White Matter Changes in Posttraumatic Stress Disorder Following Mild Traumatic Brain Injury: A Prospective Longitudinal Diffusion Tensor Imaging Study

Affective Visual Circuit Dysfunction in Trauma and Stress-Related Disorders

Posttraumatic stress disorder (PTSD) is widely recognized as involving disruption of core neurocircuitry that underlies processing, regulation, and response to threat. In particular, the prefrontal cortex-hippocampal-amygdala circuit is a major contributor to posttraumatic dysfunction. However, the functioning of core threat neurocircuitry is partially dependent on sensorial inputs, and previous research has demonstrated that dense, reciprocal connections exist between threat circuits and the ventral visual stream. Furthermore, emergent evidence suggests that trauma exposure and resultant PTSD symptoms are associated with altered structure and function of the ventral visual stream. In the current review, we discuss evidence that both threat and visual circuitry together are an integral part of PTSD pathogenesis. An overview of the relevance of visual processing to PTSD is discussed in the context of both basic and translational research, highlighting the impact of stress on affective visual circuitry. This review further synthesizes emergent literature to suggest potential timing-dependent effects of traumatic stress on threat and visual circuits that may contribute to PTSD development. We conclude with recommendations for future research to move the field toward a more complete understanding of PTSD neurobiology.

Lifetime Blast Exposure Is Not Related to White Matter Integrity in Service Members and Veterans With and Without Uncomplicated Mild Traumatic Brain Injury

This study examines the impact of lifetime blast exposure on white matter integrity in service members and veterans (SMVs). Participants were 227 SMVs, including those with a history of mild traumatic brain injury (mTBI; n = 124), orthopedic injury controls (n = 58), and non-injured controls (n = 45), prospectively enrolled in a Defense and Veterans Brain Injury Center (DVBIC)/Traumatic Brain Injury Center of Excellence (TBICoE) study. Participants were divided into three groups based on number of self-reported lifetime blast exposures: none (n = 53); low (i.e., 1-9 blasts; n = 81); and high (i.e., ≥10 blasts; n = 93). All participants underwent diffusion tensor imaging (DTI) at least 11 months post-injury. Tract-of-interest (TOI) analysis was applied to investigate fractional anisotropy and mean, radial, and axial diffusivity (AD) in left and right total cerebral white matter as well as 24 tracts. Benjamini-Hochberg false discovery rate (FDR) correction was used. Regressions investigating blast exposure and mTBI on white matter integrity, controlling for age, revealed that the presence of mTBI history was associated with lower AD in the bilateral superior longitudinal fasciculus and arcuate fasciculus and left cingulum (βs = -0.255 to -0.174; ps < 0.01); however, when non-injured controls were removed from the sample (but orthopedic injury controls remained), these relationships were attenuated and did not survive FDR correction. Regression models were rerun with modified post-traumatic stress disorder (PTSD) diagnosis added as a predictor. After FDR correction, PTSD was not significantly associated with white matter integrity in any of the models. Overall, there was no relationship between white matter integrity and self-reported lifetime blast exposure or PTSD.

White matter predictors of PTSD: Testing different machine learning models in a sample of Black American women

BACKGROUND

Machine learning neuroimaging studies of posttraumatic stress disorder (PTSD) show promise for identifying neurobiological signatures of PTSD. However, studies to date, have largely evaluated a single machine learning approach, and few studies have examined white matter microstructure as a predictor of PTSD. Further, individuals from minoritized racial groups, specifically, Black individuals, who experience disproportionate trauma frequency, and have relatively higher rates of PTSD, have been underrepresented in these studies. We used four different machine learning models to test white matter microstructure classifiers of PTSD in a sample of trauma-exposed Black American women with and without PTSD.

METHOD

Participants included 45 Black women with PTSD and 89 trauma-exposed controls recruited from an ongoing trauma study. Current PTSD presence was estimated using the Clinician-Administered PTSD Scale. Average fractional anisotropy of 53 white matter tracts served as input features. Additional exploratory analysis incorporated estimates of interpersonal and structural racism exposure. Classification models included linear support vector machine, radial basis function support vector machine, multilayer perceptron, and random forest.

RESULTS

Performance varied notably between models. With white matter features along, linear support vector machine demonstrated the best model fit and reached an average AUC = 0.643. Inclusion of estimates of exposure to racism increased linear support vector machine performance (AUC = 0.808).

CONCLUSIONS

White matter microstructure had limited ability to predict PTSD presence in this sample. These results may indicate that the relationship between white matter microstructure and PTSD may be nuanced across race and gender spectrums.

Plasma neurofilament light admission levels and development of axonal pathology in mild traumatic brain injury

BACKGROUND

It is known that blood levels of neurofilament light (NF-L) and diffusion-weighted magnetic resonance imaging (DW-MRI) are both associated with outcome of patients with mild traumatic brain injury (mTBI). Here, we sought to examine the association between admission levels of plasma NF-L and white matter (WM) integrity in post-acute stage DW-MRI in patients with mTBI.

METHODS

Ninety-three patients with mTBI (GCS ≥ 13), blood sample for NF-L within 24 h of admission, and DW-MRI ≥ 90 days post-injury (median = 229) were included. Mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated from the skeletonized WM tracts of the whole brain. Outcome was assessed using the Extended Glasgow Outcome Scale (GOSE) at the time of imaging. Patients were divided into CT-positive and -negative, and complete (GOSE = 8) and incomplete recovery (GOSE < 8) groups.

RESULTS

The levels of NF-L and FA correlated negatively in the whole cohort (p = 0.002), in CT-positive patients (p = 0.016), and in those with incomplete recovery (p = 0.005). The same groups showed a positive correlation with mean MD, AD, and RD (p < 0.001-p = 0.011). In CT-negative patients or in patients with full recovery, significant correlations were not found.

CONCLUSION

In patients with mTBI, the significant correlation between NF-L levels at admission and diffusion tensor imaging (DTI) measurements of diffuse axonal injury (DAI) over more than 3 months suggests that the early levels of plasma NF-L may associate with the presence of DAI at a later phase of TBI.

Mild traumatic brain injury history is associated with lower brain network resilience in soldiers

Special Operations Forces combat soldiers sustain frequent blast and blunt neurotrauma, most often classified as mild traumatic brain injuries. Exposure to repetitive mild traumatic brain injuries is associated with persistent behavioural, cognitive, emotional and neurological symptoms later in life. Identifying neurophysiological changes associated with mild traumatic brain injury exposure, in the absence of present-day symptoms, is necessary for detecting future neurological risk. Advancements in graph theory and functional MRI have offered novel ways to analyse complex whole-brain network connectivity. Our purpose was to determine how mild traumatic brain injury history, lifetime incidence and recency affected whole-brain graph theoretical outcome measures. Healthy male Special Operations Forces combat soldiers (age = 33.2 ± 4.3 years) underwent multimodal neuroimaging at a biomedical research imaging centre using 3T Siemens Prisma or Biograph MRI scanners in this cross-sectional study. Anatomical and functional scans were preprocessed. The blood-oxygen-level-dependent signal was extracted from each functional MRI time series using the Big Brain 300 atlas. Correlations between atlas regions were calculated and Fisher z-transformed to generate subject-level correlation matrices. The Brain Connectivity Toolbox was used to obtain functional network measures for global efficiency (the average inverse shortest path length), local efficiency (the average global efficiency of each node and its neighbours), and assortativity coefficient (the correlation coefficient between the degrees of all nodes on two opposite ends of a link). General linear models were fit to compare mild traumatic brain injury lifetime incidence and recency. Nonparametric ANOVAs were used for tests on non-normally distributed data. Soldiers with a history of mild traumatic brain injury had significantly lower assortativity than those who did not self-report mild traumatic brain injury (t148 = 2.44, P = 0.016). The assortativity coefficient was significantly predicted by continuous mild traumatic brain injury lifetime incidence [F1,144 = 6.51, P = 0.012]. No differences were observed between recency groups, and no global or local efficiency differences were observed between mild traumatic brain injury history and lifetime incidence groups. Brain networks with greater assortativity have more resilient, interconnected hubs, while those with lower assortativity indicate widely distributed, vulnerable hubs. Greater lifetime mild traumatic brain injury incidence predicted lower assortativity in our study sample. Less resilient brain networks may represent a lack of physiological recovery in mild traumatic brain injury patients, who otherwise demonstrate clinical recovery, more vulnerability to future brain injury and increased risk for accelerated age-related neurodegenerative changes. Future longitudinal studies should investigate whether decreased brain network resilience may be a predictor for long-term neurological dysfunction.

Heart and brain traumatic stress biomarker analysis with and without machine learning: A scoping review

The enigma of post-traumatic stress disorder (PTSD) is embedded in a complex array of physiological responses to stressful situations that result in disruptions in arousal and cognitions that characterise the psychological disorder. Deciphering these physiological patterns is complex, which has seen the use of machine learning (ML) grow in popularity. However, it is unclear to what extent ML has been used with physiological data, specifically, the electroencephalogram (EEG) and electrocardiogram (ECG) to further understand the physiological responses associated with PTSD. To better understand the use of EEG and ECG biomarkers, with and without ML, a scoping review was undertaken. A total of 124 papers based on adult samples were identified comprising 19 ML studies involving EEG and ECG. A further 21 studies using EEG data, and 84 studies employing ECG meeting all other criteria but not employing ML were included for comparison. Identified studies indicate classical ML methodologies currently dominate EEG and ECG biomarkers research, with derived biomarkers holding clinically relevant diagnostic implications for PTSD. Discussion of the emerging trends, algorithms used and their success is provided, along with areas for future research.

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.

Immune-metabolic mechanisms of post-traumatic stress disorder and atherosclerosis

The interaction of post-traumatic stress disorder (PTSD) and atherosclerosis (AS) increase the risk of mortality. Metabolism and immunity play important roles in the comorbidity associated with PTSD and AS. The adenosine monophosphate-activated protein kinase/mammalian target of rapamycin and phosphatidylinositol 3-kinase/Akt pathways are attractive research topics in the fields of metabolism, immunity, and autophagy. They may be effective intervention targets in the prevention and treatment of PTSD comorbidity with AS. Herein, we comprehensively review metabolic factors, including glutamate and lipid alterations, in PTSD comorbidity with AS and discuss the possible implications in the pathophysiology of the diseases.

Structural covariance of the ventral visual stream predicts posttraumatic intrusion and nightmare symptoms: a multivariate data fusion analysis

Visual components of trauma memories are often vividly re-experienced by survivors with deleterious consequences for normal function. Neuroimaging research on trauma has primarily focused on threat-processing circuitry as core to trauma-related dysfunction. Conversely, limited attention has been given to visual circuitry which may be particularly relevant to posttraumatic stress disorder (PTSD). Prior work suggests that the ventral visual stream is directly related to the cognitive and affective disturbances observed in PTSD and may be predictive of later symptom expression. The present study used multimodal magnetic resonance imaging data (n = 278) collected two weeks after trauma exposure from the AURORA study, a longitudinal, multisite investigation of adverse posttraumatic neuropsychiatric sequelae. Indices of gray and white matter were combined using data fusion to identify a structural covariance network (SCN) of the ventral visual stream 2 weeks after trauma. Participant's loadings on the SCN were positively associated with both intrusion symptoms and intensity of nightmares. Further, SCN loadings moderated connectivity between a previously observed amygdala-hippocampal functional covariance network and the inferior temporal gyrus. Follow-up MRI data at 6 months showed an inverse relationship between SCN loadings and negative alterations in cognition in mood. Further, individuals who showed decreased strength of the SCN between 2 weeks and 6 months had generally higher PTSD symptom severity over time. The present findings highlight a role for structural integrity of the ventral visual stream in the development of PTSD. The ventral visual stream may be particularly important for the consolidation or retrieval of trauma memories and may contribute to efficient reactivation of visual components of the trauma memory, thereby exacerbating PTSD symptoms. Potentially chronic engagement of the network may lead to reduced structural integrity which becomes a risk factor for lasting PTSD symptoms.

Neuroimaging in professional combat sports: consensus statement from the association of ringside physicians

Professional boxing, kickboxing, and mixed martial arts (MMA) are popular sports with substantial risk for both acute and chronic traumatic brain injury (TBI). Although rare, combat sports athletes have died in the ring or soon after the completion of a bout. Deaths in these instances are usually the result of an acute catastrophic neurological event such as an acute subdural hematoma (SDH). Other causes may include acute epidural hematoma (EDH), subarachnoid hemorrhage (SAH), intraparenchymal hemorrhage (IPH), or a controversial, rare, and still disputed clinical entity called second-impact syndrome (SIS). Neuroimaging or brain imaging is currently included in the process of registering for a license to compete in combat sports in some jurisdictions of the United States of America and around the world. However, the required imaging specifics and frequency vary with no consensus guidelines. The Association of Ringside Physicians (an international, nonprofit organization dedicated to the health and safety of the combat sports athlete) sets forth this consensus statement to establish neuroimaging guidelines in combat sports. Commissions, ringside physicians, combat sports athletes, trainers, promoters, sanctioning bodies, and other healthcare professionals can use this statement for risk stratification of a professional combat sports athlete prior to licensure, identifying high-risk athletes and for prognostication of the brain health of these athletes over the course of their career. Guidelines are also put forth regarding neuroimaging requirements in the immediate aftermath of a bout.

Detection of Chronic Blast-Related Mild Traumatic Brain Injury with Diffusion Tensor Imaging and Support Vector Machines

Blast-related mild traumatic brain injury (bmTBI) often leads to long-term sequalae, but diagnostic approaches are lacking due to insufficient knowledge about the predominant pathophysiology. This study aimed to build a diagnostic model for future verification by applying machine-learning based support vector machine (SVM) modeling to diffusion tensor imaging (DTI) datasets to elucidate white-matter features that distinguish bmTBI from healthy controls (HC). Twenty subacute/chronic bmTBI and 19 HC combat-deployed personnel underwent DTI. Clinically relevant features for modeling were selected using tract-based analyses that identified group differences throughout white-matter tracts in five DTI metrics to elucidate the pathogenesis of injury. These features were then analyzed using SVM modeling with cross validation. Tract-based analyses revealed abnormally decreased radial diffusivity (RD), increased fractional anisotropy (FA) and axial/radial diffusivity ratio (AD/RD) in the bmTBI group, mostly in anterior tracts (29 features). SVM models showed that FA of the anterior/superior corona radiata and AD/RD of the corpus callosum and anterior limbs of the internal capsule (5 features) best distinguished bmTBI from HCs with 89% accuracy. This is the first application of SVM to identify prominent features of bmTBI solely based on DTI metrics in well-defined tracts, which if successfully validated could promote targeted treatment interventions.

A Systematic Review and Meta-Analysis of Lipid Signatures in Post-traumatic Stress Disorder

BACKGROUND

Research assessing lipid levels in individuals diagnosed with post-traumatic stress disorder (PTSD) has yielded mixed results. This study aimed to employ meta-analytic techniques to characterize the relationship between the levels of lipid profiles and PTSD.

METHODS

We performed meta-analyses of studies comparing profiles and levels of lipids between PTSD patients and healthy individuals by searching Embase, Ovid Medline, Scopus, PsycINFO, and Cochrane databases for the studies until March 2021. Meta-analyses were performed using random-effects models with the restricted maximum-likelihood estimator to synthesize the effect size assessed by standardized mean difference (SMD) across studies.

FINDINGS

A total of 8,657 abstracts were identified, and 17 studies were included. Levels of total cholesterol (TC) (SMD = 0.57 95% CI, 0.27-0.87, p = 0.003), low-density lipoprotein (LDL) (SMD = 0.48, 95% CI, 0.19-0.76, p = 0.004), and triglyceride (TG) (SMD = 0.46, 95% CI, 0.22-0.70, p = 0.001) were found to be higher, while levels of high-density lipoprotein (HDL) (SMD = -0.47, -0.88 to -0.07, p = 0.026) were found to be lower in PTSD patients compared to healthy controls. Subgroup analysis showed that TG levels were higher in PTSD patients who were on or off of psychotropic medications, both < 40 and ≥ 40 years of age, and having body mass index of < 30 and ≥ 30 compared to healthy controls.

INTERPRETATION

This work suggested dysregulation of lipids in PTSD that may serve as biomarker to predict the risk. The study will be useful for physicians considering lipid profiles in PTSD patients to reduce cardiovascular morbidity and mortality.

A systematic review and data synthesis of longitudinal changes in white matter integrity after mild traumatic brain injury assessed by diffusion tensor imaging in adults

PURPOSE

This study aimed to review diffusion tensor imaging studies of mild traumatic brain injury (mTBI) in adults with longitudinal acquisition of data and investigate the variability of findings in association with related factors, such as the time post-injury.

METHODS

Eligible studies from PubMed and EMBASE were searched to identify relevant studies for review. Of the 540 studies, 23 observational studies without intervention and with the following characteristics were included: original research in which adults with mTBI were examined, diffusion tensor imaging was acquired at least twice, white matter integrity was investigated by estimating diffusion metrics, and mode of injury was not restricted to sport- or blast-related mTBI.

RESULTS

Baseline scans were acquired within 3 weeks post-injury, followed by longitudinal scans within 3 months and at 12 months post-injury. During the acute/subacute period, mixed results (increase, decrease, or no significant change) of fractional anisotropy (FA) were observed compared to those in controls. Some studies reported increased FA during the acute/subacute period compared to controls, followed by normalization of FA. Decreased FA was also reported during the acute/subacute period, which lasted long into the chronic phase. In the acute phase, the mean diffusivity (MD) was greater than that in the controls. Compared to the early phase of injury, MD was reduced in the follow-up phase in most studies in the mTBI group. Insignificant differences in FA and MD have been reported in several studies. Such variability limits the clinical usefulness of diffusion tensor metrics.

CONCLUSIONS

There was a high variability in reported changes in white matter integrity. Decreased FA not only in acute/subacute but also in long-term period after injury may indicate long-term neurodegenerative processes after mTBI. Nevertheless, longitudinal changes in MD towards normalization suggest possible recovery. Long-term cohort studies with research initiatives should be considered to elucidate brain changes after mTBI.

Neural contributors to trauma resilience: a review of longitudinal neuroimaging studies

Resilience in the face of major life stressors is changeable over time and with experience. Accordingly, differing sets of neurobiological factors may contribute to an adaptive stress response before, during, and after the stressor. Longitudinal studies are therefore particularly effective in answering questions about the determinants of resilience. Here we provide an overview of the rapidly-growing body of longitudinal neuroimaging research on stress resilience. Despite lingering gaps and limitations, these studies are beginning to reveal individual differences in neural circuit structure and function that appear protective against the emergence of future psychopathology following a major life stressor. Here we outline a neural circuit model of resilience to trauma. Specifically, pre-trauma biomarkers of resilience show that an ability to modulate activity within threat and salience networks predicts fewer stress-related symptoms. In contrast, early post-trauma biomarkers of subsequent resilience or recovery show a more complex pattern, spanning a number of major circuits including attention and cognitive control networks as well as primary sensory cortices. This novel synthesis suggests stress resilience may be scaffolded by stable individual differences in the processing of threat cues, and further buttressed by post-trauma adaptations to the stressor that encompass multiple mechanisms and circuits. More attention and resources supporting this work will inform the targets and timing of mechanistic resilience-boosting interventions.

Hybrid diffusion imaging reveals altered white matter tract integrity and associations with symptoms and cognitive dysfunction in chronic traumatic brain injury

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Hybrid Diffusion Imaging (HYDI) detects white matter associations in patients with cTBI.

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The advanced diffusion model NODDI was more sensitive in detecting between-group differences than classic DTI.

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DTI appeared to be just as sensitive as NODDI for detecting white matter correlations with self-reported symptoms.

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This study highlights the advantages of acquiring both DTI and NODDI to fully characterize white matter microstructure in cTBI.

The detection and association of in vivo biomarkers in white matter (WM) pathology after acute and chronic mild traumatic brain injury (mTBI) are needed to improve care and develop therapies. In this study, we used the diffusion MRI method of hybrid diffusion imaging (HYDI) to detect white matter alterations in patients with chronic TBI (cTBI). 40 patients with cTBI presenting symptoms at least three months post injury, and 17 healthy controls underwent magnetic resonance HYDI. cTBI patients were assessed with a battery of neuropsychological tests. A voxel-wise statistical analysis within the white matter skeleton was performed to study between group differences in the diffusion models. In addition, a partial correlation analysis controlling for age, sex, and time after injury was performed within the cTBI cohort, to test for associations between diffusion metrics and clinical outcomes. The advanced diffusion modeling technique of neurite orientation dispersion and density imaging (NODDI) showed large clusters of between-group differences resulting in lower values in the cTBI across the brain, where the single compartment diffusion tensor model failed to show any significant results. However, the diffusion tensor model appeared to be just as sensitive in detecting self-reported symptoms in the cTBI population using a within-group correlation. To the best of our knowledge this study provides the first application of HYDI in evaluation of cTBI using combined DTI and NODDI, significantly enhancing our understanding of the effects of concussion on white matter microstructure and emphasizing the utility of full characterization of complex diffusion to diagnose, monitor, and treat brain injury.

Is Higher Subjective Fear Predictive of Post-Traumatic Stress Symptoms in a Sample of the Chinese General Public?

Background: COVID-19 has taken a huge toll on medical resources and the economy and will inevitably have an impact on public mental health. Post-traumatic stress disorder (PTSD), as the most common mental illness after an epidemic, must be seriously addressed. This study aimed to investigate the subjective fear of the Chinese general public during COVID-19 and to explore how it affected the development of PTSD. Methods: An online questionnaire survey was conducted among 1,009 people from January 30 to February 14, 2020 (about 1 month after the COVID-19 outbreak). The subjective fear was measured by a self-reported single-choice question. Four items from the Pittsburgh Sleep Quality Index (PSQI) were selected to measure the subjects' sleep quality. Their post-traumatic stress symptoms (PTSS) were measured by the PTSD Checklist for DSM-5 (PCL-5). Pearson correlation, hierarchical multivariate regression analysis, multiple mediator model, and bootstrapping were used in statistical analyses. Results: Different people showed different levels of subjective fear in response to the outbreak. There was a significant positive correlation between subjective fear and the total score of PCL-5 (R = 0.513, P < 0.01), meaning that the higher the degree of subjective fear, the more severe the symptoms of post-traumatic stress are. Subjective fear was an important predictor of PTSS, accounting for 24.3% of the variance. The total effect of subjective fear on PCL-5 scores was significant (total effect = 7.426, SE = 0.405, 95% CI = 6.631-8.221). The total indirect effect of subjective fear on PCL-5 scores through sleep quality was also significant (total indirect effect = 1.945, SE = 0.258, 95% CI = 1.436-2.470). Conclusions: Subjective fear has an important predictive effect on PTSS. In addition to the direct effect, our findings firstly demonstrate the mediating role of sleep quality in the relationship between subjective fear and PTSS.

Neuroimaging in the Diagnosis of Chronic Traumatic Encephalopathy: A Systematic Review

OBJECTIVE

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repeated subconcussive and concussive head injury. Clinical features include cognitive, behavioral, mood, and motor impairments. Definitive diagnosis is only possible at postmortem. Here, the utility of neuroimaging in the diagnosis of CTE is evaluated by systematically reviewing recent evidence for changes in neuroimaging biomarkers in suspected cases of CTE compared with controls.

DATA SOURCES

Providing an update on a previous systematic review of articles published until December 2014, we searched for articles published between December 2014 and July 2016. We searched PubMed for studies assessing neuroimaging changes in symptomatic suspected cases of CTE with a history of repeated subconcussive or concussive head injury or participation in contact sports involving direct impact to the head. Exclusion criteria were case studies, review articles, and articles focusing on repetitive head trauma from military service, head banging, epilepsy, physical abuse, or animal models.

MAIN RESULTS

Seven articles met the review criteria, almost all of which studied professional athletes. The range of modalities were categorized into structural magnetic resonance imaging (MRI), diffusion MRI, and radionuclide studies. Biomarkers which differed significantly between suspected CTE and controls were Evans index (P = 0.05), cavum septum pellucidum (CSP) rate (P < 0.0006), length (P < 0.03) and ratio of CSP length to septum length (P < 0.03), regional differences in axial diffusivity (P < 0.05) and free/intracellular water fractions (P < 0.005), single-photon emission computed tomography perfusion abnormalities (P < 0.01), positron emission tomography (PET) signals from tau-binding, glucose-binding, and GABA receptor-binding radionuclides (P < 0.0001, P < 0.005, and P < 0.005, respectively). Important limitations include low specificity in identification of suspected cases of CTE across studies, the need for postmortem validation, and a lack of generalizability to nonprofessional athletes.

CONCLUSIONS

The most promising biomarker is tau-binding radionuclide PET signal because it is most specific to the underlying neuropathology and differentiated CTE from both controls and patients with Alzheimer disease (P < 0.0001). Multimodal imaging will improve specificity further. Future research should minimize variability in identification of suspected cases of CTE using published clinical criteria.

The use of machine learning techniques in trauma-related disorders: a systematic review

Establishing the diagnosis of trauma-related disorders such as Acute Stress Disorder (ASD) and Posttraumatic Stress Disorder (PTSD) have always been a challenge in clinical practice and in academic research, due to clinical and biological heterogeneity. Machine learning (ML) techniques can be applied to improve classification of disorders, to predict outcomes or to determine person-specific treatment selection. We aim to review the existing literature on the use of machine learning techniques in the assessment of subjects with ASD or PTSD. We systematically searched PubMed, Embase and Web of Science for articles published in any language up to May 2019. We found 806 abstracts and included 49 studies in our review. Most of the included studies used multiple levels of biological data to predict risk factors or to identify early symptoms related to PTSD. Other studies used ML classification techniques to distinguish individuals with ASD or PTSD from other psychiatric disorder or from trauma-exposed and healthy controls. We also found studies that attempted to define outcome profiles using clustering techniques and studies that assessed the relationship among symptoms using network analysis. Finally, we proposed a quality assessment in this review, evaluating methodological and technical features on machine learning studies. We concluded that etiologic and clinical heterogeneity of ASD/PTSD patients is suitable to machine learning techniques and a major challenge for the future is to use it in clinical practice for the benefit of patients in an individual level.

Widespread White Matter Aberrations Are Associated with Phonemic Verbal Fluency Impairment in Chronic Traumatic Brain Injury

Microstructural white matter (WM) disruption and resulting abnormal structural connectivity form a potential underlying pathology in traumatic brain injury (TBI). Herein, to determine the potential mechanism of cognitive deterioration in TBI, we examined the association of damage to specific WM tracts with cognitive function in TBI patients. We recruited 18 individuals with mild-to-moderate/severe TBI in the chronic phase and 17 age-matched controls. We determined the pattern of WM aberrations in TBI using tract-based spatial statistics (TBSS) and then examined the relationship between cognitive impairment and WM damage using the threshold-free cluster enhancement correction in TBSS. TBSS analysis showed that TBI patients exhibited WM aberrations in a wide range of brain regions. In the majority of these regions, lower fractional anisotropy (FA) largely overlapped with increased radial diffusivity, but not with axial diffusivity. Further, voxel-wise correction in TBSS demonstrated that higher FA values were associated with better performance in the phonemic verbal fluency task (VFT) in widespread WM regions, but not with the semantic VFT. Despite variation in the magnitude and location of brain injury between individual cases, chronic TBI patients exhibited widespread WM aberrations. We confirmed the findings of previous studies that WM integrity is lower across the spectrum of TBI severity in chronic subjects compared to controls. Further, phonemic VFT may be a more sensitive cognitive measure of executive dysfunction associated with WM aberrations in TBI compared with semantic VFT.

Emerging Approaches to Neurocircuits in PTSD and TBI: Imaging the Interplay of Neural and Emotional Trauma

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) commonly co-occur in general and military populations and have a number of overlapping symptoms. While research suggests that TBI is risk factor for PTSD and that PTSD may mediate TBI-related outcomes, the mechanisms of these relationships are not well understood. Neuroimaging may help elucidate patterns of neurocircuitry both specific and common to PTSD and TBI and thus help define the nature of their interaction, refine diagnostic classification, and may potentially yield opportunities for targeted treatments. In this review, we provide a summary of some of the most common and the most innovative neuroimaging approaches used to characterize the neural circuits associated with PTSD, TBI, and their comorbidity. We summarize the state of the science for each disorder and describe the few studies that have explicitly attempted to characterize the neural substrates of their shared and dissociable influence. While some promising targets in the medial frontal lobes exist, there is not currently a comprehensive understanding of the neurocircuitry mediating the interaction of PTSD and TBI. Future studies should exploit innovative neuroimaging approaches and longitudinal designs to specifically target the neural mechanisms driving PTSD-TBI-related outcomes.

Diffusion kurtosis imaging of microstructural changes in brain tissue affected by acute ischemic stroke in different locations

The location of an acute ischemic stroke is associated with its prognosis. The widely used Gaussian model-based parameter, apparent diffusion coefficient (ADC), cannot reveal microstructural changes in different locations or the degree of infarction. This prospective observational study was reviewed and approved by the Institutional Review Board of Xiamen Second Hospital, China (approval No. 2014002). Diffusion kurtosis imaging (DKI) was used to detect 199 lesions in 156 patients with acute ischemic stroke (61 males and 95 females), mean age 63.15 ± 12.34 years. A total of 199 lesions were located in the periventricular white matter (n = 52), corpus callosum (n = 14), cerebellum (n = 29), basal ganglia and thalamus (n = 21), brainstem (n = 21) and gray-white matter junctions (n = 62). Percentage changes of apparent diffusion coefficient (ΔADC) and DKI-derived indices (fractional anisotropy [ΔFA], mean diffusivity [ΔMD], axial diffusivity [ΔD_a], radial diffusivity ΔD_r, mean kurtosis [ΔMK], axial kurtosis [ΔK_a], and radial kurtosis [ΔK_r]) of each lesion were computed relative to the normal contralateral region. The results showed that (1) there was no significant difference in ΔADC, ΔMD, ΔD_a or ΔD_r among almost all locations. (2) There was significant difference in ΔMK among almost all locations (except basal ganglia and thalamus vs. brain stem; basal ganglia and thalamus vs. gray-white matter junctions; and brainstem vs. gray-white matter junctions. (3) The degree of change in diffusional kurtosis in descending order was as follows: corpus callosum > periventricular white matter > brainstem > gray-white matter junctions > basal ganglia and thalamus > cerebellum. In conclusion, DKI could reveal the differences in microstructure changes among various locations affected by acute ischemic stroke, and performed better than diffusivity among all groups.

Diffusion Tensor Imaging Analysis of Mild Traumatic Brain Injury and Posttraumatic Stress Disorder

BACKGROUND

Debate exists over the extent to which dysfunctions arising from mild traumatic brain injury (mTBI) are distinct from posttraumatic stress disorder (PTSD).

METHODS

This study investigated 1) the white matter integrity of participants with either mTBI or PTSD, and 2) the relationship between white matter integrity and postconcussive syndrome. The sample comprised 110 civilians (mTBI group = 40; PTSD group = 32; age- and sex-matched trauma-exposed control subjects = 38) recruited from community advertising. Indicators of white matter abnormalities were fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. PTSD symptoms were indexed by the Clinician-Administered PTSD Scale, and postconcussive symptoms were assessed using the Somatic and Psychological Health Report measure.

RESULTS

Fractional anisotropy was reduced in mTBI participants in the corpus callosum, tracts of the brainstem, projection fibers, association fibers, and limbic fibers compared with both PTSD and trauma-exposed control subjects. This decrease in fractional anisotropy was observed in the context of concurrent changes in radial diffusivity, axial diffusivity, and mean diffusivity. Postconcussive symptoms were largely explained by PTSD severity rather than by changes in brain white matter. mTBI appears to be characterized by distinct reductions in white matter integrity, and this cannot be attributed to PTSD.

CONCLUSIONS

PTSD symptoms appear to be more strongly associated with postconcussive syndrome than with white matter compromise. These findings extend epidemiological evidence of the relative associations of PTSD and mTBI with postconcussive syndrome.

Diffusion MRI in acute nervous system injury

Diffusion weighted magnetic resonance imaging (DWI) and related techniques such as diffusion tensor imaging (DTI) are uniquely sensitive to the microstructure of the brain and spinal cord. In the acute aftermath of nervous system injury, for example, DWI reveals changes caused by injury that remains invisible on other MRI contrasts such as T₂-weighted imaging. This ability has led to a demonstrated clinical utility in cerebral ischemia. However, despite strong promise in preclinical models and research settings, DWI has not been as readily adopted for other acute injuries such as traumatic spinal cord, brain, or peripheral nerve injury. Furthermore, the precise biophysical mechanisms that underlie DWI and DTI changes are not fully understood. In this report, we review the DWI and DTI changes that occur in acute neurological injury of cerebral ischemia, spinal cord injury, traumatic brain injury, and peripheral nerve injury. Their associations with the underlying biology are examined with an emphasis on the role of acute axon and dendrite beading. Lastly, emerging DWI techniques to overcome the limitations of DTI are discussed as these may offer the needed improvements to translate to clinical settings.

Hyperbaric Oxygen Therapy Can Induce Angiogenesis and Regeneration of Nerve Fibers in Traumatic Brain Injury Patients

Background: Recent clinical studies in stroke and traumatic brain injury (TBI) victims suffering chronic neurological injury present evidence that hyperbaric oxygen therapy (HBOT) can induce neuroplasticity. Objective: To assess the neurotherapeutic effect of HBOT on prolonged post-concussion syndrome (PPCS) due to TBI, using brain microstructure imaging. Methods: Fifteen patients afflicted with PPCS were treated with 60 daily HBOT sessions. Imaging evaluation was performed using Dynamic Susceptibility Contrast-Enhanced (DSC) and Diffusion Tensor Imaging (DTI) MR sequences. Cognitive evaluation was performed by an objective computerized battery (NeuroTrax). Results: HBOT was initiated 6 months to 27 years (10.3 ± 3.2 years) from injury. After HBOT, DTI analysis showed significantly increased fractional anisotropy values and decreased mean diffusivity in both white and gray matter structures. In addition, the cerebral blood flow and volume were increased significantly. Clinically, HBOT induced significant improvement in the memory, executive functions, information processing speed and global cognitive scores. Conclusions: The mechanisms by which HBOT induces brain neuroplasticity can be demonstrated by highly sensitive MRI techniques of DSC and DTI. HBOT can induce cerebral angiogenesis and improve both white and gray microstructures indicating regeneration of nerve fibers. The micro structural changes correlate with the neurocognitive improvements.