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The extant literature investigating the relationship between diffusion tensor imaging (DTI) and cognition following traumatic brain injury (TBI) is limited by small sample sizes and inappropriate control groups. The present study examined DTI metric differences between service members and veterans (SMVs) with bodily injury (Trauma Control; TC), uncomplicated mild TBI (mTBI), complicated mild TBI (compTBI), and severe-moderate TBI combined (smTBI), and how DTI metrics related to cognition within each group. Participants were 226 SMVs (56 TC, 112 mTBI, 29 compTBI, 29 smTBI) with valid neuropsychological testing and DTI at least 11 months post-injury. The smTBI group demonstrated decreased fractional anisotropy (FA) and increased axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) of the cerebral white matter (CWM) and several individual white matter tracts compared with the TC, mTBI, and compTBI groups (all

Introduction: Comorbid mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common in military service members. The aim of this study is to investigate brain metabolic i...

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.

Post-traumatic stress disorder (PTSD) is commonly observed in military service members with mild traumatic brain injury (mTBI); however, the relationship between mTBI and PTSD is complex and not well understood. The present study aims to elucidate a link between the degree of alteration in limbic system-related white matter tracts and PTSD symptoms in an mTBI population. Diffusion-tensor imaging (DTI) with probabilistic tractography of the fronto-limbic pathways revealed decreased white matter integrity in the uncinate fasciculus in those with co-morbid mTBI and PTSD (n = 34), relative to those with only mTBI (n = 35). Additionally, fractional anisotropy (FA) and radial diffusivity (RD) measures in the bilateral uncinate fasciculus correlated with Post-Traumatic Stress Disorder Checklist Civilian version (PCL-C) scores, and primarily within the avoidance and re-experiencing domains. Findings from this study suggest the degree of traumatic injury within the limbic system could be directly related to post-traumatic stress and post-concussive symptoms, with disrupted white matter leading to significant PTSD outcomes.

The aim of this study was to examine neuropsychological functioning and white matter integrity, in service members and veterans (SMVs) after mild traumatic brain injury (MTBI), with versus without post-traumatic stress disorder (PTSD). Participants were 116 U.S. military SMVs, prospectively enrolled from the Walter Reed National Military Medical Center (Bethesda, MD), who had sustained an MTBI (

Introduction Traumatic brain injury (TBI) plagues service members in times of war and training. Diagnosis and management of TBI remain challenging, with many suffering from sleep disorders. We hypothesized that TBI-related damage to the hypothalamus, a master regulator of breathing and sleep, could be related to post-TBI obstructive sleep apnea (OSA) and serve as a pathophysiological biomarker for a subpopulation of OSA patients. Methods This was a retrospective study of warfighters with TBI from the National Intrepid Center of Excellence (NICoE). Subjects were identified by severe TBI on neuroimaging and compared against a control group without TBI. All subjects underwent screening polysomnography (PSG). MRI was acquired via 3T scanner. The hypothalamus was automatically segmented using a diffeomorphic algorithm. DTI scalar values were analyzed with scalar t-tests between subjects and controls. Generalized linear modeling with DTI scalar values was used to predict AHI in subjects. Results 6 subjects and 61 controls were identified. There was significant sleep dysfunction amongst TBI subjects (mean apnea-hypopnea index (AHI) 5.1+/-6.6 events/hour; mild OSA incidence 33.3%; Pittsburgh Sleep Quality Index (PSQI) mean 13.3+/-2.6). Radial diffusivity (RD), axial diffusivity (AD) and mean diffusivity (MD) were significantly higher among subjects (control RD 9.64x10^-10+/-7.54x10^-11 m^2/s, subject RD 1.13x10^-9+/-1.20x10^-10m^2/s, p = 0.023; control AD 1.32x10^-9+/-7.64x10^-11m^2/s, subject AD 1.50x10^-9+/-1.43x10^-10m^2/s, p = 0.029; control MD 1.08x10^-9+/-7.43x10^-11m^2/s, subject MD 1.25x10^-9+/-1.34x10^-10m^2/s, p = 0.025). There were no differences in age or body-mass index. Generalized linear modeling with diffusivity measures as predictors of AHI in subjects was not significant. Conclusion Using a diffeomorphic algorithm to define the hypothalamus reveals significantly elevated scalar DTI measures in chronic, severe TBI compared to controls. DTI differences in the hypothalamus are a novel finding and possibly underlie part of the pathophysiology of TBI. Although this may have potential to serve as a biomarker in severe TBI patients with sleep disorders, these initial data do not support a relationship between DTI and AHI, despite high incidence of OSA and subjective sleep dysfunction. Future studies with more subjects may better elucidate the changes in hypothalamic DTI after TBI for clinical outcomes analysis. Support (if any) This work was supported by grant 130132 from USAMRMC.

The purpose of this study was to examine the relation between white matter integrity of the brain and postconcussion symptom reporting following mild traumatic brain injury (MTBI).Participants were 109 U.S. military service members (91.7% male) who had sustained a MTBI (n = 88) or orthopedic injury without TBI (trauma controls, TC, n = 21), enrolled from the Walter Reed National Military Medical Center, Bethesda, Maryland. Participants completed a battery of neurobehavioral symptom measures and underwent diffusion tensor imaging (DTI; General Electric 3T) of the whole brain, on average 44.9 months post injury (SD = 42.3). Measures of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were generated for 18 regions of interest (ROIs). Participants in the MTBI group were divided into two subgroups based on International Classification of Diseases-10th Revision (ICD-10) Category C criteria for postconcussion syndrome (PCS): PCS-present (n = 41) and PCS-absent (n = 47).The PCS-present group had significantly worse scores on all 13 neurobehavioral measures than the PCS-absent group (p .001, d = 0.87-2.50) and TC group (p .003, d = 0.84-2.06). For all ROIs, there were no significant main effects across the three groups for FA, MD, AD, and RD (all ps.03). Pairwise comparisons revealed no significant differences for all ROIs when using FA and RD, and only two significant pairwise differences were found between PCS-present and PCS-absent groups when using MD and AD [i.e., anterior thalamic radiation and cingulate gyrus (supracallosal) bundle].Consistent with past research, but not all studies, postconcussion symptom reporting was not associated with white matter integrity in the subacute to chronic phase of recovery following MTBI.

Brain venous volume above the lateral ventricle in military patients with traumatic brain injury (TBI) was assessed using two segmentation approaches on susceptibility weighted images (SWI) and quantitative susceptibility maps (QSM). This retrospective study included a total of 147 subjects: 14 patients with severe TBI; 38 patients with moderate TBI, 58 patients with mild TBI (28 with blast-related injuries and 30 with non-blast-related injuries), and 37 control subjects without history of TBI. Using the multiscale vessel enhancement filter on SWI images, patients with severe TBI demonstrated significantly higher segmented venous volumes compared with controls. Using a threshold approach on QSM images, TBI patients with different severities all demonstrated increased segmented volumes compared with control subjects: in the whole brain (severe

The aim of this study was to apply recently developed automated fiber segmentation and quantification methods using diffusion tensor imaging (DTI) and DTI‐based deterministic and probabilistic tractography to access local and global diffusion changes in blast‐induced mild traumatic brain injury (bmTBI). Two hundred and two (202) male active US service members who reported persistent post‐concussion symptoms for more than 6 months after injury were recruited. An additional forty (40) male military controls were included for comparison. DTI results were examined in relation to post‐concussion and post‐traumatic stress disorder (PTSD) symptoms. No significant group difference in DTI metrics was found using voxel‐wise analysis. However, group comparison using tract profile analysis and tract specific analysis, as well as single subject analysis using tract profile analysis revealed the most prominent white matter microstructural injury in chronic bmTBI patients over the frontal fiber tracts, that is, the front‐limbic projection fibers (cingulum bundle, uncinate fasciculus), the fronto‐parieto‐temporal association fibers (superior longitudinal fasciculus), and the fronto‐striatal pathways (anterior thalamic radiation). Effects were noted to be sensitive to the number of previous blast exposures, with a negative association between fractional anisotropy (FA) and time since most severe blast exposure in a subset of the multiple blast‐exposed group. However, these patterns were not observed in the subgroups classified using macrostructural changes (T2 white matter hyperintensities). Moreover, post‐concussion symptoms and PTSD symptoms, as well as neuropsychological function were associated with low FA in the major nodes of compromised neurocircuitry. Hum Brain Mapp 38:352–369, 2017. © 2016 Wiley Periodicals, Inc.

To detect cerebral microhemorrhages in military service members with chronic traumatic brain injury by using susceptibility-weighted magnetic resonance (MR) imaging. The longitudinal evolution of microhemorrhages was monitored in a subset of patients by using quantitative susceptibility mapping.The study was approved by the Walter Reed National Military Medical Center institutional review board and is compliant with HIPAA guidelines. All participants underwent two-dimensional conventional gradient-recalled-echo MR imaging and three-dimensional flow-compensated multiecho gradient-recalled-echo MR imaging (processed to generate susceptibility-weighted images and quantitative susceptibility maps), and a subset of patients underwent follow-up imaging. Microhemorrhages were identified by two radiologists independently. Comparisons of microhemorrhage number, size, and magnetic susceptibility derived from quantitative susceptibility maps between baseline and follow-up imaging examinations were performed by using the paired t test.Among the 603 patients, cerebral microhemorrhages were identified in 43 patients, with six excluded for further analysis owing to artifacts. Seventy-seven percent (451 of 585) of the microhemorrhages on susceptibility-weighted images had a more conspicuous appearance than on gradient-recalled-echo images. Thirteen of the 37 patients underwent follow-up imaging examinations. In these patients, a smaller number of microhemorrhages were identified at follow-up imaging compared with baseline on quantitative susceptibility maps (mean ± standard deviation, 9.8 microhemorrhages ± 12.8 vs 13.7 microhemorrhages ± 16.6; P = .019). Quantitative susceptibility mapping-derived quantitative measures of microhemorrhages also decreased over time: -0.85 mm(3) per day ± 1.59 for total volume (P = .039) and -0.10 parts per billion per day ± 0.14 for mean magnetic susceptibility (P = .016).The number of microhemorrhages and quantitative susceptibility mapping-derived quantitative measures of microhemorrhages all decreased over time, suggesting that hemosiderin products undergo continued, subtle evolution in the chronic stage.

Introduction While sleep disorders occur in 40–70% of chronic traumatic brain injury (TBI) patients, the pathophysiology remains unknown. Increasingly, DTI has been used to evaluate gray matter structures, but no prior studies have evaluated hypothalamic regions in TBI. We hypothesized that TBI patients with poor sleep quality by questionnaire and/or polysomnography (PSG) may have structural injury to hypothalamic sleep circuitry and that this may be detectable by diffusion magnetic resonance imaging (dMRI). We examined diffusion tensor parameters in warfighters using dMRI within the hypothalamus of poor sleepers and compared them to good sleepers. Methods A retrospective review of 92 warfighters with blast TBI and loss of consciousness included demographics, structural MRI, dMRI, PSG and Pittsburgh Sleep Quality Index (PSQI) questionnaire. Acquisition of diffusion-weighted and structural data was performed with three Tesla MRI. Using the California Institute of Technology probabilistic high-resolution in vivo atlas as a prior, the hypothalamic nuclei were segmented by applying diffeomorphic registration of T1- and T2-weighted structural images and mapped to dMRI space. Results TBI patients within the lowest quartile of hypothalamic fractional anisotropy (FA) measures demonstrated decreased total sleep time (320 +/- 52 minutes vs. 382 +/- 19, p=0.006) on PSG and had more sleep complaints on PSQI (p=0.029) compared to those with the highest quartile of FA measures. There was no difference in BMI, age or AHI among the quartiles. Radial, mean and axial diffusivity quartiles did not carry significant differences in TST or PSQI. Linear models did not show significant correlation between any imaging parameter and sleep quality measures. Conclusion Our results reveal microstructural differences in the hypothalami of military TBI patients that may be related to clinical sleep dysfunction. Biomarkers of sleep circuitry damage may further our understanding of sleep dysfunction after TBI. Lack of correlations in linear models may be a reflection of the small sample size or a complex interaction, and removal of outliers did not change our results. Larger longitudinal studies may help clarify the association between hypothalamic and brainstem circuitry structure after TBI and sleep dysfunction. Support This work was supported by a grant 130132 from USAMRMC.

The trajectory of regional volume changes during the first year of sustained abstinence in those recovering from an alcohol use disorder is unclear because previous research typically employed only two assessment points. To better understand the trajectory of regional brain volume recovery in treatment-seeking alcohol-dependent individuals (ALC), regional brain volumes were measured after 1 week, 1 month and 7.5 months of sustained abstinence via magnetic resonance imaging at 1.5 T. ALC showed significant volume increases in frontal, parietal and occipital gray matter (GM) and white matter (WM), total cortical GM and total lobar WM, thalamus and cerebellum, and decreased ventricular volume over 7.5 months of abstinence. Volume increases in regional GM were significantly greater over 1 week to 1 month than from 1 month to 7.5 months of abstinence, indicating a non-linear rate of change in regional GM over 7.5 months. Overall, regional lobar WM showed linear volume increases over 7.5 months. With increasing age, smoking ALC showed lower frontal and total cortical GM volume recovery than non-smoking ALC. Despite significant volume increases, ALC showed smaller GM volumes in all regions, except the frontal cortex, than controls after 7.5 months of abstinence. ALC and controls showed no regional WM volume differences at any assessment point. In non-smoking ALC only, increasing regional GM and WM volumes were related to improving processing speed. Findings may indicate a differential rate of recovery of cell types/cellular components contributing to GM and WM volume during early abstinence, and that GM volume deficits persist after 7.5 months of sustained sobriety in this ALC cohort.

Traumatic brain injury (TBI) is a common combat injury, often through explosive blast, and produces heterogeneous brain changes due to various mechanisms of injury. It is unclear whether the vulnerability of white matter differs between blast and impact injury, and the consequences of microstructural changes on neuropsychological function are poorly understood in military TBI patients. Diffusion tensor imaging (DTI) techniques were used to assess the neurocircuitry in 37 U.S. service members (29 mild, 7 moderate, 1 severe; 17 blast and 20 nonblast), who sustained a TBI while deployed, compared to 14 nondeployed, military controls. High-dimensional deformable registration of MRI diffusion tensor data was followed by fiber tracking and tract-specific analysis along with region-of-interest analysis. DTI results were examined in relation to post-concussion and post-traumatic stress disorder (PTSD) symptoms. The most prominent white matter microstructural injury for both blast and nonblast patients was in the frontal fibers within the fronto-striatal (corona radiata, internal capsule) and fronto-limbic circuits (fornix, cingulum), the fronto-parieto-occipital association fibers, in brainstem fibers, and in callosal fibers. Subcortical superior-inferiorly oriented tracts were more vulnerable to blast injury than nonblast injury, while direct impact force had more detrimental effects on anterior-posteriorly oriented tracts, which tended to cause heterogeneous left and right hemispheric asymmetries of white matter connectivity. The tractography using diffusion anisotropy deficits revealed the cortico-striatal-thalamic-cerebellar-cortical (CSTCC) networks, where increased post-concussion and PTSD symptoms were associated with low fractional anisotropy in the major nodes of compromised CSTCC neurocircuitry, and the consequences on cognitive function were explored as well.

Perfusion deficits in patients with mild traumatic brain injury (TBI) from a military population were characterized by dynamic susceptibility contrast perfusion imaging. Relative cerebral blood flow (rCBF) was calculated by a model-independent deconvolution approach from the tracer concentration curves following a bolus injection of gadolinium diethylenetriaminepentaacetate (Gd-DTPA) using both manually and automatically selected arterial input functions (AIFs). Linear regression analysis of the mean values of rCBF from selected regions of interest showed a very good agreement between the two approaches, with a regression coefficient of R = 0.88 and a slope of 0.88. The Bland–Altman plot also illustrated the good agreement between the two approaches, with a mean difference of 0.6 ± 12.4 mL/100 g/min. Voxelwise analysis of rCBF maps from both approaches demonstrated multiple clusters of decreased perfusion (p

Traumatic axonal injury is a progressive process evoked by shear forces on the brain, gradually evolving from focal axonal alteration and cumulating in neural disconnection. Clinical classifiers and conventional neuroimaging are limited in traumatic axonal injury detection, outcome prediction, and treatment guidance. Diffusion weighted imaging is an advanced magnetic resonance imaging (MRI) technique that is sensitive to the movement of water molecules, providing additional information on the micro-structural arrangement of tissue. Quantitative analysis of diffusion metrics can aid in the localization of axonal injury and/or de(dys)myelination caused by trauma. Diffusion MRI tractography is an extension of diffusion weighted imaging, and can provide additional information about white matter pathways and the integrity of brain neural networks. Both techniques are able to detect the early micro-structural changes caused by Traumatic Brain Injury (TBI), and can be used to increase understanding of the mechanisms of brain plasticity in recovery after brain injury and possibly optimize treatment planning of patients with Traumatic Brain Injury. This review focuses on the theoretical basis and applied advanced techniques of diffusion weighted imaging, their limitations and applications, and future directions in the application to TBI.

To describe the initial neuroradiology findings in a cohort of military service members with primarily chronic mild traumatic brain injury (TBI) from blast by using an integrated magnetic resonance (MR) imaging protocol.This study was approved by the Walter Reed National Military Medical Center institutional review board and is compliant with HIPAA guidelines. All participants were military service members or dependents recruited between August 2009 and August 2014. There were 834 participants with a history of TBI and 42 participants in a control group without TBI (not explicitly age- and sex-matched). MR examinations were performed at 3 T primarily with three-dimensional volume imaging at smaller than 1 mm(3) voxels for the structural portion of the examination. The structural portion of this examination, including T1-weighted, T2-weighted, before and after contrast agent administrtion T2 fluid attenuation inversion recovery, and susceptibility-weighted images, was evaluated by neuroradiologists by using a modified version of the neuroradiology TBI common data elements (CDEs). Incident odds ratios (ORs) between the TBI participants and a comparison group without TBI were calculated.The 834 participants were diagnosed with predominantly chronic (mean, 1381 days; median, 888 days after injury) and mild (92% [768 of 834]) TBI. Of these participants, 84.2% (688 of 817) reported one or more blast-related incident and 63.0% (515 of 817) reported loss of consciousness at the time of injury. The presence of white matter T2-weighted hyperintense areas was the most common pathologic finding, observed in 51.8% (432 of 834; OR, 1.75) of TBI participants. Cerebral microhemorrhages were observed in a small percentage of participants (7.2% [60 of 834]; OR, 6.64) and showed increased incidence with TBI severity (P.001, moderate and severe vs mild). T2-weighted hyperintense areas and microhemorrhages did not collocate by visual inspection. Pituitary abnormalities were identified in a large proportion (29.0% [242 of 834]; OR, 16.8) of TBI participants.Blast-related injury and loss of consciousness is common in military TBI. Structural MR imaging demonstrates a high incidence of white matter T2-weighted hyperintense areas and pituitary abnormalities, with a low incidence of microhemorrhage in the chronic phase.

Resumen Fundamento La resonancia magnetica (RM) mediante tensor de difusion permite el estudio de la integridad de los tractos de sustancia blanca (SB). Los estudios publicados sugieren que en el trastorno bipolar podria estar alterada su integridad. La heterogeneidad de los metodos de diagnostico por imagen cerebral, de las muestras estudiadas y de los tratamientos farmacologicos no contribuye a dilucidar la localizacion, la naturaleza y la gravedad de las anomalias de la SB. Metodos Aplicamos el programa informatico FSL con la herramienta tract-based spatial statistics (TASS) a los parametros de RM mediante tensor de difusion para comparar la anisotropia fraccional (AF) y la difusividad media y radial de la estructura de SB en un grupo de 40 pacientes ingresados consecutivamente, afectados por un episodio depresivo mayor, sin caracteristicas psicoticas, con un diagnostico de trastorno bipolar de tipo I, y 21 individuos voluntarios, sanos, no emparentados, de la poblacion general. Resultados Comparado con los individuos de control, en los pacientes se identifico una menor AF en la rodilla del cuerpo calloso y en la parte anterior y supraposterior derecha de la corona radiada y mayores valores de difusividad radial en los tractos de SB del esplenio, rodilla y cuerpo del cuerpo calloso, parte mediodorsal derecha del haz del cingulo, parte anterior izquierda y superior y posterior bilateral de la corona radiada, fasciculo longitudinal superior bilateral y radiacion talamica posterior derecha. En los pacientes no se detectaron areas cerebrales con mayores valores de AF o menores valores de difusividad que en los individuos de control. Conclusiones La disminucion de la AF con un aumento de la difusividad media y radial sugiere una desmielinizacion y/o dismielinizacion significativa sin una perdida axonica. Comparando nuestros hallazgos con otras observaciones de muestras homogeneas de pacientes eutimicos y maniacos, se puede formular la hipotesis de que los cambios en los parametros de la integridad de la SB podrian ser comparables a las fases de la enfermedad en el trastorno bipolar.

Background: Diffusion tensor imaging allows the study of integrity of white matter (WM) tracts. Literature suggests that WM integrity could be altered in bipolar disorder. Heterogeneity of brain imaging methods, the studied samples, and drug treatments make localization, nature, and severity of the WM abnormalities unclear. Methods: We applied tract-based spatial statistics of diffusion tensor imaging measures to compare fractional anisotropy (FA), mean, and radial diffusivity of the WM skeleton in a group of 40 consecutively admitted inpatients affected by a major depressive episode without psychotic features with a diagnosis of bipolar disorder type I and 21 unrelated healthy volunteers from the general population. Results: Compared with control subjects, patients showed lower FA in the genu of the corpus callosum and in anterior and right superior-posterior corona radiata and higher values of radial diffusivity in WM tracts of splenium, genu and body of corpus callosum, right mid-dorsal part of the cingulum bundle, left anterior and bilateral superior and posterior corona radiata, bilateral superior longitudinal fasciculus, and right posterior thalamic radiation. Patients had no brain areas with higher FA or lower diffusivity values than control subjects. Conclusions: Reduced FA with increased mean and radial diffusivity suggests significant demyelination and/or dysmyelination without axonal loss. Comparing our findings with other observations in homogeneous samples of euthymic and manic patients, it can be hypothesized that changes in measures of WM integrity might parallel illness phases of bipolar illness. ""Background: Diffusion tensor imaging allows the study of integrity of white matter (WM) tracts. Literature suggests that WM integrity could be altered in bipolar disorder. Heterogeneity of brain imaging methods, the studied samples, and drug treatments make localization, nature, and severity of the WM abnormalities unclear. Methods: We applied tract-based spatial statistics of diffusion tensor imaging measures to compare fractional anisotropy (FA), mean, and radial diffusivity of the WM skeleton in a group of 40 consecutively admitted inpatients affected by a major depressive episode without psychotic features with a diagnosis of bipolar disorder type I and 21 unrelated healthy volunteers from the general population. Results: Compared with control subjects, patients showed lower FA in the genu of the corpus callosum and in anterior and right superior-posterior corona radiata and higher values of radial diffusivity in WM tracts of splenium, genu and body of corpus callosum, right mid-dorsal part of the cingulum bundle, left anterior and bilateral superior and posterior corona radiata, bilateral superior longitudinal fasciculus, and right posterior thalamic radiation. Patients had no brain areas with higher FA or lower diffusivity values than control subjects. Conclusions: Reduced FA with increased mean and radial diffusivity suggests significant demyelination and\\\/or dysmyelination without axonal loss. Comparing our findings with other observations in homogeneous samples of euthymic and manic patients, it can be hypothesized that changes in measures of WM integrity might parallel illness phases of bipolar illness.""

Most previous neuroimaging studies of alcohol-induced brain injury and recovery thereof during abstinence from alcohol used a single imaging modality. They have demonstrated widespread microstructural, macrostructural or metabolite abnormalities that were partially reversible with abstinence, with the cigarette smoking potentially modulating these processes. The goals of this study were to evaluate white matter injury and recovery thereof, simultaneously with diffusion tensor imaging, magnetic resonance imaging and spectroscopy in the same cohort; and to evaluate the relationships between outcome measures of similar regions. We scanned 16 non-smoking and 20 smoking alcohol-dependent individuals at 1 week of abstinence from alcohol and 22 non-smoking light drinkers using a 1.5 T magnetic resonance scanner. Ten non-smoking alcohol-dependent individuals and 11 smoking alcohol-dependent individuals were re-scanned at 1 month of abstinence. All regional diffusion tensor imaging, magnetic resonance imaging and spectroscopic outcome measures were calculated over comparable volumes of frontal, temporal, parietal and occipital white matter. At 1 week of abstinence and relative to non-smoking light drinkers, non-smoking alcohol-dependent individuals had higher mean diffusivity in frontal, temporal and parietal white matter (all P < 0.008), whereas smoking alcohol-dependent individuals had elevated mean diffusivity only in frontal white matter (P = 0.03). Smoking alcohol-dependent individuals demonstrated lower concentrations of N-acetyl-aspartate (a marker of neuronal viability) in frontal white matter (P = 0.03), whereas non-smoking alcohol-dependent individuals had lower N-acetyl-aspartate in parietal white matter (P = 0.05). These abnormalities were not accompanied by detectable white matter atrophy. However, the patterns of white matter recovery were different between non-smoking alcohol-dependent individuals and smoking alcohol-dependent individuals. In non-smoking alcohol-dependent individuals, the increase in fractional anisotropy of temporal white matter (P = 0.003) was accompanied by a pattern of decreases mean diffusivity in all regions over 1 month of abstinence; no corresponding changes were observed in smoking alcohol-dependent individuals. In contrast, a pattern of white matter volume increase in frontal and temporal lobes was apparent in smoking alcohol-dependent individuals but not in non-smoking alcohol-dependent individuals. These results were not accompanied by significant changes in metabolite concentrations. Finally, there were no consistent patterns of association between measures obtained with different imaging modalities, either cross-sectionally or longitudinally. These data demonstrate significant white matter improvements with abstinence from alcohol, reflected either as microstructural recovery or volumetric increases that depend on the smoking status of the participants. We believe our results to be important, as they demonstrate that use of a single imaging modality provides an incomplete picture of neurobiological processes associated with alcohol-induced brain injury and recovery thereof that may even lead to improper interpretation of results.

Previous diffusion tensor imaging (DTI) studies indicated microstructural disruption of white matter in alcohol dependence. To investigate the microstructure of primary neurocircuitry involved in alcohol use disorders, the present study used Tract-Based Spatial Statistics (TBSS) of DTI measures as well as probabilistic tractography. Eleven recovering alcoholics in their first week of abstinence from alcohol were compared with ten light drinking controls; diffusion measures were correlated with measures of neurocognition and drinking severity. Regions characterized by low fractional anisotropy and high mean diffusivity included cortico-striatal fibers and those in frontal white matter and limbic pathways. Greater diffusion abnormalities in sections of commissural fibers (inter-hemispheric connections) were associated with stronger drinking severity, and lower fractional anisotropy measures in frontal and limbic fiber tracts correlated with lower visuospatial memory performance. These study findings provide direct evidence of compromised integrity of the motivational brain circuitry in alcohol use disorders. These abnormalities in fiber connections could be partially responsible for deficiencies in executive functions, behavioral regulation, and impulse control commonly described in alcohol dependence.

There is evidence that intra- and inter-hemispheric white matter communication, mainly fronto-limbic and callosal connectivity, is impaired in bipolar disorder as reported in several magnetic resonance (MR) diffusion imaging studies. In this review we will discuss diffusion imaging studies that examined white matter integrity in patients with bipolar disorder, trying to outline future research strategies.

The purpose of this work is to develop a framework for single-subject analysis of diffusion tensor imaging (DTI) data. This framework (termed TOADDI) is capable of testing whether an individual tract as represented by the major eigenvector of the diffusion tensor and its corresponding angular dispersion are significantly different from a group of tracts on a voxel-by-voxel basis. This work develops two complementary statistical tests based on the elliptical cone of uncertainty (COU), which is a model of uncertainty or dispersion of the major eigenvector of the diffusion tensor. The orientation deviation test examines whether the major eigenvector from a single subject is within the average elliptical COU formed by a collection of elliptical COUs. The shape deviation test is based on the two-tailed Wilcoxon-Mann-Whitney two-sample test between the normalized shape measures (area and circumference) of the elliptical cones of uncertainty of the single subject against a group of controls. The False Discovery Rate (FDR) and False Non-discovery Rate (FNR) were incorporated in the orientation deviation test. The shape deviation test uses FDR only. TOADDI was found to be numerically accurate and statistically effective. Clinical data from two Traumatic Brain Injury (TBI) patients and one non-TBI subject were tested against the data obtained from a group of 45 non-TBI controls to illustrate the application of the proposed framework in single-subject analysis. The frontal portion of the superior longitudinal fasciculus seemed to be implicated in both tests as significantly different from that of the control group. The TBI patients and the single non-TBI subject were well separated under the shape deviation test at the chosen FDR level of 0.0005. TOADDI is a simple but novel geometrically based statistical framework for analyzing DTI data., Comment: 49 pages, 6 figures, 2 tables

A definitive diagnosis of mild traumatic brain injury (mTBI) is difficult due to the absence of biomarkers in standard clinical imaging. The brain is a complex network of interconnected neurons and subtle changes can modulate key networks of cognitive function. The resting state default mode network (DMN) has been shown to be sensitive to changes induced by pathology. This study seeks to determine whether quantitative measures of the DMN are sensitive in distinguishing mTBI subjects. Resting state functional magnetic resonance imaging data were obtained for healthy (n=12) and mTBI subjects (n=15). DMN maps were computed using dual-regression Independent Component Analysis (ICA). A goodness-of-fit (GOF) index was calculated to assess the degree of spatial specificity and sensitivity between healthy controls and mTBI subjects. DMN regions and neuropsychological assessments were examined to identify potential relationships. The resting state DMN maps indicate an increase in spatial coactivity in mTBI subjects within key regions of the DMN. Significant coactivity within the cerebellum and supplementary motor areas of mTBI subjects were also observed. This has not been previously reported in seed-based resting state network analysis. The GOF suggested the presence of high variability within the mTBI subject group, with poor sensitivity and specificity. The neuropsychological data showed correlations between areas of coactivity within the resting state network in the brain with a number of measures of emotion and cognitive functioning. The poor performance of the GOF highlights the key challenge associated with mTBI injury: the high variability in injury mechanisms and subsequent recovery. However, the quantification of the DMN using dual-regression ICA has potential to distinguish mTBI from healthy subjects, and provide information on the relationship of aspects of cognitive and emotional functioning with their potential neural correlates.

Although the pathogenesis of bipolar disorder is still not completely understood, there is evidence from imaging studies that abnormalities in inter-hemispheric communication may play a major role in the pathophysiology of bipolar disorder. In the present review, we discuss the most consistent findings from diffusion imaging studies exploring corpus callosum integrity in bipolar disorder.

Traumatic brain injury (TBI) is a common combat injury, often through explosive blast, and produces heterogeneous brain changes due to various mechanisms of injury. It is unclear whether the vulnerability of white matter differs between blast and impact injury, and the consequences of microstructural changes on neuropsychological function are poorly understood in military TBI patients. Diffusion tensor imaging (DTI) techniques were used to assess the neurocircuitry in 37 US service members (29 mild, 7 moderate, 1 severe; 17 blast and 20 nonblast), who sustained a TBI while deployed, compared to 14 nondeployed, military controls. High‐dimensional deformable registration of MRI diffusion tensor data was followed by fiber tracking and tract‐specific analysis along with region‐of‐interest analysis. DTI results were examined in relation to post‐concussion and post‐traumatic stress disorder (PTSD) symptoms. The most prominent white matter microstructural injury for both blast and nonblast patients was in the frontal fibers within the fronto‐striatal (corona radiata, internal capsule) and fronto‐limbic circuits (fornix, cingulum), the fronto‐parieto‐occipital association fibers, in brainstem fibers, and in callosal fibers. Subcortical superior‐inferiorly oriented tracts were more vulnerable to blast injury than nonblast injury, while direct impact force had more detrimental effects on anterior‐posteriorly oriented tracts, which tended to cause heterogeneous left and right hemispheric asymmetries of white matter connectivity. The tractography using diffusion anisotropy deficits revealed the cortico‐striatal‐thalamic‐cerebellar‐cortical (CSTCC) networks, where increased post‐concussion and PTSD symptoms were associated with low fractional anisotropy in the major nodes of compromised CSTCC neurocircuitry, and the consequences on cognitive function were explored as well. Hum Brain Mapp 35:2652–2673, 2014. © 2013 Wiley Periodicals, Inc.

Recent brain imaging studies have shed light on understanding the pathogenesis of mood disorders. Evidence of structural, chemical, and functional brain changes, particularly in prefrontal cortex, cingulate, and amygdala, has been revealed in major depressive disorder (MDD). Furthermore, imaging techniques have been applied to monitor the effects of antidepressants (ADs) both in the brains of healthy volunteers and MDD patients. Although with some discrepancies due to the differences in study designs and patient samples, imaging findings have shown that ADs, particularly those having effects on the serotonergic system, modulate the volumes, functions and biochemistry of brain structures, i.e. dorsolateral prefrontal cortex, anterior cingulate and amygdala, which have been demonstrated abnormal in MDD by earlier imaging studies. This paper reviews imaging studies conducted in MDD patients and healthy controls treated with different ADs.

Abnormalities of the cortico-striatal-thalamic-cortical (CSTC) and the limbic-cortico-striatal-thalamic-cortical (LCSTC) circuits have been hypothesized in mood disorders. We performed principal component analysis (PCA) to identify latent volumetric systems on regional brain volumes and correlated these patterns with clinical characteristics; further, we performed exploratory structural equation modeling (SEM) to test a priori hypotheses about the organization among the structures comprising the CSTC and LCSTC circuits, and to investigate differences among subjects with bipolar disorder (BD), major depressive disorder (MDD), and healthy controls (HC). Participants included 45 BD and 31 MDD patients, and 72 HC. Regional MR brain volumes were used to calculate patterns of volumetric covariance. The identified latent volumetric systems were related to the depression severity and the duration of illness. BD differed from HC on the estimated parameters describing the paths of cortico-striatal, thalamo-striatal and intrastriatal loops of the CSTC circuit, and the paths between anterior and posterior cingulate cortex (PCC), and hippocampus to amygdala of the LCSTC circuit. MDD differed from HC on the paths between putamen and thalamus, and PCC to hippocampus. This study provides evidence to suggest different organizational patterns among structures within the CSTC and LCSTC circuits for BD, MDD, and HC, which may point to structural abnormalities underlying mood disorders.

In this review, we debate the evidence for abnormal white matter microstructure and myelination in bipolar disorder, as mainly detected by diffusion tensor imaging (DTI) studies. The effects of mood stabilizers on white matter are discussed, based on available findings from human and animal studies. Last, perspectives in this field of research are also drawn.

The dorsolateral prefrontal cortex (DLPFC) has been implicated in the pathophysiology of mental disorders. Previous region-of-interest MRI studies that attempted to delineate this region adopted various landmarks and measurement techniques, with inconsistent results. We developed a new region-of-interest measurement method to obtain morphometric data of this region from structural MRI scans, taking into account knowledge from cytoarchitectonic postmortem studies and the large inter-individual variability of this region. MRI scans of 10 subjects were obtained, and DLPFC tracing was performed in the coronal plane by two independent raters using the semi-automated software Brains2. The intra-class correlation coefficients between two independent raters were 0.94 for the left DLPFC and 0.93 for the right DLPFC. The mean +/- S.D. DLPFC volumes were 9.23 +/- 2.35 ml for the left hemisphere and 8.20 +/- 2.08 ml for the right hemisphere. Our proposed method has high inter-rater reliability and is easy to implement, permitting the standardized measurement of this region for clinical research applications

Memory function is largely mediated by the medial temporal lobe (MTL), and its compromise has been observed in alcohol dependence and chronic cigarette smoking. The effects of heavy alcohol consumption and chronic smoking on hippocampal volumes and MTL metabolites and their recovery during abstinence from alcohol have not been assessed. Male alcoholics in treatment (ALC) [13 smokers (sALC) and 11 non-smokers (nsALC)] underwent quantitative magnetic resonance imaging and short-echo proton magnetic resonance spectroscopic imaging at 1 week and 1 month of sobriety. Outcome measures were compared with 14 age-matched, non-smoking light-drinkers and were related to visuospatial learning and memory. Over 1 month of abstinence, N-acetyl-aspartate, a neuronal marker, and membrane-associated choline-containing metabolites normalized in the MTL of nsALC subjects, but remained low in the MTL of sALC subjects. Metabolite concentration changes in both groups were associated with improvements in visuospatial memory. Hippocampal volumes increased in both groups during abstinence, but increasing volumes correlated with visuospatial memory improvements only in nsALC subjects. In summary, chronic cigarette smoking in alcohol-dependent men appears to have adverse effects on MTL metabolite recovery during short-term sobriety. These data may also have implications for other conditions with established MTL involvement and significant smoking co-morbidity, such as schizophrenia-spectrum and mood disorders.

Aims: Resumption of hazardous drinking after treatment is common in alcohol use disorders (AUD). This study examined the ability of multimodality magnetic resonance, neurocognitive, psychiatric and demographic, to predict alcohol consumption after treatment for AUD. Methods: Seventy treatment-seeking participants completed 1.5T magnetic resonance studies, yielding regional gray matter (GM) and white matter (WM) surrogate markers of neuronal integrity ( N -acetylaspartate: NAA) and cell membrane turnover/synthesis (choline: Cho), assessment of major psychiatric disorders and comprehensive neurocognitive assessment after ∼1 month of abstinence. Participants were followed up 6–12 months after treatment and classified as Abstainers (no alcohol consumption; n = 26) and Resumers (any alcohol consumption; n = 44). Abstainers and Resumers were contrasted on various outcome measures, and those that significantly differed between groups were entered as factors in a logistical regression model to predict drinking status at follow-up. Results: The following variables were independent predictors of resumption of drinking: temporal GM NAA, frontal WM NAA, frontal GM Cho, processing speed and comorbid unipolar mood disorder. With each standard deviation unit decrease in temporal GM NAA, frontal WM NAA, frontal GM Cho and processing speed, the odds of resumption of drinking were increased 3.1, 3.3, 6.4 and 14.2 times, respectively. Diagnosis of a unipolar mood disorder was associated with 14.5-fold increased odds of resumed drinking. Conclusions: The findings suggest that Resumers, relative to Abstainers, demonstrated greater abnormalities in anterior frontal-subcortical circuits involved in mood and behavioral regulation, and development and maintenance of alcohol use disorders, The magnetic resonance-derived variables used in this study may provide additional information regarding the prediction and neurobiological correlates of resumption of hazardous drinking.

Background Hierarchical linear modeling (HLM) can reveal complex relationships between longitudinal outcome measures and their covariates under proper consideration of potentially unequal error variances. We demonstrate the application of HLM to the study of magnetic resonance imaging (MRI)-derived brain volume changes and cognitive changes in abstinent alcohol-dependent individuals as a function of smoking status, smoking severity, and drinking quantities. Methods Twenty non-smoking recovering alcoholics (nsALC) and 30 age-matched smoking recovering alcoholics (sALC) underwent quantitative MRI and cognitive assessments at 1 week, 1 month, and 7 months of sobriety. Eight non-smoking light drinking controls were studied at baseline and 7 months later. Brain and ventricle volumes at each time point were quantified using MRI masks, while the boundary shift integral method measured volume changes between time points. Using HLM, we modeled volumetric and cognitive outcome measures as a function of cigarette and alcohol use variables. Results Different hierarchical linear models with unique model structures are presented and discussed. The results show that smaller brain volumes at baseline predict faster brain volume gains, which were also related to greater smoking and drinking severities. Over 7 months of abstinence from alcohol, sALC compared to nsALC showed less improvements in visuospatial learning and memory despite larger brain volume gains and ventricular shrinkage. Conclusions Different and unique hierarchical linear models allow assessments of the complex relationships among outcome measures of longitudinal data sets. These HLM applications suggest that chronic cigarette smoking modulates the temporal dynamics of brain structural and cognitive changes in alcoholics during prolonged sobriety.

Available online 22 August 2021. White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process. This work was conducted in part using the resources of the Ad- vanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. KS, BL, CH were supported by the Na- tional Institutes of Health under award numbers R01EB017230, and T32EB001628, and in part by ViSE/VICTR VR3029 and the National Center for Research Resources, Grant UL1 RR024975-01. This work was also possible thanks to the support of the Institutional Research Chair in NeuroInformatics of Universitéde Sherbrooke, NSERC and Compute Canada (MD, FR). MP received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sk ł odowska-Curie grant agreement No 754462. The Wisconsin group acknowledges the support from a core grant to the Waisman Cen- ter from the National Institute of Child Health and Human Develop- ment (IDDRC U54 HD090256). NSF OAC-1916518, NSF IIS-1912270, NSF IIS-1636893, NSF BCS-1734853, NIH NIBIB 1R01EB029272-01, and a Microsoft Faculty Fellowship to F.P. LF acknowledges the sup- port of the Cluster of Excellence Matters of Activity. Image Space Mate- rial funded by the Deutsche Forschungsgemeinschaft (DFG, German Re- search Foundation) under Germany´s Excellence Strategy –EXC 2025. SW is supported by a Medical Research Council PhD Studentship UK [MR/N013913/1]. The Nottingham group’s processing was performed using the University of Nottingham’s Augusta HPC service and the Pre- cision Imaging Beacon Cluster. JPA, MA and SMS acknowledges the support of FCT - Fundação para a Ciência e a Tecnologia within CIN- TESIS, R&D Unit (reference UID/IC/4255/2013). MM was funded by the Wellcome Trust through a Sir Henry Wellcome Postdoctoral Fellow- ship [213722/Z/18/Z]. EJC-R is supported by the Swiss National Sci- ence Foundation (SNSF, Ambizione grant PZ00P2 185814/1). CMWT is supported by a Sir Henry Wellcome Fellowship (215944/Z/19/Z) and a Veni grant from the Dutch Research Council (NWO) (17331). FC acknowledges the support of the National Health and Medical Re- search Council of Australia (APP1091593 and APP1117724) and the Australian Research Council (DP170101815). NSF OAC-1916518, NSF IIS-1912270, NSF IIS-1636893, NSF BCS-1734853, Microsoft Faculty Fellowship to F.P. D.B. was partially supported by NIH NIMH T32- MH103213 to William Hetrick (Indiana University). CL is partly sup- ported by NIH grants P41 EB027061 and P30 NS076408 “Institutional Center Cores for Advanced Neuroimaging. JYMY received positional funding from the Royal Children’s Hospital Foundation (RCH 1000). JYMY, JC, and CEK acknowledge the support of the Royal Children’s Hospital Foundation, Murdoch Children’s Research Institute, The Uni- versity of Melbourne Department of Paediatrics, and the Victorian Gov- ernment’s Operational Infrastructure Support Program. C-HY is grateful to the Ministry of Science and Technology of Taiwan (MOST 109-2222- E-182-001-MY3) for the support. LC acknowledges support from CONA- CYT and UNAM. ARM acknowledges support from CONACYT. LJO, YR, and FZ were supported by NIH P41EB015902 and R01MH119222. AJG was supported by P41EB015898. NM was supported by R01MH119222, K24MH116366, and R01MH111917. This project has received funding from the European Union’s Horizon 2020 Research and Innovation Pro- gramme under Grant Agreement No. 785907 & 945539 (HBP SGA2 & SGA3), and from the ANR IFOPASUBA- 19-CE45-0022-01. PG, CR, NL and AV were partially supported by ANID-Basal FB0008 and ANID- FONDECYT 1190701 grants. We would like to acknowledge John C Gore, Hiromasa Takemura, Anastasia Yendiki, and Riccardo Galbusera for their helplful suggestions regarding the analysis, figures, and discussions.