Multicenter measurements of myelin water fraction and geometric mean T<sub>2</sub>: Intra‐ and intersite reproducibility
Bibliographic record
Abstract
PURPOSE: To assess the reproducibility of myelin water fraction (MWF) and geometric mean T2 (GMT2 ), which are in vivo markers of pathological changes underlying disability and progression in diseases such as multiple sclerosis. MATERIALS AND METHODS: Five healthy volunteers were scanned twice within 24 hours at six different sites using the same manufacturer's 3T magnetic resonance (MR) system. T2 distributions were produced by fitting multiecho 3D T2 data using non-negative least squares, with stimulated echo correction. MWF, the fraction of signal with T2 between 15 and 40 msec to the entire signal, and GMT2 , the mean T2 on a logarithmic scale from T2 between 40 and 200 msec, were examined in white matter. RESULTS: Intrasite coefficients of variation (COVs) were low (mean 3.99% for MWF and 0.51% for GMT2 ), as were intersite COVs (mean 4.68% for MWF, 0.31% for GMT2 ). Scan-rescan intraclass correlation coefficients (ICCs) (0.76 for MWF and 0.93 for GMT2 ) and Bland-Altman plots indicated good agreement between single site scans. Intersite ICCs were relatively high (0.69 for MWF and 0.92 for GMT2 ), revealing good intersite reliability. CONCLUSION: MWF and GMT2 measures are reproducible between scans and across sites with an equivalent MR scanner and sequence protocol. Multicenter clinical trials using quantitative T2 relaxation are feasible.
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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 | 0.002 | 0.002 |
| 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 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".