Rapid myelin water imaging in human cervical spinal cord
Bibliographic record
Abstract
PURPOSE: relaxation is a quantitative MRI technique that can be used as an in vivo biomarker for myelin in the central nervous system. MWI using a multi-echo spin echo sequence currently takes more than 20 min to acquire eight axial slices (5 mm thickness) in the cervical spinal cord, making spinal cord MWI impractical for implementation in clinical studies. METHODS: In this study, an accelerated gradient and spin echo sequence (GRASE), previously validated for brain MWI, was adapted for spinal cord MWI. Ten healthy volunteers were scanned with the GRASE sequence (acquisition time 8.5 min) and compared with the multi-echo spin echo sequence (acquisition time 23.5 min). RESULTS: Using region of interest analysis, myelin estimates obtained from the two sequences were found to be in good agreement (mean difference = -0.0092, 95% confidence interval = - 0.0092 ± 0.061; regression slope = 1.01, ρ = 0.9). MWI using GRASE was shown to be highly reproducible with an average coefficient of variation of 6.1%. CONCLUSION: The results from this study show that MWI can be performed in the cervical spinal cord in less than 10 min, allowing for practical implementation in multimodal clinical studies. Magn Reson Med 78:1482-1487, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".