Computational protocol: The Effects of External Jugular Compression Applied during Head Impact Exposure on Longitudinal Changes in Brain Neuroanatomical and Neurophysiological Biomarkers: A Preliminary Investigation

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Protocol publication

[…] Diffusion tensor imaging data were processed with the Functional MRI of the Brain (FMRIB) Software Library (FSL) software package (www.fmrib.ox.ac.uk/fsl). In FSL, skull stripping was performed using the brain extraction tool (BET) function. Eddy current and head motion artifact were corrected in FSL by aligning diffusion weighted images to the first b0 image with an affine transformation with 12 degrees of freedom. The following four commonly used DTI measures were calculated using standard methods: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) (). The tract-based Spatial Statistics (TBSS) approach was used in the image analysis in the present study (). This is a method developed to ameliorate the registration error at the boundary of narrow WM fiber bundles, a common source of error in voxel-based style analysis. Studies have shown that TBSS can effectively reduce the granularity and improve accuracy during the normalization. We followed standard TBSS analysis steps summarized briefly as follows: (1) after DTI scalar maps were generated, FA maps from all subjects were first aligned via a non-linear transformation to determine a target image that was closest to the mean of the FA maps in the study; (2) the target image was aligned to Montreal Neurological Institute (MNI) space using affine registration; (3) individual FA map was registered into the MNI space based on the combined transformation; (4) all the aligned FA maps were averaged to generate a mean FA and then thresholded at FA > 0.2 to create a mean FA skeleton, which represented the WM tracts most common to all the subjects; (5) FA maps from individual subjects were projected onto the skeleton with the FA values determined via a special algorithm for local maximum FA; and (6) the MD, AD, and RD maps were projected to the skeleton using the TBSS_non_FA function in FSL based on the same overall transformation as calculated in the processing of FA maps. The group statistical analysis was conducted only in the WM skeleton with the individual projected DTI maps as input and the skeleton as mask, thus restricting the analysis to determine the major WM tracts that are common to all subjects. In association with the current study, we explored the potential physiological effects of exercise and time on DTI measures in the absence of head impact exposure. To evaluate the stability of DTI measures, we captured a sub-sample of matched athletes from the same school competing in track and field. The track athletes were assessed using identical MR sequences to the current sample of hockey periods over a similar time period (data not shown). The results indicated no significant changes in DTI measures, for the specific DTI outcome measured, between baseline and follow-up. […]

Pipeline specifications

Software tools FSL, BET
Application Magnetic resonance imaging
Diseases Lymphoma, Non-Hodgkin, Nerve Compression Syndromes, Cerebrovascular Trauma, Radial Neuropathy