Myelin Water Atlas: A Template for Myelin Distribution in the Brain
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Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Myelin water imaging (MWI) is a magnetic resonance imaging technique that quantifies myelin in-vivo. Although MWI has been extensively applied to study myelin-related diseases in groups, clinical use in individual patients is challenging mainly due to population heterogeneity. The purpose of this study was twofold: (1) create a normative brain myelin water atlas depicting the population mean and regional variability of myelin content; and (2) apply the myelin atlas to assess the degree of demyelination in individuals with multiple sclerosis (MS). METHODS: 3T MWI was performed on 50 healthy adults (25 M/25 F, mean age 25 years [range 17-42 years]). The myelin water atlas was created by averaging coregistered myelin water fraction (MWF) maps from all healthy individuals. To illustrate the preliminary utility of the atlas, white matter (WM) regional MWF variations were evaluated and voxel-wise z-score maps (z < -1.96) from the MWI of three MS participants were produced to assess individually the degree of demyelination. RESULTS: The myelin water atlas demonstrated significant MWF variation across control WM. No significant MWF differences were found between male and female healthy participants. MS z-score maps revealed diffuse regions of demyelination in the two participants with Expanded Disability Status Scale (EDSS) = 2.0 but not in the participant with EDSS = 0. CONCLUSIONS: The myelin water atlas can be used as a reference (URL: https://sourceforge.net/projects/myelin-water-atlas/) to demonstrate areas of demyelination in individual MS participants. Future studies will expand the atlas age range, account for education, and other variables that may affect myelination.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it