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Structural brain connectivity network alterations following mild traumatic brain injury1Turku Brain and Mind Center, University of Turku, Turku, Finland, 2Department of Neurology, University of Turku, Turku, Finland, 3Division of Clinical Neurosciences, Traumatic Brain Injury Centre, Turku University Hospital, Turku, Finland, 4Turku PET Centre, Turku University Hospital, Turku, Finland, 5Department of Radiology, University of Turku, Turku, Finland
Synopsis
We used graph theoretical analysis to investigate structural brain connectivity networks in mild traumatic brain injury (mTBI). Global and local measures of structural connectivity were investigated in acute/sub-acute and chronic phases after TBI. There were no statistically significant differences in the global network measures between patients and controls at either of the stages after TBI. Node-level differences were found between patients and controls in local efficiency, strength, and betweenness centrality in several brain regions. However, only betweenness centrality in the right pars opercularis endured the Bonferroni correction for multiple comparisons.
INTRODUCTION
Traumatic brain injury (TBI) is a global public health burden with more than 50 million new cases each year (1), more than 90% of which are considered to be mild (mTBI)(2). TBI often results in cognitive and behavioral dysfunction, hence disrupting the normal functioning of the patients (1). Conventional neuroimaging methods often fail to show the subtle changes in the brain due to lack of sensitivity (3). Diffusion-weighted (DW) MRI is capable of detecting the subtle microstructural abnormalities associated with mTBI (4). Most of the studies, which have investigated these changes are based on diffusion parameters extracted from DW-MR images. However, it is shown that due to the heterogeneity of mTBI, modeling the brain networks could better characterize brain’s complex topology and regional connectivity (5). In this study, we investigated structural brain network alterations in patients with mTBI.METHODS
We investigated 85 patients with mTBI (47±20 years) and 30 orthopedic trauma controls (50±20 years) in this study. All subjects underwent MRI with Siemens Magnetom Verio 3T (Siemens Healthcare, Erlangen, Germany). T1-weighted and DW-MRI data were acquired using MPRAGE and echo-planar imaging sequences, respectively. Sixty-four gradient directions with a b-value of 1000 were used for the acquisition of the DW images. In addition, one b=0 s/mm2 image was also acquired. The DW-MR images were preprocessed by correcting for bias field, subject motion, eddy current induced, and echo planar imaging distortions by using MRtrix3 (6) and FSL (7). T1-weighted images were then nonlinearly co-registered to the DW images. Fiber orientations were then estimated by using constrained spherical deconvolution (CSD) and probabilistic tractography was performed in MRtrix3. Ten million anatomically feasible streamlines were generated to obtain whole brain tractograms (8). T1-weighted images were parcellated with FreeSurfer by using the Desikan-Killiany atlas (9). As a result, 84 gray matter areas were extracted and used as nodes of the structural brain networks, and the number of streamlines was used as an edge weight (Figure 1). Finally, graph theoretical analysis was performed by using Brain Connectivity Toolbox (10) and in-house MATLAB scripts to investigate global and local network differences between the groups. Seven global network measures (betweenness centrality (BC), normalized clustering coefficient, normalized global efficiency, normalized characteristics path length, small-worldness, degree, and strength) and three local network measures (BC, local efficiency, and strength) were investigated. Statistical analysis was performed using IBM SPSS (version 23, SPSS IBM, New York, NY) and a confidence interval of 95% was used to assess the significance of the results. Age and gender were used as covariates in the statistical analyses. Results were then corrected for multiple comparisons by using Bonferroni correction.RESULTS
No significant differences were found in the global network measures between patients and controls at either of the stages after the injury. Several areas were found to have significant differences between patients and controls at both acute/sub-acute and chronic stage in all of the local network properties (Tables 1 and 2). However, only the right pars opercularis (p<0.00059) remained significant after the Bonferroni correction for multiple comparisons, as shown in Figure 2, and only at the chronic stage of TBI.DISCUSSION
Our results indicate that the organization of the structural brain connectivity network was altered only regionally but not at a global level. Local network differences were observed both at acute/sub-acute and chronic stages. Right pars opercularis, left caudal middle frontal, and right caudate were affected at both stages of TBI indicating that network changes persist months after injury.CONCLUSION
Our results show alterations in brain connectivity after an mTBI, which may well be an explanation for the cognitive deficits frequently seen in these patients.Acknowledgements
T.R. received funding from the Emil Aaltonen Foundation (Finland), the Finnish Cultural Foundation (Finland), and Maud Kuistila Memorial Foundation (Finland). M.M received funding from the University of Turku graduate school.References
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