Changes in volumetric and metabolic parameters relate to differences in exposure to sub-concussive head impacts

Abstract

Structural and calibrated magnetic resonance imaging data were acquired on 44 collegiate football players prior to the season (PRE), following the first four weeks in-season (PTC) and one month after the last game (POST). Exposure data collected from g-Force accelerometers mounted to the helmet of each player were used to split participants into HIGH (N = 22) and LOW (N = 22) exposure groups, based on the frequency of impacts sustained by each athlete. Significant decreases in grey-matter volume specific to the HIGH group were documented at POST (P = 0.009), compared to baseline. Changes in resting cerebral blood flow (CBF₀), corrected for partial volume effects, were observed within the HIGH group, throughout the season (P < 0.0001), suggesting that alterations in perfusion may follow exposure to sub-concussive collisions. Co-localized significant increases in cerebral metabolic rate of oxygen consumption (CMRO₂|₀) mid-season were also documented in the HIGH group, with respect to both PRE- and POST values. No physiological changes were observed in the LOW group. Therefore, cerebral metabolic demand may be elevated in players with greater exposure to head impacts. These results provide novel insight into the effects of sub-concussive collisions on brain structure and cerebrovascular physiology and emphasize the importance of multi-modal imaging for a complete characterization of cerebral health.

Keywords: Brain structure; cerebral blood flow; cerebral metabolism; dual-calibrated fMRI; sub-concussive impacts.

Figure 1.

Schematic timeline of the study visits throughout the two seasons during which longitudinal data was collected. The timeline of the study design shows when subjects completed magnetic resonance imaging (MRI) with respect to the timing of the season; prior to training camp (PRE), following training camp and two season games (PTC), and one month following the last playoff game of the season (POST).

Figure 2.

Example of the effects of the respiratory manipulations on perfusion and blood oxygen level-dependent signals in a representative participant. (a) The continuous trace (light blue) for P_CO2 (top) and P_O2 (bottom) sampled from the RA-MR™ (Thornhill Research Inc., Toronto, ON) are shown for both breathing manipulations. The end-tidal values for CO₂ (P_ETCO₂; navy filled circles) and O₂ (P_ETO₂; red filled circles) are also highlighted. The P_ETCO₂ was targeted at 10 mmHg above the subject’s baseline during hypercapnia. The P_ETO₂ was targeted at 300 mmHg during hyperoxia. (b) Mean cerebral blood flow (CBF) maps for each period of the respiratory challenges (baseline, stimulus, recovery) shown in the subject’s native space. (c) Mean grey-matter relative change in blood level oxygen dependent (BOLD) signal during each breathing manipulation over time.

Figure 3.

Data-informed grouping of the participants based on helmet accelerometer biometrics. (a) The LOW (N = 22) and HIGH (N = 22) groups were defined based on the average daily exposure to sub-concussive impacts (per session) having a linear acceleration of 15 g and above. Both practices and games were recorded for each participant and were used to characterize their exposure per session. The median (red dotted line; median = 9.21 head impacts per session) was used as the thresholding parameter. (b) The number of impacts per session for each location was compared between the groups showing that the HIGH exposure recorded higher counts of impacts on all sides of the helmet. *P < 0.05 for a univariate ANOVA.

Figure 4.

Significant clusters for the interaction between exposure and time on the volumetric data. Voxelwise two-by-three ANOVA corrected at P < 0.05 for multiple comparisons (minimum cluster size 148.6 voxels) revealed widespread significant differences in grey-matter volume based on the interaction between exposure and time. Coronal (a), sagittal (b), and axial (c) slices of the statistical results are overlaid on the symmetric grey-matter template derived from the group data. The template was normalized to the 2 mm Montréal Neurological Institute (MNI) 2 mm atlas.

Figure 5.

Significant results for the interaction between time and exposure in the voxelwise and region-of-interest analyses of the hemodynamic parameters. (a) Significant cluster from the voxelwise analysis of the baseline cerebral blood flow (CBF₀) with partial volume correction adjusted for multiple comparisons at P < 0.05 (minimum cluster size = 1324 voxels) showing the interaction between time and exposure. The statistical map is overlaid onto the freesurfer surface to show lateral, medial, superior and inferior views from the left (LH) and right (RH) hemispheres. (b) Post-hoc results showing mean (±standard deviation) regional CBF₀ (top), resting oxygen extraction fraction (OEF₀), and cerebral metabolic rate of oxygen consumption (CMRO_2|0) extracted for each exposure group (LOW = dark grey, HIGH = light grey) and time point (PRE, PTC, POST) within the significant cluster identified in (a). Time-varying end-tidal CO₂ was controlled for in the analysis of CBF₀ and OEF₀. The red asterisk represents parameters (e.g. CBF₀ and CMRO_2|0) that showed a significant interaction between time and exposure. *P < 0.05; **P < 0.001; N.S. = not significant.