Magnetization transfer ratio evolution with demyelination and remyelination in multiple sclerosis lesions
Bibliographic record
Abstract
OBJECTIVE: To assess demyelination and remyelination in vivo in acute gadolinium (Gd)-enhancing lesions of multiple sclerosis (MS). METHODS: We measured significant changes in magnetization transfer ratio (MTR) consistent with demyelination and remyelination of individual lesion voxels, as well as the mean normalized MTR over all lesion voxels during and after contrast enhancement, in MS patients participating in a 3-year Canadian trial assessing immunoablation and autologous stem cell transplantation for treatment of MS. RESULTS: The average mean normalized lesion MTR over all lesions exhibited partial recovery over 2 to 4 months after Gd enhancement. Voxel-based analysis demonstrated that approximately 70% of the initially enhancing lesion volume (GdLV) was left with stably low MTR over 39 months of evaluation. The percentage of the GdLV undergoing significant increases in MTR consistent with remyelination increased for approximately 7 months after enhancement and then stabilized at 21 %GdLV. Significant decreases in MTR consistent with demyelination were ongoing for approximately 33 months after enhancement, stabilizing at 9 %GdLV. The estimated error of these measurements, based on scan/rescan analysis, was less than 0.4 %GdLV. INTERPRETATION: We found significant changes in MTR consistent with demyelination and remyelination that followed different temporal evolutions and were ongoing in different lesion regions for at least 3 years after lesion formation.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".