Quantitative magnetization transfer and myelin water imaging of the evolution of acute multiple sclerosis lesions
Bibliographic record
Abstract
Quantitative magnetization transfer imaging provides in vivo estimates of liquid and semisolid constituents of tissue, while estimates of the liquid subpopulations, including myelin water, can be obtained from multicomponent T(2) analysis. Both methods have been suggested to provide improved myelin specificity compared to conventional MRI. The goal of this study was to investigate the sensitivity of each technique to the progression of acute, gadolinium-enhancing regions of multiple sclerosis. Magnetization transfer and T(2) relaxometry data were acquired longitudinally over the course of 1 year in five relapsing-remitting multiple sclerosis patients and in five healthy controls. Parametric maps were analyzed in enhancing lesions and normal-appearing white matter regions. Quantitative magnetization transfer parameters in lesions were most abnormal at the time of enhancement and followed a pattern of recovery over subsequent months. Lesion myelin water fraction was abnormal but did not show a significant trend over time. Quantitative magnetization transfer was able to track the degree and timing of the partial recovery in enhancing multiple sclerosis lesions in a small group of patients, while the recovery was not detected in myelin water estimates, possibly due to their large variability. Our data suggest the recovery is characterized by quick resolution of inflammation and a slower remyelination process.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".