Acute and Chronic Changes in Diffusivity Measures after Sports Concussion
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Bibliographic record
Abstract
Despite negative neuroimaging findings in concussed athletes, studies indicate that the acceleration and deceleration of the brain after concussive impacts result in metabolic and electrophysiological alterations that may be attributable to changes in white matter resulting from biomechanical strain. In the present study we investigated the effects of sports concussion on white matter using three different diffusion tensor imaging (DTI) measures: fractional anisotropy (FA), mean diffusivity (MD), and axial diffusivity (AD). We compared a group of 10 non-concussed athletes with a group of 18 concussed athletes of the same age (mean age 22.5 years) and education (mean 16 years) using a voxel-based approach (VBA) in both the acute and chronic post-injury phases. All concussed athletes were scanned 1-6 days post-concussion and again 6 months later in a 3T Siemens Trio(™) MRI. Three 2×2 repeated-measures analyses of variance (ANOVAs) were conducted, one for each measure of DTI used in the current study. There was a main group effect of FA, which was increased in dorsal regions of both corticospinal tracts (CST) and in the corpus callosum in concussed athletes at both time points. There was a main group effect of AD in the right CST, where concussed athletes showed elevated values relative to controls at both time points. MD values were decreased in concussed athletes, in whom analyses revealed significant group differences in the CST and corpus callosum at both time points. Although the use of VBA does limit the analyses to large tracts, and it has clinical limitations with regard to individual analyses, our results nevertheless indicate that sports concussions do result in changes in diffusivity in the corpus callosum and CST that are not detected using conventional neuroimaging techniques.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it