7T MRI Versus 3T MRI of the Brain in Professional Fighters and Patients With Head Trauma
Bibliographic record
Abstract
Many studies have investigated the imaging sequelae of repetitive head trauma with mixed results, particularly with regard to the detection of intracranial white matter changes (WMCs) and cerebral microhemorrhages (CMHs) on ≤3 Tesla (T) field magnetic resonance imaging (MRI). 7T MRI, which has recently been approved for clinical use, is more sensitive at detecting lesions associated with multiple neurological diagnoses. In this study, we sought to determine whether 7T MRI would detect more WMCs and CMHs than 3T MRI in 19 professional fighters, 16 patients with single TBI, versus 82 normal healthy controls (NHCs). Fighters and patients with TBI underwent both 3T and 7T MRI; NHCs underwent either 3T ( n = 61) or 7T ( n = 21) MRI. Readers agreed on the presence/absence of WMCs in 88% (84 of 95) of 3T MRI studies (Cohen's kappa, 0.76) and in 93% (51 of 55) of 7T MRI studies (Cohen's kappa, 0.79). Readers agreed on the presence/absence of CMHs in 96% (91 of 95) of 3T MRI studies (Cohen's kappa, 0.76) and in 96% (54 of 56) of 7T MRI studies (Cohen's kappa, 0.88). The number of WMCs detected was greater in fighters and patients with TBI than NHCs at both 3T and 7T. Moreover, the number of WMCs was greater at 7T than at 3T for fighters, patients with TBI, and NHCs. There was no difference in the number of CMHs detected with 7T MRI versus 3T MRI or in the number of CMHs observed in fighters/patients with TBI versus NHCs. These initial findings suggest that fighters and patients with TBI may have more WMCs than NHCs and that the improved voxel size and signal-to-noise ratio at 7T may help to detect these changes. As 7T MRI becomes more prevalent clinically, larger patient populations should be studied to determine the cause of these WMCs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".