Reproducibility of <i>in vivo</i> magnetic resonance imaging–based measurement of myelin water
Bibliographic record
Abstract
PURPOSE: To evaluate the reproducibility of multicomponent quantitative T(2) (QT2) measurements, in particular the myelin water fraction (MWF), to determine the sensitivity of this method for monitoring myelin changes in longitudinal studies and to provide a basis for correctly powering such studies. MATERIALS AND METHODS: The de facto standard 32-echo spin-echo imaging sequence was used throughout, and data were analyzed using regularized non-negative least squares (NNLS) to produce T(2) distributions. Three studies were conducted in healthy subjects. First, two acquisition protocols were compared in 10 subjects. Second, variability of QT2 was evaluated over same-day scan-rescan experiments in 6 subjects. Finally, variability was quantified in a longitudinal study of 5 subjects. RESULTS: A within-subject coefficient of variation (CoV) of 12% (range 4-25%) was observed for the MWF in brain white matter (WM) regions of interest (ROIs). The geometric mean T(2) was more stable, with a longitudinal CoV of 4% (range 1-6%). The choice of the geometry and repetition time of the acquisition protocol influenced the estimates of the MWF and T(2) values. The choice of integration range for the short-T(2) component had a significant effect on MWF estimates, but not on reproducibility. CONCLUSION: The reproducibility of QT2 measurements using existing methods is moderate and the method can be used in longitudinal studies, with careful consideration of the methodologic variability and an appropriate group size.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".