Project description:OBJECTIVE:To examine metacognitive ability (MC) following moderate to severe traumatic brain injury (TBI) using an empirical assessment approach and to determine the relationship between alterations in gray matter volume (GMV) and MC. METHOD:A sample of 62 individuals (TBI n = 34; healthy control [HC] n = 28) were included in the study. Neuroimaging and neuropsychological data were collected for all participants during the same visit. MC was quantified using an approach borrowed from signal detection theory (Type II area under the receiver operating characteristic curve calculation) to evaluate judgments during a modified version of the 3rd edition of the Wechsler Adult Intelligence Scale's Matrix Reasoning subtest where half of the items were presented randomly and half were presented in the order of increasing difficulty. Retrospective confidence judgments were collected on an item-by-item basis. Brain volumetric analyses were conducted using FreeSurfer software. RESULTS:Analyses of the modified Matrix Reasoning task data demonstrated that HCs significantly outperformed TBIs (ordered: d = .63; random: d = .58). There was a significant difference between groups for MC for the randomly presented stimuli (d = .54) but not the ordered stimuli. There was an association between GMV and MC in the TBI group between the right orbital region and MC (R2 = .11). In the HC group, there were associations between the left posterior (R2 = .17), left orbital (R2 = .29), and left dorsolateral (R2 = .21) regions and MC. CONCLUSIONS:These results are consistent with those of previous research on MC in the cognitive neurosciences, but this study demonstrates that injury may moderate the regional contributions to MC. (PsycINFO Database Record
Project description:To examine the underlying pathophysiology of mild traumatic brain injury through changes in gray matter diffusion and atrophy during the semiacute stage.Fifty patients and 50 sex-, age-, and education-matched controls were evaluated with a clinical and neuroimaging battery approximately 14 days postinjury, with 26 patients returning for follow-up 4 months postinjury. Clinical measures included tests of attention, processing speed, executive function, working memory, memory, and self-reported postconcussive symptoms. Measures of diffusion (fractional anisotropy [FA], mean diffusivity) and atrophy were obtained for cortical and subcortical structures to characterize effects of injury as a function of time.Patients reported more cognitive, somatic, and emotional complaints during the semiacute injury phase, which were significantly reduced 4 months postinjury. Patients showed evidence of increased FA in the bilateral superior frontal cortex during the semiacute phase, with the left superior frontal cortex remaining elevated 4 months postinjury. There were no significant differences between patients and matched controls on neuropsychological testing or measures of gray matter atrophy/mean diffusivity at either time point.Increased cortical FA is largely consistent with an emerging animal literature of gray matter abnormalities after neuronal injury. Potential mechanistic explanations for increased FA include cytotoxic edema or reactive gliosis. In contrast, there was no evidence of cortical or subcortical atrophy in the current study, suggesting that frank neuronal or neuropil loss does not occur early in the chronic disease course for patients with typical mild traumatic brain injury.
Project description:ObjectiveWe investigated the association between regional white and gray matter volume loss and performance on executive functions (EFs) in patients with penetrating traumatic brain injury (pTBI).MethodsWe studied 164 pTBI patients and 43 healthy controls from the Vietnam Head Injury Study. We acquired CT scans for pTBI patients and divided them according to lesion localization (left and right prefrontal cortex [PFC]). We administered EF tests (Verbal Fluency, Trail Making, Twenty Questions) and used voxel-based lesion symptom mapping (VLSM) and group-based correlational and multiple regression analyses to examine the relative influence of gray and white matter lesions on EF recovery.ResultsThe VLSM analysis revealed that white and gray white matter lesions were associated with impaired EFs. In the left PFC lesion group, damage to the PFC gray matter, anterior corona radiata, and superior longitudinal fasciculus (SLF) were most correlated with functional recovery. Verbal Fluency, which involves a broad fronto-temporo-parietal network, was best predicted by SLF lesion volume. Trail Making and Twenty Questions, which is associated with more focal left frontal damage, was better predicted by PFC lesions.ConclusionsOur results indicated that white matter volume loss can be a superior predictor of recovery and a crucial factor driving clinical outcome in functions involving a broad network such as Verbal Fluency. White matter damage may place additional burden on recovery by deteriorating signal transmission between cortical areas within a functional network.
Project description:This study evaluates the correlation between injuries to deep gray matter nuclei, as quantitated by lesions in these nuclei on MR T2 Fast Spin Echo (T2 FSE) images, with 6-month neurological outcome after severe traumatic brain injury (TBI).Ninety-five patients (80 males, mean age = 36.7y) with severe TBI were prospectively enrolled. All patients underwent a MR scan within the 45 days after the trauma that included a T2 FSE acquisition. A 3D deformable atlas of the deep gray matter was registered to this sequence; deep gray matter lesions (DGML) were evaluated using a semi-quantitative classification scheme. The 6-month outcome was dichotomized into unfavorable (death, vegetative or minimally conscious state) or favorable (minimal or no neurologic deficit) outcome.Sixty-six percent of the patients (63/95) had both satisfactory registration of the 3D atlas on T2 FSE and available clinical follow-up. Patients without DGML had an 89% chance (P = 0.0016) of favorable outcome while those with bilateral DGML had an 80% risk of unfavorable outcome (P = 0.00008). Multivariate analysis based on DGML accurately classified patients with unfavorable neurological outcome in 90.5% of the cases.Lesions in deep gray matter nuclei may predict long-term outcome after severe TBI with high sensitivity and specificity.
Project description:Traumatic brain injury (TBI) is a leading cause of death and long-term disability in the United States. The heterogeneity of the disease coupled with the lack of comprehensive, standardized scales to adequately characterize multiple types of TBI remain to be major challenges facing effective therapeutic development. A systems level approach to TBI diagnosis through the use of metabolomics could lead to a better understanding of cellular changes post-TBI and potential therapeutic targets. In the current study, we utilize a GC-MS untargeted metabolomics approach to demonstrate altered metabolism in response to TBI in a translational pig model, which possesses many neuroanatomical and pathophysiologic similarities to humans. TBI was produced by controlled cortical impact (CCI) in Landrace piglets with impact velocity and depth of depression set to 2m/s;6mm, 4m/s;6mm, 4m/s;12mm, or 4m/s;15mm resulting in graded neural injury. Serum samples were collected pre-TBI, 24 hours post-TBI, and 7 days post-TBI. Partial least squares discriminant analysis (PLS-DA) revealed that each impact parameter uniquely influenced the metabolomic profile after TBI, and gray and white matter responds differently to TBI on the biochemical level with evidence of white matter displaying greater metabolic change. Furthermore, pathway analysis revealed unique metabolic signatures that were dependent on injury severity and brain tissue type. Metabolomic signatures were also detected in serum samples which potentially captures both time after injury and injury severity. These findings provide a platform for the development of a more accurate TBI classification scale based unique metabolomic signatures.
Project description:New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.
Project description:There is increasing recognition that traumatic brain injury (TBI) may initiate long-term neurodegenerative processes, particularly chronic traumatic encephalopathy. However, insight into the mechanisms transforming an initial biomechanical injury into a neurodegenerative process remain elusive, partly as a consequence of the paucity of informative pre-clinical models. This study shows the functional, whole brain imaging and neuropathological consequences at up to one year survival from single severe TBI by controlled cortical impact in mice. TBI mice displayed persistent sensorimotor and cognitive deficits. Longitudinal T2 weighted magnetic resonance imaging (MRI) showed progressive ipsilateral (il) cortical, hippocampal and striatal volume loss, with diffusion tensor imaging demonstrating decreased fractional anisotropy (FA) at up to one year in the il-corpus callosum (CC: -30%) and external capsule (EC: -21%). Parallel neuropathological studies indicated reduction in neuronal density, with evidence of microgliosis and astrogliosis in the il-cortex, with further evidence of microgliosis and astrogliosis in the il-thalamus. One year after TBI there was also a decrease in FA in the contralateral (cl) CC (-17%) and EC (-13%), corresponding to histopathological evidence of white matter loss (cl-CC: -68%; cl-EC: -30%) associated with ongoing microgliosis and astrogliosis. These findings indicate that a single severe TBI induces bilateral, long-term and progressive neuropathology at up to one year after injury. These observations support this model as a suitable platform for exploring the mechanistic link between acute brain injury and late and persistent neurodegeneration.
Project description:Pharmacotherapy for traumatic brain injury (TBI) is focused on resuscitation, prevention of secondary injury, rehabilitation and recovery. Pharmacogenomics may play a role in TBI for predicting therapies for sedation, analgesia, seizure prevention, intracranial pressure-directed therapy and neurobehavioral/psychiatric symptoms. Research into genetic predictors of outcomes and susceptibility to complications may also help clinicians to tailor therapeutics for high-risk individuals. Additionally, the expanding use of genomics in the drug development pipeline has provided insight to novel investigational and repurposed medications that may be useful in the treatment of TBI and its complications. Genomics in the context of treatment and prognostication for patients with TBI is a promising area for clinical progress of pharmacogenomics.
Project description:Severe traumatic brain injury (sTBI) is a major contributor to long-term disability and a leading cause of death worldwide. Medical management of the sTBI patient, beginning with prehospital triage, is aimed at preventing secondary brain injury. This review discusses prehospital and emergency department management of sTBI, as well as aspects of TBI management in the intensive care unit where advances have been made in the past decade. Areas of emphasis include intracranial pressure management, neuromonitoring, management of paroxysmal sympathetic hyperactivity, neuroprotective strategies, prognostication, and communication with families about goals of care. Where appropriate, differences between the third and fourth editions of the Brain Trauma Foundation guidelines for the management of severe traumatic brain injury are highlighted.