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Detecting axonal injury in individual patients after traumatic brain injury.

ABSTRACT: Poor outcomes after traumatic brain injury (TBI) are common yet remain difficult to predict. Diffuse axonal injury is important for outcomes, but its assessment remains limited in the clinical setting. Currently, axonal injury is diagnosed based on clinical presentation, visible damage to the white matter or via surrogate markers of axonal injury such as microbleeds. These do not accurately quantify axonal injury leading to misdiagnosis in a proportion of patients. Diffusion tensor imaging provides a quantitative measure of axonal injury in vivo, with fractional anisotropy often used as a proxy for white matter damage. Diffusion imaging has been widely used in TBI but is not routinely applied clinically. This is in part because robust analysis methods to diagnose axonal injury at the individual level have not yet been developed. Here, we present a pipeline for diffusion imaging analysis designed to accurately assess the presence of axonal injury in large white matter tracts in individuals. Average fractional anisotropy is calculated from tracts selected on the basis of high test-retest reliability, good anatomical coverage and their association to cognitive and clinical impairments after TBI. We test our pipeline for common methodological issues such as the impact of varying control sample sizes, focal lesions and age-related changes to demonstrate high specificity, sensitivity and test-retest reliability. We assess 92 patients with moderate-severe TBI in the chronic phase (?6 months post-injury), 25 patients in the subacute phase (10 days to 6 weeks post-injury) with 6-month follow-up and a large control cohort (n?=?103). Evidence of axonal injury is identified in 52% of chronic and 28% of subacute patients. Those classified with axonal injury had significantly poorer cognitive and functional outcomes than those without, a difference not seen for focal lesions or microbleeds. Almost a third of patients with unremarkable standard MRIs had evidence of axonal injury, whilst 40% of patients with visible microbleeds had no diffusion evidence of axonal injury. More diffusion abnormality was seen with greater time since injury, across individuals at various chronic injury times and within individuals between subacute and 6-month scans. We provide evidence that this pipeline can be used to diagnose axonal injury in individual patients at subacute and chronic time points, and that diffusion MRI provides a sensitive and complementary measure when compared to susceptibility weighted imaging, which measures diffuse vascular injury. Guidelines for the implementation of this pipeline in a clinical setting are discussed.

SUBMITTER: Jolly AE

PROVIDER: S-EPMC7880666 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Detecting axonal injury in individual patients after traumatic brain injury.

Jolly Amy E AE Bălăeţ Maria M Azor Adriana A Friedland Daniel D Sandrone Stefano S Graham Neil S N NSN Zimmerman Karl K Sharp David J DJ

Brain : a journal of neurology 20210201 1

Poor outcomes after traumatic brain injury (TBI) are common yet remain difficult to predict. Diffuse axonal injury is important for outcomes, but its assessment remains limited in the clinical setting. Currently, axonal injury is diagnosed based on clinical presentation, visible damage to the white matter or via surrogate markers of axonal injury such as microbleeds. These do not accurately quantify axonal injury leading to misdiagnosis in a proportion of patients. Diffusion tensor imaging provi ...[more]

PMID: 33257929

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Project description:Diffuse axonal injury (DAI) is a common feature of severe traumatic brain injury (TBI) and may also be a predominant pathology in mild TBI or "concussion". The rapid deformation of white matter at the instant of trauma can lead to mechanical failure and calcium-dependent proteolysis of the axonal cytoskeleton in association with axonal transport interruption. Recently, a proteolytic fragment of alpha-II spectrin, "SNTF", was detected in serum acutely following mild TBI in patients and was prognostic for poor clinical outcome. However, direct evidence that this fragment is a marker of DAI has yet to be demonstrated in either humans following TBI or in models of mild TBI. Here, we used immunohistochemistry (IHC) to examine for SNTF in brain tissue following both severe and mild TBI. Human severe TBI cases (survival <7d; n = 18) were compared to age-matched controls (n = 16) from the Glasgow TBI archive. We also examined brains from an established model of mild TBI at 6, 48 and 72 h post-injury versus shams. IHC specific for SNTF was compared to that of amyloid precursor protein (APP), the current standard for DAI diagnosis, and other known markers of axonal pathology including non-phosphorylated neurofilament-H (SMI-32), neurofilament-68 (NF-68) and compacted neurofilament-medium (RMO-14) using double and triple immunofluorescent labeling. Supporting its use as a biomarker of DAI, SNTF immunoreactive axons were observed at all time points following both human severe TBI and in the model of mild TBI. Interestingly, SNTF revealed a subpopulation of degenerating axons, undetected by the gold-standard marker of transport interruption, APP. While there was greater axonal co-localization between SNTF and APP after severe TBI in humans, a subset of SNTF positive axons displayed no APP accumulation. Notably, some co-localization was observed between SNTF and the less abundant neurofilament subtype markers. Other SNTF positive axons, however, did not co-localize with any other markers. Similarly, RMO-14 and NF-68 positive axonal pathology existed independent of SNTF and APP. These data demonstrate that multiple pathological axonal phenotypes exist post-TBI and provide insight into a more comprehensive approach to the neuropathological assessment of DAI.

Project description:Objective: Pupil dilation patterns are outside of conscious control and provide information regarding neuropsychological processes related to deception, cognitive effort, and familiarity. This study examined the incremental utility of pupillometry on the Test of Memory Malingering (TOMM) in classifying individuals with verified traumatic brain injury (TBI), individuals simulating TBI, and healthy comparisons. Method: Participants were 177 adults across three groups: verified TBI (n = 53), feigned cognitive impairment due to TBI (SIM, n = 52), and heathy comparisons (HC, n = 72). Results: Logistic regression and ROC curve analyses identified several pupil indices that discriminated the groups. Pupillometry discriminated best for the comparison of greatest clinical interest, verified TBI versus simulators, adding information beyond traditional accuracy scores. Simulators showed evidence of greater cognitive load than both groups instructed to perform at their best ability (HC and TBI). Additionally, the typically robust phenomenon of dilating to familiar stimuli was relatively diminished among TBI simulators compared to TBI and HC. This finding may reflect competing, interfering effects of cognitive effort that are frequently observed in pupillary reactivity during deception. However, the familiarity effect appeared on nearly half the trials for SIM participants. Among those trials evidencing the familiarity response, selection of the unfamiliar stimulus (i.e., dilation-response inconsistency) was associated with a sizeable increase in likelihood of being a simulator. Conclusions: Taken together, these findings provide strong support for multimethod assessment: adding unique performance assessments such as biometrics to standard accuracy scores. Continued study of pupillometry will enhance the identification of simulators who are not detected by traditional performance validity test scoring metrics. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Project description:Non-invasive brain stimulation has been widely investigated as a potential treatment for a range of neurological and psychiatric conditions, including brain injury. However, the behavioural effects of brain stimulation are variable, for reasons that are poorly understood. This is a particular challenge for traumatic brain injury, where patterns of damage and their clinical effects are heterogeneous. Here we test the hypothesis that the response to transcranial direct current stimulation following traumatic brain injury is dependent on white matter damage within the stimulated network. We used a novel simultaneous stimulation-MRI protocol applying anodal, cathodal and sham stimulation to 24 healthy control subjects and 35 patients with moderate/severe traumatic brain injury. Stimulation was applied to the right inferior frontal gyrus/anterior insula node of the salience network, which was targeted because our previous work had shown its importance to executive function. Stimulation was applied during performance of the Stop Signal Task, which assesses response inhibition, a key component of executive function. Structural MRI was used to assess the extent of brain injury, including diffusion MRI assessment of post-traumatic axonal injury. Functional MRI, which was simultaneously acquired to delivery of stimulation, assessed the effects of stimulation on cognitive network function. Anodal stimulation improved response inhibition in control participants, an effect that was not observed in the patient group. The extent of traumatic axonal injury within the salience network strongly influenced the behavioural response to stimulation. Increasing damage to the tract connecting the stimulated right inferior frontal gyrus/anterior insula to the rest of the salience network was associated with reduced beneficial effects of stimulation. In addition, anodal stimulation normalized default mode network activation in patients with poor response inhibition, suggesting that stimulation modulates communication between the networks involved in supporting cognitive control. These results demonstrate an important principle: that white matter structure of the connections within a stimulated brain network influences the behavioural response to stimulation. This suggests that a personalized approach to non-invasive brain stimulation is likely to be necessary, with structural integrity of the targeted brain networks an important criterion for patient selection and an individualized approach to the selection of stimulation parameters.

Project description:The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a controlled cortical impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4 T MRI at 2 weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in the corpus callosum, indicating white matter changes in the segments subjected to high strain, as predicted by the model. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of traumatic brain injury. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets.

Dataset Information

Detecting axonal injury in individual patients after traumatic brain injury.

Publications

Detecting axonal injury in individual patients after traumatic brain injury.

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