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Low-Magnitude Hits Matter: Single-Season Longitudinal DTI Study on Asymptomatic High School Football Players1School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States, 2School of Mechanical Engineering, Purdue University, West Lafayette, IN, United States, 3Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, MA, United States, 4Institute for Aging Research Instructor in Medicine, Harvard Medical School, Boston, MA, United States, 5Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States, 6Department of Basic Medical Sciences, Purdue University, West Lafayette, IN, United States, 7Department of Health and Kinesiology, Purdue University, West Lafayette, IN, United States
Synopsis
The potential consequences of repeated low-magnitude head acceleration events (
INTRODUCTION
Although many studies have reported that the immense impacts on the head disrupt the white matter integrity, the potential consequences of repeated low-magnitude head acceleration events (HAEs) have been less frequently investigated. In this retrospective study, we examine the hypotheses that athletes who experience repetitive HAEs will exhibit greater changes in diffusivity than athletes who do not and that low-magnitude HAEs will affect the integrity of the white matter.METHODS
1) Participants: 181 high school-aged male athletes participating in American Football (N=162) or non-collision-sports (N=19) underwent multiple MRI sessions including diffusion-weighted imaging (DWI). Football athletes (FBA; N=150) who participated in at least four MRI sessions within a season and non-collision-sport athletes (NCA; N=19) who did at least two were evaluated. See Figure 1 for participation schedule and Figure 2 for demographics.
2) Head Acceleration Event Monitoring: All FBA were monitored for HAEs during all team practices and games to assess mechanical loading on the head. See Figure 3 for a summary of HAE counts.
3) DWI Acquisition: MRI was conducted using a 16ch brain array on a 3T GE Signa HDx. DWI were acquired using a spin-echo echo-planar-imaging sequence (TR/TE=12,000/83.6ms; matrix=96x96; FOV=24cm; 46 axial-slices; 2.5mm isotropic resolution) with 30 diffusion gradient directions at b=1000s/mm2 and one volume acquired without a diffusion gradient.
4) Image Processing: Image processing was performed based using FSL 5.0 toolbox and tract-based spatial statistics (TBSS)1-2. After correcting for motion and eddy current-induced distortions3, steps performed included segmentation, tensor fitting, co-registration, and mean WM skeleton generation. Finally, subject-level fractional anisotropy (FA) and mean diffusivity (MD) maps were generated.
5) Analysis: Individual subject changes during and after exposure to HAEs were obtained through subject-specific quantification of the extent of significantly-increased/decreased FA (or MD) values. First, for voxels in which the distribution of changes in FA (or MD) passed the Shapiro-Wilk test for normality, a 95% confidence interval (CI) was constructed from the NCA pool based on FA (or MD) changes observed at Retest relative to Test. Second, “signed change masks” -- i.e., roi_ΔFA+j,i, roi_ΔFA-j,i, roi_ΔMD+j,i, roi_ΔMD-j,i, where for j∈FBA: i∈{Pre, In1, In2, Post}; and for j∈NCA: i∈{Test, Retest} – were created for each athlete (FBA and NCA) at each follow-up session (FBA: In1, In2, and Post; NCA: Retest), through identification of those voxels for which the change in FA (or MD), relative to Pre (or Test), fell outside the corresponding voxel-specific NCA 95% CI. For each of the signed change masks, the percentage volumes (of the white matter) exhibiting change were compared across the FBA and NCA pools using an unpaired t-test (or Wilcoxon rank-sum test for non-normal cases). To evaluate the effect of low-magnitude head impacts, for all change masks, linear regression analyses were conducted on the volume exhibiting change at each FBA follow-up session, relative to the “to-date” HAE count (in practices and games) exceeding a given peak linear acceleration (PLA) threshold, Th∈{20g, 30g, …, 70g}. For each regression, confidence bands were determined, and Pearson correlation analyses were conducted.
RESULTS
At all follow-up sessions, FBA exhibited significantly (p<0.001) greater volumes of significant increase/decrease in FA and MD compared to NCA. The evaluation of the effect of low-magnitude hits revealed that the regression with the counts of HAEs exceeding 20g had the strongest association with the FA/MD change volumes as opposed to higher magnitudes (Figure 4). The number of HAEs exceeding 20g PLA were significantly associated with the volume of decreased FA (p<0.001) and increased MD (p<0.05) (Figure 5).DISCUSSION
Retrospective examination of diffusion-weighted-imaging data collected longitudinally from male high school athletes was used to examine the hypotheses that athletes who experience repetitive HAEs will exhibit greater changes in diffusivity than athletes who do not experience repetitive HAEs and that low-magnitude HAEs will affect the integrity of the white matter. Examination of brain volumes exhibiting changes in FA and MD during/after a football season revealed appreciably greater volumes of changed FA and MD than NCA who did not experience HAEs from their sport. The next analysis showed that not only high-magnitude-HAEs but also low-magnitude-HAEs have an effect on the change of WM integrity. Critically, the extent of change volumes in the football athletes exhibiting decreased FA or increased MD consistently grew throughout the course of the season and persisted for several months after cessation of exposure to HAEs.CONCLUSSION
The findings suggest an appreciable potential for long-term accumulation of altered white matter physiology with extended participation in collision-based sports. Ultimately, this study supports heightened public concern for athletes who begin and continue participation in collision-based sports during periods of rapid brain development4.Acknowledgements
No acknowledgement found.References
1. Smith, Stephen M., Mark Jenkinson, Heidi Johansen-Berg, Daniel Rueckert, Thomas E. Nichols, Clare E. Mackay, Kate E. Watkins et al. "Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data." Neuroimage 31, no. 4 (2006): 1487-1505.
2. Smith, Stephen M., Mark Jenkinson, Mark W. Woolrich, Christian F. Beckmann, Timothy EJ Behrens, Heidi Johansen-Berg, Peter R. Bannister et al. "Advances in functional and structural MR image analysis and implementation as FSL." Neuroimage 23 (2004): S208-S219.
3. Andersson, J. L., and Sotiropoulos, S. N. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage. 2016; 125, 1063-1078.
4. Stamm, Julie M., Alexandra P. Bourlas, Christine M. Baugh, Nathan G. Fritts, Daniel H. Daneshvar, Brett M. Martin, Michael D. McClean, Yorghos Tripodis, and Robert A. Stern. "Age of first exposure to football and later-life cognitive impairment in former NFL players." Neurology 84, no. 11 (2015): 1114-1120.
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