Brain and cord myelin water imaging: a progressive multiple sclerosis biomarker
Bibliographic record
Abstract
OBJECTIVES: Conventional magnetic resonance imaging (MRI) is used to diagnose and monitor inflammatory disease in relapsing remitting (RR) multiple sclerosis (MS). In the less common primary progressive (PP) form of MS, in which focal inflammation is less evident, biomarkers are still needed to enable evaluation of novel therapies in clinical trials. Our objective was to characterize the association - across the brain and cervical spinal cord - between clinical disability measures in PPMS and two potential biomarkers (one for myelin, and one for atrophy, both resulting from the same imaging technique). METHODS: Multi-component driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) MRI of the brain and cervical spinal cord were obtained for 15 PPMS patients and 11 matched controls. Data were analysed to estimate the signal related to myelin water (VFM), as well as volume measurements. MS disability was assessed using the Multiple Sclerosis Functional Composite score, which includes measures of cognitive processing (Paced Auditory Serial Addition Test), manual dexterity (9-Hole Peg Test) and ambulatory function (Timed 25-Foot Walk); and the Expanded Disability Status Scale. RESULTS: Brain and spinal cord volumes were different in PPMS compared to controls, particularly ventricular (+ 46%, p = 0.0006) and cervical spinal cord volume (- 16%, p = 0.0001). Brain and spinal cord myelin (VFM) were also reduced in PPMS (brain: - 11%, p = 0.01; spine: - 19%, p = 0.000004). Cognitive processing correlated with brain ventricular volume (p = 0.009). Manual dexterity correlated with brain ventricular volume (p = 0.007), and both brain and spinal cord VFM (p = 0.01 and 0.06, respectively). Ambulation correlated with spinal cord volume (p = 0.04) and spinal cord VFM (p = 0.04). INTERPRETATION: In this study we demonstrated that mcDESPOT can be used to measure myelin and atrophy in the brain and spinal cord. Results correlate well with clinical disability scores in PPMS representing cognitive, fine motor and ambulatory disability.
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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 | 0.000 | 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) | 0.001 | 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".