18F-Flortaucipir (AV1451) imaging identifies grey matter atrophy in retired athletes
Bibliographic record
Abstract
BACKGROUND: The long-term consequences of concussions may include pathological neurodegeneration as seen in Alzheimer's disease (AD) and chronic traumatic encephalopathy (CTE). Tau-PET showed promise as a method to detect tau pathology of CTE, but more studies are needed OBJECTIVE: This study aimed (1) to assess the association of imaging evidence of tau pathology with brain volumes in retired athletes and (2) to examine the relationship between tau-PET and neuropsychological functioning. METHODS: F]flortaucipir tau-PET, and a neuropsychological battery. Memory composite was created by averaging the Rey Auditory Verbal Learning Test and Rey Visual Design Learning Test z-scores. Grey matter (GM) volumes were age/intracranial volume corrected using normal control MRIs. Tau-PET % positivity in GM was calculated as the number of positive voxels (≥ 1.3 standardized uptake value ratio (SUVR)/total voxels). RESULTS: 47 retired contact sport athletes negative for AD (age:51 ± 14; concussions/athlete:15 ± 2) and 54 normal controls (age:50 ± 13) were included. Tau-PET positive voxels had significantly lower GM volumes, compared to tau-PET negative voxels (- 0.37 ± 0.41 vs. - 0.31 ± 0.37, paired p = .006). There was a significant relationship between GM tau-PET % positivity and memory composite score (r = - .366, p = .02), controlled for age, PET scanner, and PET scan duration. There was no relationship between tau-PET measures and concussion number, or years of sport played. CONCLUSION: A higher tau-PET signal was associated with reduced GM volumes and lower memory scores. Tau-PET may be useful for identifying those at risk for neurodegeneration.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".