P.172 Diffusion MRI characteristics change in select cerebral white matter tracts after decompressive surgery for degenerative cervical myelopathy
Bibliographic record
Abstract
Background: Degenerative cervical myelopathy is characterized by progressive compression of the spinal cord resulting in debilitating loss of dexterity, independent ambulation, and sphincter control. Diffusion tensor imaging (DTI) has shown that, compared to healthy controls, myelopathy patients have decreased integrity of the corticospinal tracts and corpus callosum (Bernabeu-Sanz et al, 2020). Methods: Twenty-six myelopathy patients consented to cerebral diffusion tensor imaging (3 Tesla, 32 directions, b=1000) preoperatively, as well as 6-weeks, 12-weeks, and 6-months postoperatively. Average mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were measured in the corticospinal tracts, forceps major, and forceps minor. Results: Both MD and RD decreased from 6-12 weeks postoperatively in the right corticospinal tract. The forceps major of the corpus callosum showed an initial postoperative increase in MD followed by a subsequent increase in FA and decrease in RD 3-6 months postoperatively. The AD of the forceps major increased both immediately and 3-6 months postoperatively. Conclusions: Changes in microstructural integrity of the corticospinal tract and forceps major over the postoperative recovery period suggest a pattern of recovery in myelopathy patients. This study is the first to report postoperative DTI changes in myelopathy-relevant white matter tracts in the brain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".