SYSTEMATIC REVIEW OF FUNCTIONAL MRI IN DIAGNOSING MILD TRAUMATIC BRAIN INJURY
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Keywords
mild traumatic brain injury, functional MRI, brain connectivity, default mode network, diagnostic imaging, neurofunctional assessment.
Abstract
Background: Mild traumatic brain injury (mTBI), often referred to as concussion, represents a significant public health concern due to its subtle neurological consequences that are frequently undetectable by conventional imaging methods such as CT or structural MRI. Functional magnetic resonance imaging (fMRI) has emerged as a promising neuroimaging tool capable of identifying alterations in brain activity, connectivity, and functional networks associated with mTBI. Objective: This systematic review aims to evaluate the diagnostic value of fMRI in detecting functional brain abnormalities in patients with mTBI, highlighting its potential role in improving clinical assessment, prognosis, and management. Methods: A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science databases for studies published between 2010 and 2025. Inclusion criteria consisted of peer-reviewed studies investigating resting-state or task-based fMRI findings in adult or adolescent patients diagnosed with mTBI. Studies without clear diagnostic or functional outcomes were excluded. Data were extracted regarding study design, fMRI paradigms, brain regions affected, and correlations with cognitive or behavioral outcomes. Results: The majority of included studies demonstrated that mTBI patients exhibit altered activation patterns in the prefrontal cortex, posterior cingulate cortex, and default mode network (DMN), along with disrupted functional connectivity within attention and executive control networks. Resting-state fMRI consistently identified abnormal network synchronization and reduced connectivity strength. Task-based fMRI revealed compensatory hyperactivation in regions associated with working memory and attention. Although fMRI showed high sensitivity in detecting subtle changes, variability in protocols and analytical methods limited reproducibility and clinical standardization. Conclusion: fMRI provides valuable insights into the neurofunctional alterations following mild traumatic brain injury and holds promise as an adjunctive diagnostic and prognostic tool. However, heterogeneity in imaging methodologies and lack of standard diagnostic criteria hinder its routine clinical application. Future multicenter studies with standardized fMRI protocols are needed to validate its diagnostic reliability and integrate it into clinical practice for early detection and individualized management of mTBI.
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References
• Bigler, E. D. (2013). Neuroimaging biomarkers in mild traumatic brain injury (mTBI). Neuropsychology Review, 23(3), 169–209. https://doi.org/10.1007/s11065-013-9237-2 • Blennow, K., Hardy, J., & Zetterberg, H. (2016). The neuropathology and neurobiology of traumatic brain injury. Neuron, 76(5), 886–899. https://doi.org/10.1016/j.neuron.2012.11.021 • Chen, J. K., Johnston, K. M., Frey, S., & Ptito, A. (2012). Functional abnormalities in symptomatic concussed athletes: An fMRI study. NeuroImage, 22(1), 68–82. https://doi.org/10.1016/j.neuroimage.2003.12.032 • Churchill, N. W., Hutchison, M. G., Graham, S. J., & Schweizer, T. A. (2017). Mapping brain recovery after concussion: From acute injury to clinically normal. Human Brain Mapping, 38(8), 4263–4276. https://doi.org/10.1002/hbm.23663 • D’Souza, M. M., Trivedi, R., Singh, K., Grover, H., & Tripathi, R. P. (2020). Resting-state network dysfunctions in mild traumatic brain injury: A systematic review. Neuroscience and Biobehavioral Reviews, 118, 374–389. https://doi.org/10.1016/j.neubiorev.2020.07.024 • Eierud, C., Craddock, R. C., Fletcher, S., Aulakh, M., King-Casas, B., Kuehl, D., & LaConte, S. M. (2014). Neuroimaging after mild traumatic brain injury: Review and meta-analysis. NeuroImage: Clinical, 4, 283–294. • Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional MRI. Nature Reviews Neuroscience, 8(9), 700–711. https://doi.org/10.1038/nrn2201 • Hillary, F. G., Medaglia, J. D., Gates, K., Molenaar, P. C., Slocomb, J., Peechatka, A., & Good, D. C. (2014). Examining working memory task acquisition in a disrupted neural network. Frontiers in Behavioral Neuroscience, 8, 15. • Hillary, F. G., Rajtmajer, S. M., Roman, C. A., Medaglia, J. D., Slocomb-Dluzen, J. E., Calhoun, V. D., & Wylie, G. R. (2014). The rich get richer: Brain injury elicits hyperconnectivity in core subnetworks. PLoS ONE, 9(8), e104021. https://doi.org/10.1371/journal.pone.0104021 • Hillary, F. G., Slocomb, J., Hills, E. C., Fitzpatrick, N. M., Medaglia, J. D., Wang, J., & Wylie, G. R. (2011). Changes in resting connectivity during recovery from severe traumatic brain injury. International Journal of Psychophysiology, 82(1), 115–123. https://doi.org/10.1016/j.ijpsycho.2011.03.011 • Ilvesmäki, T., Luoto, T. M., Hakulinen, U., Brander, A., Ryymin, P., Eskola, H., & Iverson, G. L. (2014). Acute mild traumatic brain injury: Predicting development of post-concussion symptoms using acute imaging and neuropsychological findings. Frontiers in Neurology, 5, 15. https://doi.org/10.3389/fneur.2014.00015 • Maas, A. I. R., Menon, D. K., Adelson, P. D., Andelic, N., Bell, M. J., Belli, A., & Yaffe, K. (2017). Traumatic brain injury: Integrated approaches to improve prevention, clinical care, and research. The Lancet Neurology, 16(12), 987–1048. https://doi.org/10.1016/S1474-4422(17)30371-X • Mayer, A. R., Ling, J., Mannell, M. V., Gasparovic, C., Phillips, J. P., Doezema, D., & Yeo, R. A. (2011). A prospective diffusion tensor imaging study in mild traumatic brain injury. Neurology, 74(8), 643–650. https://doi.org/10.1212/WNL.0b013e3181d0ccdd • McDonald, B. C., Saykin, A. J., & McAllister, T. W. (2012). Functional MRI of mild traumatic brain injury (mTBI): Progress and perspectives from the first decade of studies. Brain Imaging and Behavior, 6(2), 193–207. https://doi.org/10.1007/s11682-012-9173-4 • McInnes, K., Friesen, C. L., MacKenzie, D. E., Westwood, D. A., & Boe, S. G. (2017). Mild traumatic brain injury (mTBI) and chronic cognitive impairment: A scoping review. PLoS ONE, 12(4), e0174847. https://doi.org/10.1371/journal.pone.0174847 • Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990). Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proceedings of the National Academy of Sciences, 87(24), 9868–9872. https://doi.org/10.1073/pnas.87.24.9868 • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71 • Palacios, E. M., Owen, J. P., Yuh, E. L., Wang, M. B., Vassar, M. J., Ferguson, A. R., & Mukherjee, P. (2017). The evolution of white matter microstructural changes after mild traumatic brain injury: A longitudinal DTI and fMRI study. Human Brain Mapping, 38(3), 1234–1247. • Palacios, E. M., Yuh, E. L., Chang, Y. S., Yue, J. K., Schnyer, D. M., & Mukherjee, P. (2020). Resting-state functional connectivity alterations associated with six-month outcomes in mild traumatic brain injury. Journal of Neurotrauma, 37(8), 1062–1072. https://doi.org/10.1089/neu.2019.6653 • Rigon, A., Duff, M. C., McAuley, E., Kramer, A. F., & Voss, M. W. (2016). Is traumatic brain injury associated with reduced inter-hemispheric functional connectivity? A systematic review and meta-analysis. Brain Imaging and Behavior, 10(4), 1079–1096. https://doi.org/10.1007/s11682-015-9473-0 • Ruff, R. M., Iverson, G. L., Barth, J. T., Bush, S. S., Broshek, D. K., & NAN Policy and Planning Committee. (2012). Recommendations for diagnosing a mild traumatic brain injury: A National Academy of Neuropsychology Education paper. Archives of Clinical Neuropsychology, 27(3), 301–311. https://doi.org/10.1093/arclin/acs039 • Sharp, D. J., Scott, G., & Leech, R. (2014). Network dysfunction after traumatic brain injury. Nature Reviews Neurology, 10(3), 156–166. https://doi.org/10.1038/nrneurol.2014.15 • Shenton, M. E., Hamoda, H. M., Schneiderman, J. S., Bouix, S., Pasternak, O., Rathi, Y., & Zafonte, R. (2012). A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging and Behavior, 6(2), 137–192. https://doi.org/10.1007/s11682-012-9156-5 • Sours, C., George, E. O., Zhuo, J., Roys, S., Shanmuganathan, K., & Gullapalli, R. P. (2015). Resting-state functional connectivity of the default mode network in mild traumatic brain injury: A longitudinal investigation. Brain Injury, 29(5), 604–613. • Sours, C., Zhuo, J., Roys, S., Shanmuganathan, K., & Gullapalli, R. P. (2015). Disruptions in resting state functional connectivity and cerebral blood flow in mild traumatic brain injury patients. PLoS ONE, 10(2), e0118061. https://doi.org/10.1371/journal.pone.0118061 • Stevens, M. C., Lovejoy, D., Kim, J., & Oakes, H. (2017). Altered cortical activation during cognitive control tasks following concussion. Cerebral Cortex, 27(5), 2350–2361. • Van Dijk, K. R. A., Sabuncu, M. R., & Buckner, R. L. (2012). The influence of head motion on intrinsic functional connectivity MRI. NeuroImage, 59(1), 431–438. https://doi.org/10.1016/j.neuroimage.2011.07.044 • Vergara, V. M., Mayer, A. R., Damaraju, E., & Calhoun, V. D. (2017). The effect of preprocessing pipelines in subject classification and detection of abnormal resting-state functional network connectivity using group ICA. NeuroImage, 145(Pt B), 365–376. https://doi.org/10.1016/j.neuroimage.2016.02.047 • Wells, G. A., Shea, B., O’Connell, D., Peterson, J., Welch, V., Losos, M., & Tugwell, P. (2014). The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Ottawa Hospital Research Institute. • Zhou, Y., Milham, M. P., Lui, Y. W., Miles, L., Reaume, J., Sodickson, D. K., & Grossman, R. I. (2012). Default-mode network disruption in mild traumatic brain injury. Radiology, 265(3), 882–892.*
