Brain Injuries

Because mild Traumatic Brain Injuries (mTBI) are heterogeneous, classification methods perform outlier detection from a model of healthy tissue. Such a model is challenging to construct. Instead, we utilize region-specific pairwise (person-to-person) comparisons. Each person-region is characterized by a distribution of Fractional Anisotropy and comparisons are made via Median, Mean, Bhattacharya and Kullback-Liebler distances. Additionally, we examine an ordinal decision rule which compares a subject's nth most atypical region to a healthy control's. Ordinal comparison is motivated by mTBI's heterogeneity; each mTBI has some set of damaged tissue which is not necessarily spatially consistent. These improvements correctly distinguish Persistent Post-Concussive Symptoms in a small dataset but achieve only a .74 AUC in identifying mTBI subjects with milder symptoms. Finally, we perform subject-specific simulations which characterize which injuries are detected and which are missed.

Lower Fractional Anisotropy in the Gray Matter of Amygdala-Hippocampus-Nucleus Accumbens Circuit in Methamphetamine Users: an In Vivo Diffusion Tensor Imaging Study

The basolateral amygdala (BLA), hippocampal ventral subiculum, and nucleus accumbens (NAc) comprise the amygdala-hippocampus-NAc (AHN) circuit, which is implicated in drug seeking and reward. The goal of this study was to evaluate microstructural changes and relevant clinical features of the AHN circuit gray matter (GM) in methamphetamine (MA) users using diffusion tensor imaging (DTI). Thirty MA users and 30 age-matched normal volunteers underwent 3-T MR imaging to obtain structural T1-weighted images and DTI data. Freesurfer software was used to automatically segment the NAc and subiculum. A Jülich probability map was employed to parcellate the BLA. Fractional anisotropy (FA) and mean diffusivity (MD) maps were generated and non-linearly coregistered to structural space. DTI measures of the AHN circuit GM were compared between MA users and controls using repeated measures analysis of variance. Correlation analyses were performed between DTI measures and clinical characteristics. Anatomical correlations between the NAc and BLA/subiculum in both groups were assessed using correlation analyses. The MA group had significant lower FA in the bilateral BLA, subiculum, and NAc. Higher total MA dose corresponded with lower FA in all three structures. Hamilton Anxiety Rating Scale scores negatively correlated with the right subiculum FA. Lower left BLA FA was associated with higher thinking disorder and hostile-suspicion factor scores. Left BLA FA was significantly associated with bilateral NAc FA in MA users. Those findings provided neuroimaging evidence of MA-induced microstructural impairment in the AHN circuit GM. Enhanced anatomical correlations between the left BLA and bilateral NAc may be part of the mechanism of MA intake relapse and for development of psychosis.

Free water improves detection of changes in the substantia nigra in parkinsonism: A multisite study

BACKGROUND

Imaging markers that are sensitive to parkinsonism across multiple sites are critically needed for clinical trials. The objective of this study was to evaluate changes in the substantia nigra using single- and bi-tensor models of diffusion magnetic resonance imaging in PD, MSA, and PSP.

METHODS

The study cohort (n = 425) included 107 healthy controls and 184 PD, 63 MSA, and 71 PSP patients from 3 movement disorder centers. Bi-tensor free water, free-water-corrected fractional anisotropy, free-water-corrected mean diffusivity, single-tensor fractional anisotropy, and single-tensor mean diffusivity were computed for the anterior and posterior substantia nigra. Correlations were computed between diffusion MRI measures and clinical measures.

RESULTS

In the posterior substantia nigra, free water was greater for PSP than MSA and PD patients and controls. PD and MSA both had greater free water than controls. Free-water-corrected fractional anisotropy values were greater for PSP patents than for controls and PD patients. PSP and MSA patient single-tensor mean diffusivity values were greater than controls, and single-tensor fractional anisotropy values were lower for PSP patients than for healthy controls. The parkinsonism effect size for free water was 0.145 in the posterior substantia nigra and 0.072 for single-tensor mean diffusivity. The direction of correlations between single-tensor mean diffusivity and free-water values and clinical scores was similar at each site.

CONCLUSIONS

Free-water values in the posterior substantia nigra provide a consistent pattern of findings across patients with PD, MSA, and PSP in a large cohort across 3 sites. Free water in the posterior substantia nigra relates to clinical measures of motor and cognitive symptoms in a large cohort of parkinsonism. © 2017 International Parkinson and Movement Disorder Society.

A Mechanistic End-to-End Concussion Model That Translates Head Kinematics to Neurologic Injury

Past concussion studies have focused on understanding the injury processes occurring on discrete length scales (e.g., tissue-level stresses and strains, cell-level stresses and strains, or injury-induced cellular pathology). A comprehensive approach that connects all length scales and relates measurable macroscopic parameters to neurological outcomes is the first step toward rationally unraveling the complexity of this multi-scale system, for better guidance of future research. This paper describes the development of the first quantitative end-to-end (E2E) multi-scale model that links gross head motion to neurological injury by integrating fundamental elements of tissue and cellular mechanical response with axonal dysfunction. The model quantifies axonal stretch (i.e., tension) injury in the corpus callosum, with axonal functionality parameterized in terms of axonal signaling. An internal injury correlate is obtained by calculating a neurological injury measure (the average reduction in the axonal signal amplitude) over the corpus callosum. By using a neurologically based quantity rather than externally measured head kinematics, the E2E model is able to unify concussion data across a range of exposure conditions and species with greater sensitivity and specificity than correlates based on external measures. In addition, this model quantitatively links injury of the corpus callosum to observed specific neurobehavioral outcomes that reflect clinical measures of mild traumatic brain injury. This comprehensive modeling framework provides a basis for the systematic improvement and expansion of this mechanistic-based understanding, including widening the range of neurological injury estimation, improving concussion risk correlates, guiding the design of protective equipment, and setting safety standards.