Cervical cord myelin water imaging shows degenerative changes over one year in multiple sclerosis but not neuromyelitis optica spectrum disorder
Bibliographic record
Abstract
Spinal cord pathology is a feature of both neuromyelitis optica spectrum disorder (NMOSD) and relapsing-remitting multiple sclerosis (MS). While subclinical disease activity has been described in MS using quantitative magnetic resonance imaging measures, current evidence suggests that neurodegeneration is absent between relapses in NMOSD, although most evidence comes from brain studies. We aimed to assess cross-sectional differences and longitudinal changes in myelin integrity in relapse-free MS and NMOSD subjects over one year. 15 NMOSD, 15 MS subjects, and 17 healthy controls were scanned at 3 T using a cervical cord mcDESPOT protocol. A subset of 8 NMOSD, 11 MS subjects and 14 controls completed follow-up. Measures of the myelin water fraction (f M ) within lesioned and non-lesioned cord segments were collected. At baseline, f M in lesioned and non-lesioned segments was significantly reduced in MS (lesioned: p = 0.002; non-lesioned: p = 0.03) and NMOSD (lesioned: p = 0.0007; non-lesioned: p = 0.002) compared to controls. Longitudinally, f M decreased within non-lesioned cord segments in the MS group (− 7.3%, p = 0.02), but not in NMOSD (+ 5.8%, p = 0.1), while change in lesioned segments f M did not differ from controls' in either patient group. These results suggest that degenerative changes outside of lesioned areas can be observed over a short time frame in MS, but not NMOSD, and support the use of longitudinal myelin water imaging for the assessment of pathological changes in the cervical cord in demyelinating diseases.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".