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A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury

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Abstract

Mild traumatic brain injury (mTBI), also referred to as concussion, remains a controversial diagnosis because the brain often appears quite normal on conventional computed tomography (CT) and magnetic resonance imaging (MRI) scans. Such conventional tools, however, do not adequately depict brain injury in mTBI because they are not sensitive to detecting diffuse axonal injuries (DAI), also described as traumatic axonal injuries (TAI), the major brain injuries in mTBI. Furthermore, for the 15 to 30 % of those diagnosed with mTBI on the basis of cognitive and clinical symptoms, i.e., the “miserable minority,” the cognitive and physical symptoms do not resolve following the first 3 months post-injury. Instead, they persist, and in some cases lead to long-term disability. The explanation given for these chronic symptoms, i.e., postconcussive syndrome, particularly in cases where there is no discernible radiological evidence for brain injury, has led some to posit a psychogenic origin. Such attributions are made all the easier since both posttraumatic stress disorder (PTSD) and depression are frequently co-morbid with mTBI. The challenge is thus to use neuroimaging tools that are sensitive to DAI/TAI, such as diffusion tensor imaging (DTI), in order to detect brain injuries in mTBI. Of note here, recent advances in neuroimaging techniques, such as DTI, make it possible to characterize better extant brain abnormalities in mTBI. These advances may lead to the development of biomarkers of injury, as well as to staging of reorganization and reversal of white matter changes following injury, and to the ability to track and to characterize changes in brain injury over time. Such tools will likely be used in future research to evaluate treatment efficacy, given their enhanced sensitivity to alterations in the brain. In this article we review the incidence of mTBI and the importance of characterizing this patient population using objective radiological measures. Evidence is presented for detecting brain abnormalities in mTBI based on studies that use advanced neuroimaging techniques. Taken together, these findings suggest that more sensitive neuroimaging tools improve the detection of brain abnormalities (i.e., diagnosis) in mTBI. These tools will likely also provide important information relevant to outcome (prognosis), as well as play an important role in longitudinal studies that are needed to understand the dynamic nature of brain injury in mTBI. Additionally, summary tables of MRI and DTI findings are included. We believe that the enhanced sensitivity of newer and more advanced neuroimaging techniques for identifying areas of brain damage in mTBI will be important for documenting the biological basis of postconcussive symptoms, which are likely associated with subtle brain alterations, alterations that have heretofore gone undetected due to the lack of sensitivity of earlier neuroimaging techniques. Nonetheless, it is noteworthy to point out that detecting brain abnormalities in mTBI does not mean that other disorders of a more psychogenic origin are not co-morbid with mTBI and equally important to treat. They arguably are. The controversy of psychogenic versus physiogenic, however, is not productive because the psychogenic view does not carefully consider the limitations of conventional neuroimaging techniques in detecting subtle brain injuries in mTBI, and the physiogenic view does not carefully consider the fact that PTSD and depression, and other co-morbid conditions, may be present in those suffering from mTBI. Finally, we end with a discussion of future directions in research that will lead to the improved care of patients diagnosed with mTBI.

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Acknowledgements

This work was supported in part by the INTRuST Posttraumatic Stress Disorder and Traumatic Brain Injury Clinical Consortium funded by the Department of Defense Psychological Health/Traumatic Brain Injury Research Program (X81XWH-07-CC-CS-DoD; MES, JSS, SB, OP, MK, YR, M-AV, C-FW, RZ), by an NIH NINDS funded R01 (R01 NS 078337; RS, MES, JSS), by a Center for Integration of Medicine (CIMIT) Soldier in Medicine Award (SB, MES), by an NIH NIMH funding R01 (R01 MH082918; SB), by funding from the National Research Service Award (T32AT000051; MPP) from the National Center for Complementary and Alternative Medicine (NCCAM) at the National Institute of Health, by the Harvard Medical School Fellowship as part of the Eleanor and Miles Shore Fellowship Program (HH), by the Deutsche Akademischer Austauschdienst (DAAD; IK), and by funding from NCRR, including the National Alliance for Medical Image Computing (NAMIC-U54 EBOO5149; RK, MK, MES), and the Neuroimaging Analysis Center (NAC; P41RR13218; RK and CF).

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Authors and Affiliations

  1. Clinical Neuroscience Laboratory, Laboratory of Neuroscience, Department of Psychiatry, VA Boston Healthcare System, and Harvard Medical School, Brockton, MA, USA

    M. E. Shenton

  2. Psychiatry Neuroimaging Laboratory, Departments of Psychiatry and Radiology, Brigham and Women’s Hospital, and Harvard Medical School, 1249 Boylston Street, Boston, MA, 02215, USA

    M. E. Shenton, H. M. Hamoda, J. S. Schneiderman, S. Bouix, O. Pasternak, Y. Rathi, M.-A. Vu, M. P. Purohit, I. Koerte & M. Kubicki

  3. Department of Psychiatry, Children’s Hospital, and Harvard Medical School, Boston, MA, USA

    H. M. Hamoda

  4. Laboratory of Mathematics in Imaging, Department of Radiology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, MA, USA

    O. Pasternak & C.-F. Westin

  5. Spaulding Rehabilitation Hospital, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    M. P. Purohit & R. Zafonte

  6. Division of Medicine, Beth Israel-Deaconness Medical Center, and Harvard Medical School, Boston, MA, USA

    M. P. Purohit

  7. Department of Radiology, Athinoula A.Martinos Center, Massachusetts General Hospital, and Harvard Medical School, Charlestown, MA, USA

    K. Helmer

  8. Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, MA, USA

    A. P. Lin

  9. Surgical Planning Laboratory, MRI Division, Department of Radiology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, MA, USA

    R. Kikinis

  10. Center for The Study of Traumatic Encephalopathy, Departments of Neurology and Neurosurgery, Boston University Medical School, Boston, MA, USA

    R. A. Stern

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Shenton, M.E., Hamoda, H.M., Schneiderman, J.S. et al. A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging and Behavior 6, 137–192 (2012). https://doi.org/10.1007/s11682-012-9156-5

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