Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology
Bibliographic record
Abstract
Various magnetic resonance (MR) techniques are used to study the pathological evolution of demyelinating diseases, such as multiple sclerosis (MS). However, few studies have validated MR derived measurements with histopathology. Here, we determine the correlation of myelin water imaging, an MR measure of myelin content, with quantitative histopathologic measures of myelin density. The multi-component T2 distribution of water was determined from 25 formalin-fixed MS brain samples using a multi-echo T2 relaxation MR experiment. The myelin water fraction (MWF), defined as T2 signal below 30 milliseconds divided by the total signal, was determined for various regions of interest and compared to Luxol fast blue (myelin stain) mean optical density (OD) for each sample. MWF had a strong correlation with myelin stain [mean (range) R2 = 0.67 (0.45-0.92)], validating MWF as a measure of myelin density. This quantitative technique has many practical applications for the in vivo monitoring of demyelination and remyelination in a variety of disorders of myelin.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".