Mild traumatic brain injury (TBI) represents one of the most significant health issues in VA and active duty military patients. Diagnosing and monitoring of TBI are major focuses of VA research. Mild (and some moderate) TBI can be difficult to diagnose because the injuries are generally not visible on conventional acute neuroimaging techniques (e.g., CT and MRI). Furthermore, conventional neuroimaging techniques have limited sensitivity to the physiological alterations due to TBI, and poor predictive utility for long-term outcome. Our preliminary study shows that neuronal tissues injured by trauma generate low frequency electromagnetic signals, decreased functional connectivity, and reduction of diffusion anisotropy. The proposed study will use integrated multi-modality neuroimaging approach involving Magnetoencephalography (MEG) and diffusion tensor imaging (DTI) in diagnosing and monitoring mild TBI. This approach has the potential of attaining higher sensitivity and specificity than conventional imaging techniques in detecting subtle neuronal injuries in mild TBI patients in VA and active duty military patients. There are three specific aims in the proposed study:
Specific Aim 1 will investigate the diagnostic value of the integrated MEG-DTI approach in VA and active duty patients with mTBI by detecting neuronal injuries (loci of the injury as well as affected neuronal networks) not visible with conventional neuroimaging methods (e.g., CT and MRI). Our preliminary data show that pathological MEG slow-waves, reduced MEG functional connectivity, and reduced DTI anisotropy are characteristics of axonal injury due to tissue shearing and stretching in mTBI, with markedly better sensitivity than CT/MRI in diagnosing individual mild TBI patients.
Specific Aim 2 studies the neurophysiological basis of the cognitive impairments using N-back working memory (WM) MEG task in active duty and VA patients with mild TBI.
Specific Aim 3 of the present application will study the relationship between post-concussive symptoms, cognitive deficits as measured by neuropsychological exams, and the neuroimaging measurements with MEG and DTI in VA and active duty patients with mTBI. To achieve these aims, we propose to develop new imaging analysis tools: frequency-domain VESTAL for accurately localizing pathological MEG slow-waves; Dual-core Beamformer for reliably obtaining the neuronal networks with reduced functional connectivity using MEG under the condition of poor signal to noise ratio; and a platform for integrating the functional MEG findings in the gray-matter with structural DTI findings in the white-matter fiber tracts. The success of the proposed approach will not only greatly enhance our ability to diagnose mild TBI by detecting subtle neural injuries (e.g., loci and networks) that are invisible using conventional neuroimaging techniques, but also will provide the neuroimaging tools and software which can potentially be used as an objective evaluation method during pre- and post-intervention assessments of novel neuropharmacological and/or neuropsychological treatments for VA and active duty patients with TBI.

Public Health Relevance

Traumatic brain injury is a leading cause of sustained physical, cognitive, emotional, and behavioral deficits in VA and active duty military patients. Diagnosing mild TBI is challenging. Patients with mild TBI often show significant neuropsychological dysfunction despite the lack of obvious external injuries and visible findings from conventional neuroimaging techniques (e.g., CT and MRI) MRI or CT. On the other hand, our preliminary study shows that neuronal tissues injured by trauma generate low frequency electromagnetic signals, decreased functional connectivity, and reduction of diffusion anisotropy. The proposed study will use integrated multi-modality neuroimaging approach involving Magnetoencephalography (MEG) and diffusion tensor imaging (DTI) in diagnosing and monitoring mild TBI. This approach has the potential of attaining higher sensitivity and specificity than conventional imaging techniques in detecting subtle neuronal injuries in mild TBI patients in VA and active duty military patients.

Agency
National Institute of Health (NIH)
Institute
Veterans Affairs (VA)
Type
Non-HHS Research Projects (I01)
Project #
5I01CX000499-04
Application #
8768456
Study Section
Neurobiology C (NURC)
Project Start
2011-10-01
Project End
2015-09-30
Budget Start
2014-10-01
Budget End
2015-09-30
Support Year
4
Fiscal Year
2015
Total Cost
Indirect Cost
Name
VA San Diego Healthcare System
Department
Type
DUNS #
073358855
City
San Diego
State
CA
Country
United States
Zip Code
92161
Huang, Ming-Xiong; Nichols, Sharon; Robb-Swan, Ashley et al. (2018) MEG Working Memory N-Back Task Reveals Functional Deficits in Combat-Related Mild Traumatic Brain Injury. Cereb Cortex :
Edgar, J Christopher; Fisk IV, Charles L; Chen, Yu-Han et al. (2017) By our bootstraps: Comparing methods for measuring auditory 40 Hz steady-state neural activity. Psychophysiology 54:1110-1127
Huang, Ming-Xiong; Anderson, Bill; Huang, Charles W et al. (2017) Development of advanced signal processing and source imaging methods for superparamagnetic relaxometry. Phys Med Biol 62:734-757
Huang, Ming-Xiong; Harrington, Deborah L; Robb Swan, Ashley et al. (2017) Resting-State Magnetoencephalography Reveals Different Patterns of Aberrant Functional Connectivity in Combat-Related Mild Traumatic Brain Injury. J Neurotrauma 34:1412-1426
Huang, Ming-Xiong; Swan, Ashley Robb; Quinto, Annemarie Angeles et al. (2017) A pilot treatment study for mild traumatic brain injury: Neuroimaging changes detected by MEG after low-intensity pulse-based transcranial electrical stimulation. Brain Inj 31:1951-1963
Huang, Mingxiong; Risling, MÃ¥rten; Baker, Dewleen G (2016) The role of biomarkers and MEG-based imaging markers in the diagnosis of post-traumatic stress disorder and blast-induced mild traumatic brain injury. Psychoneuroendocrinology 63:398-409
Huang, Charles W; Huang, Ming-Xiong; Ji, Zhengwei et al. (2016) High-resolution MEG source imaging approach to accurately localize Broca's area in patients with brain tumor or epilepsy. Clin Neurophysiol 127:2308-16
Robb Swan, Ashley; Nichols, Sharon; Drake, Angela et al. (2015) Magnetoencephalography Slow-Wave Detection in Patients with Mild Traumatic Brain Injury and Ongoing Symptoms Correlated with Long-Term Neuropsychological Outcome. J Neurotrauma 32:1510-21
Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley et al. (2014) MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images. Neuroimage 84:585-604
Huang, Ming-Xiong; Yurgil, Kate A; Robb, Ashley et al. (2014) Voxel-wise resting-state MEG source magnitude imaging study reveals neurocircuitry abnormality in active-duty service members and veterans with PTSD. Neuroimage Clin 5:408-19

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