Myelin-Related Advanced MRI Demonstrates Different Degrees Of Change Between Various White Matter Tracts in MS (S44.004)
Bibliographic record
Abstract
OBJECTIVE: To evaluate 3 quantitative myelin-related MRI measurements for detecting differences between MS patients and healthy controls in various white matter tracts. BACKGROUND: MRI is routinely used to assess myelin changes in MS; advanced MRI sequences can provide tissue specificity and allow quantitative measurements. The magnetisation transfer ratio (MTR) is related to macromolecule content, while the myelin water fraction (MWF) uses relaxation characteristics to isolate the signal from water trapped between the myelin bilayers. Relaxation can also be investigated using steady-state imaging, providing a measure termed myelin volume fraction (MVF). Each metric has different biological influences, sensitivity, noise characteristics and ease of acquisition. DESIGN/METHODS: Fifty-eight relapsing-remitting MS patients participating in a phase III randomised placebo-controlled trial of ocrelizumab were scanned at baseline before treatment initiation. Thirty-four age/gender-matched healthy controls were included. Average MTR, MWF and MVF values were calculated across the whole cerebrum for all normal appearing white matter (NAWM), and for 5 white matter tracts: the corpus callosum (CC), cortical spinal tract (CST), minor forceps (MN), inferior longitudinal fasciculus (ILF), and superior longitudinal fasciculus (SLF). RESULTS: Across all NAWM, significant reductions were found in MTR (1.4%, p=0.001) and MVF (1.9%, p=0.02) for MS compared to healthy controls. MWF showed the largest decrease (4.2%, p=0.09). Across individual tracts, MWF always showed the greatest reductions with a much larger range of changes between structures, but all 3 metrics followed the same pattern showing the greatest decreases in the ILF, followed by the CC, SLF, MN and finally CST. CONCLUSIONS: All 3 myelin-related MRI metrics demonstrate reduction across structures in MS compared to healthy controls. MWF demonstrated the largest decreases and range of differences between structures. MS subjects and controls will be followed over 2 years to monitor myelin health and stability of these advanced imaging metrics, respectively. Study Supported by: F. Hoffmann-La Roche Ltd., Basel, Switzerland.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".