Abstract
Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.







Similar content being viewed by others
Data Availability
Data available on request due to privacy/ethical restrictions.
References
Abdullah, A. N., Ahmad, A. H., Zakaria, R., Tamam, S., Abd Hamid, A. I., Chai, W. J., Omar, H., Abdul Rahman, M. R., Fitzrol, D. N., Idris, Z., Ghani, A. R. I., Wan Mohamad, W. N. A., Mustafar, F., Hanafi, M. H., Reza, M. F., Umar, H., Mohd Zulkifly, M. F., Ang, S. Y., Zakaria, Z., … Abdullah, J. M. (2022). Disruption of white matter integrity and its relationship with cognitive function in non-severe traumatic brain injury. Frontiers in Neurology, 13, 1011304.
Akiki, T. J., Averill, C. L., Wrocklage, K. M., Scott, J. C., Averill, L. A., Schweinsburg, B., Alexander-Bloch, A., Martini, B., Southwick, S. M., Krystal, J. H., & Abdallah, C. G. (2018). Default mode network abnormalities in posttraumatic stress disorder: A novel network-restricted topology approach. NeuroImage, 176, 489–498.
Andersson, J. L., Skare, S., & Ashburner, J. (2003). How to correct susceptibility distortions in spin-echo echo-planar images: Application to diffusion tensor imaging. NeuroImage, 20, 870–888.
Andersson, J. L. R., & Sotiropoulos, S. N. (2016). An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. NeuroImage, 125, 1063–1078.
Bassett, D. S., & Sporns, O. (2017). Network neuroscience. Nature Neuroscience, 20, 353–364.
Brown, S. S. G., Dams-O’Connor, K., Watson, E., Balchandani, P., & Feldman, R. E. (2021). Case report: An MRI traumatic brain injury longitudinal case study at 7 tesla: Pre- and post-injury structural network and volumetric reorganization and recovery. Frontiers in Neurology, 12, 631330.
Bukkieva, T., Pospelova, M., Efimtsev, A., Fionik, O., Alekseeva, T., Samochernych, K., Gorbunova, E., Krasnikova, V., Makhanova, A., Levchuk, A., Trufanov, G., Combs, S., & Shevtsov, M. (2022). Functional network connectivity reveals the brain functional alterations in breast cancer survivors. Journal of Clinical Medicine, 11, 617.
Caeyenberghs, K., Leemans, A., Leunissen, I., Gooijers, J., Michiels, K., Sunaert, S., & Swinnen, S. P. (2014). Altered structural networks and executive deficits in traumatic brain injury patients. Brain Structure & Function, 219, 193–209.
Cordero-Grande, L., Christiaens, D., Hutter, J., Price, A. N., & Hajnal, J. V. (2019). Complex diffusion-weighted image estimation via matrix recovery under general noise models. NeuroImage, 200, 391–404.
Corrigan, J. D., & Bogner, J. (2007). Initial reliability and validity of the Ohio State University TBI Identification Method. The Journal of Head Trauma Rehabilitation, 22, 318–329.
Desikan, R. S., Segonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., Albert, M. S., & Killiany, R. J. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31, 968–980.
Douaud, G., Lee, S., Alfaro-Almagro, F., Arthofer, C., Wang, C., Mccarthy, P., Lange, F., Andersson, J. L. R., Griffanti, L., Duff, E., Jbabdi, S., Taschler, B., Keating, P., Winkler, A. M., Collins, R., Matthews, P. M., Allen, N., Miller, K. L., Nichols, T. E., & Smith, S. M. (2022). SARS-CoV-2 is associated with changes in brain structure in UK Biobank. Nature, 604, 697–707.
Edlow, B. L., Copen, W. A., Izzy, S., Bakhadirov, K., van der Kouwe, A., Glenn, M. B., Greenberg, S. M., Greer, D. M., & Wu, O. (2016). Diffusion tensor imaging in acute-to-subacute traumatic brain injury: A longitudinal analysis. BMC Neurology, 16, 2.
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.
Farahani, F. V., Karwowski, W., & Lighthall, N. R. (2019). Application of graph theory for identifying connectivity patterns in human brain networks: A systematic review. Frontiers in Neuroscience, 13, 585.
Filippi, M., Basaia, S., Canu, E., Imperiale, F., Magnani, G., Falautano, M., Comi, G., Falini, A., & Agosta, F. (2020). Changes in functional and structural brain connectome along the Alzheimer’s disease continuum. Molecular Psychiatry, 25, 230–239.
Fino, P. C., Raffegeau, T. E., Parrington, L., Peterka, R. J., & King, L. A. (2020). Head stabilization during standing in people with persisting symptoms after mild traumatic brain injury. Journal of Biomechanics, 112, 110045.
Fischl, B. (2012). FreeSurfer. Neuroimage, 62, 774–781.
Fischl, B., Sereno, M. I., Tootell, R. B., & Dale, A. M. (1999). High-resolution intersubject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 8, 272–284.
Fortier, C. B., Amick, M. M., Grande, L., McGlynn, S., Kenna, A., Morra, L., Clark, A., Milberg, W. P., & McGlinchey, R. E. (2014). The Boston Assessment of Traumatic Brain Injury-Lifetime (BAT-L) semistructured interview: Evidence of research utility and validity. The Journal of Head Trauma Rehabilitation, 29, 89–98.
Genovese, C. R., Lazar, N. A., & Nichols, T. (2002). Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage, 15, 870–878.
Gilmore, J. H., Knickmeyer, R. C., & Gao, W. (2018). Imaging structural and functional brain development in early childhood. Nature Reviews Neuroscience, 19, 123–137.
Goulas, A., Uylings, H. B., & Hilgetag, C. C. (2017). Principles of ipsilateral and contralateral cortico-cortical connectivity in the mouse. Brain Structure & Function, 222, 1281–1295.
Graham, N. S., & Sharp, D. J. (2019). Understanding neurodegeneration after traumatic brain injury: From mechanisms to clinical trials in dementia. Journal of Neurology, Neurosurgery and Psychiatry, 90, 1221–1233.
Hannawi, Y., & Stevens, R. D. (2016). Mapping the connectome following traumatic brain injury. Current Neurology and Neuroscience Reports, 16, 44.
Hilger, K., & Markett, S. (2021). Personality network neuroscience: Promises and challenges on the way toward a unifying framework of individual variability. Netw Neurosci, 5, 631–645.
Holland, D., Kuperman, J. M., & Dale, A. M. (2010). Efficient correction of inhomogeneous static magnetic field-induced distortion in Echo Planar Imaging. NeuroImage, 50, 175–183.
Imms, P., Clemente, A., Cook, M., D’Souza, W., Wilson, P. H., Jones, D. K., & Caeyenberghs, K. (2019). The structural connectome in traumatic brain injury: A meta-analysis of graph metrics. Neuroscience and Biobehavioral Reviews, 99, 128–137.
Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W., & Smith, S. M. (2012). Fsl. Neuroimage, 62, 782–790.
Johnson, V. E., Stewart, W., & Smith, D. H. (2013). Axonal pathology in traumatic brain injury. Experimental Neurology, 246, 35–43.
Kang, X., Yoon, B. C., & Adamson, M. M. (2023). Fixel-based analysis of the diffusion properties of the patients with brain injury and chronic health symptoms. Neuroscience Research, 192, 63–76.
Kang, X., Yund, E. W., Herron, T. J., & Woods, D. L. (2007). Improving the resolution of functional brain imaging: Analyzing functional data in anatomical space. Magnetic Resonance Imaging, 25, 1070–1078.
Kellner, E., Dhital, B., Kiselev, V. G., & Reisert, M. (2016). Gibbs-ringing artifact removal based on local subvoxel-shifts. Magnetic Resonance in Medicine, 76, 1574–1581.
Kerley, C. I., Cai, L. Y., Yu, C., Crawford, L. M., Elenberger, J. M., Singh, E. S., Schilling, K. G., Aboud, K. S., Landman, B. A., & Rex, T. S. (2021). Joint analysis of structural connectivity and cortical surface features: Correlates with mild traumatic brain injury. Proceedings of SPIE - The International Society for Optical Engineering, 11596, 115960R. https://doi.org/10.1117/12.2580902
Kinnunen, K. M., Greenwood, R., Powell, J. H., Leech, R., Hawkins, P. C., Bonnelle, V., Patel, M. C., Counsell, S. J., & Sharp, D. J. (2011). White matter damage and cognitive impairment after traumatic brain injury. Brain, 134, 449–463.
Klimova, A., Korgaonkar, M. S., Whitford, T., & Bryant, R. A. (2019). Diffusion tensor imaging analysis of mild traumatic brain injury and posttraumatic stress disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4, 81–90.
Konigs, M., van Heurn, L. W. E., Bakx, R., Vermeulen, R. J., Goslings, J. C., Poll-The, B. T., van der Wees, M., Catsman-Berrevoets, C. E., Oosterlaan, J., & Pouwels, P. J. W. (2017). The structural connectome of children with traumatic brain injury. Human Brain Mapping, 38, 3603–3614.
Krzywinski, M., Schein, J., Birol, I., Connors, J., Gascoyne, R., Horsman, D., Jones, S. J., & Marra, M. A. (2009). Circos: An information aesthetic for comparative genomics. Genome Research, 19, 1639–1645.
Mallas, E. J., De Simoni, S., Scott, G., Jolly, A. E., Hampshire, A., Li, L. M., Bourke, N. J., Roberts, S. A. G., Gorgoraptis, N., & Sharp, D. J. (2021). Abnormal dorsal attention network activation in memory impairment after traumatic brain injury. Brain, 144, 114–127.
Moody, J. F., Adluru, N., Alexander, A. L., & Field, A. S. (2021). The connectomes: Methods of white matter tractography and contributions of resting state fMRI. Seminars in Ultrasound, CT, and MR, 42, 507–522.
Nathan, D. E., Bellgowan, J. F., Oakes, T. R., French, L. M., Nadar, S. R., Sham, E. B., Liu, W., & Riedy, G. (2016). Assessing quantitative changes in intrinsic thalamic networks in blast and nonblast mild traumatic brain injury: Implications for mechanisms of injury. Brain Connectivity, 6, 389–402.
Oishi, K., Mielke, M. M., Albert, M., Lyketsos, C. G., & Mori, S. (2011). DTI analyses and clinical applications in Alzheimer’s disease. Journal of Alzheimer’s Disease : JAD, 26(Suppl 3), 287–296.
Proessl, F., Dretsch, M. N., Connaboy, C., Lovalekar, M., Dunn-Lewis, C., Canino, M. C., Sterczala, A. J., Deshpande, G., Katz, J. S., Denney, T. S., & Flanagan, S. D. (2020). Structural connectome disruptions in military personnel with mild traumatic brain injury and post-traumatic stress disorder. Journal of Neurotrauma, 37, 2102–2112.
Quinn, D. K., Mayer, A. R., Master, C. L., & Fann, J. R. (2018). Prolonged postconcussive symptoms. The American Journal of Psychiatry, 175, 103–111.
Raffelt, D., Tournier, J. D., Rose, S., Ridgway, G. R., Henderson, R., Crozier, S., Salvado, O., & Connelly, A. (2012). Apparent fibre density: A novel measure for the analysis of diffusion-weighted magnetic resonance images. NeuroImage, 59, 3976–3994.
Raffelt, D. A., Tournier, J. D., Smith, R. E., Vaughan, D. N., Jackson, G., Ridgway, G. R., & Connelly, A. (2017). Investigating white matter fibre density and morphology using fixel-based analysis. NeuroImage, 144, 58–73.
Raizman, R., Tavor, I., Biegon, A., Harnof, S., Hoffmann, C., Tsarfaty, G., Fruchter, E., Tatsa-Laur, L., Weiser, M., & Livny, A. (2020). Traumatic brain injury severity in a network perspective: A diffusion MRI based connectome study. Science and Reports, 10, 9121.
Rosen, B. Q., & Halgren, E. (2021). A whole-cortex probabilistic diffusion tractography connectome. eNeuro, 8(1), ENEURO.0416-20.2020. https://doi.org/10.1523/ENEURO.0416-20.2020
Rowland, J. A., Stapleton-Kotloski, J. R., Dobbins, D. L., Rogers, E., Godwin, D. W., & Taber, K. H. (2018). Increased small-world network topology following deployment-acquired traumatic brain injury associated with the development of post-traumatic stress disorder. Brain Connectivity, 8, 205–211.
Rubiano, A. M., Carney, N., Chesnut, R., & Puyana, J. C. (2015). Global neurotrauma research challenges and opportunities. Nature, 527, S193–S197.
Sim, K. S., Lai, M. A., Tso, C. P., & Teo, C. C. (2011). Single image signal-to-noise ratio estimation for magnetic resonance images. Journal of Medical Systems, 35, 39–48.
Smith, R. E., Tournier, J. D., Calamante, F., & Connelly, A. (2012). Anatomically-constrained tractography: Improved diffusion MRI streamlines tractography through effective use of anatomical information. NeuroImage, 62, 1924–1938.
Smith, R. E., Tournier, J. D., Calamante, F., & Connelly, A. (2013). SIFT: Spherical-deconvolution informed filtering of tractograms. NeuroImage, 67, 298–312.
Smith, R. E., Tournier, J. D., Calamante, F., & Connelly, A. (2015a). The effects of SIFT on the reproducibility and biological accuracy of the structural connectome. NeuroImage, 104, 253–265.
Smith, R. E., Tournier, J. D., Calamante, F., & Connelly, A. (2015b). SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography. NeuroImage, 119, 338–351.
Sours, C., Raghavan, P., Medina, A. E., Roys, S., Jiang, L., Zhuo, J., & Gullapalli, R. P. (2017). Structural and functional integrity of the intraparietal sulcus in moderate and severe traumatic brain injury. Journal of Neurotrauma, 34, 1473–1481.
Sun, D., Davis, S. L., Haswell, C. C., Swanson, C. A., Mid-Atlantic, M. W., LaBar, K. S., Fairbank, J. A., & Morey, R. A. (2018). Brain structural covariance network topology in remitted posttraumatic stress disorder. Frontiers in Psychiatry / Frontiers Research Foundation, 9, 90.
Tournier, J. D., Calamante, F., & Connelly, A. (2007). Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution. NeuroImage, 35, 1459–1472.
Tournier, J. D., Calamante, F., & Connelly, A. (2013). Determination of the appropriate b value and number of gradient directions for high-angular-resolution diffusion-weighted imaging. NMR in Biomedicine, 26, 1775–1786.
Tournier, J. D., Calamante, F., Gadian, D. G., & Connelly, A. (2004). Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. NeuroImage, 23, 1176–1185.
Tournier, J. D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C. H., & Connelly, A. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 202, 116137.
Tustison, N. J., Avants, B. B., Cook, P. A., Zheng, Y., Egan, A., Yushkevich, P. A., & Gee, J. C. (2010). N4ITK: Improved N3 bias correction. IEEE Transactions on Medical Imaging, 29, 1310–1320.
Veraart, J., Novikov, D. S., Christiaens, D., Ades-Aron, B., Sijbers, J., & Fieremans, E. (2016). Denoising of diffusion MRI using random matrix theory. NeuroImage, 142, 394–406.
Wallace, E. J., Mathias, J. L., & Ward, L. (2018). Diffusion tensor imaging changes following mild, moderate and severe adult traumatic brain injury: A meta-analysis. Brain Imaging and Behavior, 12, 1607–1621.
Yourganov, G., Stark, B., Fridriksson, J., Bonilha, L., & Rorden, C. (2021). Effect of stroke on contralateral functional connectivity. Brain Connectivity, 11, 543–552.
Yu, S., Dai, G., Wang, Z., Li, L., Wei, X., & Xie, Y. (2018). A consistency evaluation of signal-to-noise ratio in the quality assessment of human brain magnetic resonance images. BMC Medical Imaging, 18, 17.
Yuan, W., Treble-Barna, A., Sohlberg, M. M., Harn, B., & Wade, S. L. (2017). Changes in structural connectivity following a cognitive intervention in children with traumatic brain injury. Neurorehabilitation and Neural Repair, 31, 190–201.
Yuan, W., Wade, S. L., & Babcock, L. (2015). Structural connectivity abnormality in children with acute mild traumatic brain injury using graph theoretical analysis. Human Brain Mapping, 36, 779–792.
Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: Identifying differences in brain networks. NeuroImage, 53, 1197–1207.
Zhang, Y., & Burock, M. A. (2020). Diffusion tensor imaging in Parkinson's disease and parkinsonian syndrome: A systematic review. Frontiers in Neurology, 11, 531993.
Acknowledgements
We would like to thank Santa Clara Brain Injury Center and our Veterans for their support to the study.
Funding
This study was supported by War Related Illness and Injury Center (WRIISC) located at VA Palo Alto.
Author information
Authors and Affiliations
Contributions
All authors wrote the main manuscript text and X. K. prepared all figures. All authors reviewed the manuscript.
Corresponding author
Ethics declarations
Competing Interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Kang, X., Yoon, B.C., Grossner, E. et al. Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study. Neuroinform 22, 573–589 (2024). https://doi.org/10.1007/s12021-024-09681-7
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12021-024-09681-7