Article

Cerebral Atrophy after Traumatic White Matter Injury: Correlation with Acute Neuroimaging and Outcome

Department of Neurology, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9036, USA.
Journal of Neurotrauma (Impact Factor: 3.71). 12/2008; 25(12):1433-40. DOI: 10.1089/neu.2008.0683
Source: PubMed

ABSTRACT

Traumatic brain injury (TBI) is a pathologically heterogeneous disease, including injury to both neuronal cell bodies and axonal processes. Global atrophy of both gray and white matter is common after TBI. This study was designed to determine the relationship between neuroimaging markers of acute diffuse axonal injury (DAI) and cerebral atrophy months later. We performed high-resolution magnetic resonance imaging (MRI) at 3 Tesla (T) in 20 patients who suffered non-penetrating TBI, during the acute (within 1 month after the injury) and chronic stage (at least 6 months after the injury). Volume of abnormal fluid-attenuated inversion-recovery (FLAIR) signal seen in white matter in both acute and follow-up scans was quantified. White and gray matter volumes were also quantified. Functional outcome was measured using the Functional Status Examination (FSE) at the time of the chronic scan. Change in brain volumes, including whole brain volume (WBV), white matter volume (WMV), and gray matter volume (GMV), correlates significantly with acute DAI volume (r = -0.69, -0.59, -0.58, respectively; p <0.01 for all). Volume of acute FLAIR hyperintensities correlates with volume of decreased FLAIR signal in the follow-up scans (r = -0.86, p < 0.001). FSE performance correlates with acute hyperintensity volume and chronic cerebral atrophy (r = 0.53, p = 0.02; r = -0.45, p = 0.03, respectively). Acute axonal lesions measured by FLAIR imaging are strongly predictive of post-traumatic cerebral atrophy. Our findings suggest that axonal pathology measured as white matter lesions following TBI can be identified using MRI, and may be a useful measure for DAI-directed therapies.

Download full-text

Full-text

Available from: Caryn Rose Harper
  • Source
    • "Furthermore, recent evidence suggests that tissue pathology related to TBI can be progressive and chronic (Ding et al., 2008, Cole et al., 2015). "
    [Show abstract] [Hide abstract]
    ABSTRACT: In the United States alone, the number of persons living with the enduring consequences of traumatic brain injuries is estimated to be between 3.2 and 5 million. This number does not include individuals serving in the United States military or seeking care at Veterans Affairs hospitals. The importance of understanding the neurobiological consequences of mild traumatic brain injury (mTBI) has increased with the return of veterans from conflicts overseas, many of who have suffered this type of brain injury. However, identifying the neuroanatomical regions most affected by mTBI continues to prove challenging. The aim of this study was to assess the use of mean cortical curvature as a potential indicator of progressive tissue loss in a cross-sectional sample of 54 veterans with mTBI compared to 31 controls evaluated with MRI. It was hypothesized that mean cortical curvature would be increased in veterans with mTBI, relative to controls, due in part to cortical restructuring related to tissue volume loss. Mean cortical curvature was assessed in 60 bilateral regions (31 sulcal, 29 gyral). Of the 120 regions investigated, nearly 50% demonstrated significantly increased mean cortical curvature in mTBI relative to controls with 25% remaining significant following multiple comparison correction (all, pFDR<.05). These differences were most prominent in deep gray matter regions of the cortex. Additionally, significant relationships were found between mean cortical curvature and gray and white matter volumes (all, p<.05). These findings suggest potentially unique patterns of atrophy by region and indicate that changes in brain microstructure due to mTBI are sensitive to measures of mean curvature.
    Full-text · Article · Jan 2016 · Clinical neuroimaging
  • Source
    • "To date, there do not appear to be studies examining white matter hyperintensities (WMH) or other T2-w/FLAIR abnormalities in military and/or Veteran cohorts. Anecdotally, WMH are commonly observed in Service Member and/or Veteran participants with mTBI, and examination of these findings may yield additional information as studies in civilian TBI populations have demonstrated modest relationships between WMH volume and clinical outcomes including TBI severity (Bigler et al. 2013), functional outcomes (Marquez de la Plata et al. 2007), and atrophic changes (Ding et al. 2008). Currently, there also appear to be no studies specifically examining SWI abnormalities in military or Veteran populations . "
    [Show abstract] [Hide abstract]
    ABSTRACT: Traumatic brain injury (TBI) remains one of the most prevalent forms of morbidity among Veterans and Service Members, particularly for those engaged in the conflicts in Iraq and Afghanistan. Neuroimaging has been considered a potentially useful diagnostic and prognostic tool across the spectrum of TBI generally, but may have particular importance in military populations where the diagnosis of mild TBI is particularly challenging, given the frequent lack of documentation on the nature of the injuries and mixed etiologies, and highly comorbid with other disorders such as post-traumatic stress disorder, depression, and substance misuse. Imaging has also been employed in attempts to understand better the potential late effects of trauma and to evaluate the effects of promising therapeutic interventions. This review surveys the use of structural and functional neuroimaging techniques utilized in military studies published to date, including the utilization of quantitative fluid attenuated inversion recovery (FLAIR), susceptibility weighted imaging (SWI), volumetric analysis, diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), positron emission tomography (PET), magnetoencephalography (MEG), task-based and resting state functional MRI (fMRI), arterial spin labeling (ASL), and magnetic resonance spectroscopy (MRS). The importance of quality assurance testing in current and future research is also highlighted. Current challenges and limitations of each technique are outlined, and future directions are discussed.
    Full-text · Article · Sep 2015 · Brain Imaging and Behavior
  • Source
    • "After the acute injury secondary processes including complex metabolic cascades, alterations in cerebral blood flow and raised intracranial pressure may occur contributing to the burden of injury. It is well recognised that complex pathophysiological processes including secondary Wallerian-type degeneration continue to occur months to years after the initial insult (Meythaler et al., 2001; Ding et al., 2008; Warner et al., 2010a). In order to improve treatment stratification and patient outcomes, as well as more accurately predict outcome, we need to better understand the complexity and heterogeneity of TBI both in the acute and chronic stages. "
    [Show abstract] [Hide abstract]
    ABSTRACT: We propose a framework for the robust and fully-automatic segmentation of magnetic resonance (MR) brain images called "Multi-Atlas Label Propagation with Expectation-Maximisation based refinement" (MALP-EM). The presented approach is based on a robust registration approach (MAPER), highly performant label fusion (joint label fusion) and intensity-based label refinement using EM. We further adapt this framework to be applicable for the segmentation of brain images with gross changes in anatomy. We propose to account for consistent registration errors by relaxing anatomical priors obtained by multi-atlas propagation and a weighting scheme to locally combine anatomical atlas priors and intensity-refined posterior probabilities. The method is evaluated on a benchmark dataset used in a recent MICCAI segmentation challenge. In this context we show that MALP-EM is competitive for the segmentation of MR brain scans of healthy adults when compared to state-of-the-art automatic labelling techniques. To demonstrate the versatility of the proposed approach, we employed MALP-EM to segment 125 MR brain images into 134 regions from subjects who had sustained traumatic brain injury (TBI). We employ a protocol to assess segmentation quality if no manual reference labels are available. Based on this protocol, three independent, blinded raters confirmed on 13 MR brain scans with pathology that MALP-EM is superior to established label fusion techniques. We visually confirm the robustness of our segmentation approach on the full cohort and investigate the potential of derived symmetry-based imaging biomarkers that correlate with and predict clinically relevant variables in TBI such as the Marshall Classification (MC) or Glasgow Outcome Score (GOS). Specifically, we show that we are able to stratify TBI patients with favourable outcomes from non-favourable outcomes with 64.7% accuracy using acute-phase MR images and 66.8% accuracy using follow-up MR images. Furthermore, we are able to differentiate subjects with the presence of a mass lesion or midline shift from those with diffuse brain injury with 76.0% accuracy. The thalamus, putamen, pallidum and hippocampus are particularly affected. Their involvement predicts TBI disease progression.
    Full-text · Article · Feb 2015 · Medical Image Analysis
Show more