Five-year longitudinal changes in quantitative spinal cord MRI in multiple sclerosis
Bibliographic record
Abstract
Background: The spinal cord (SC) is highly relevant to disability in multiple sclerosis (MS), but few studies have evaluated longitudinal changes in quantitative spinal cord magnetic resonance imaging (SC-MRI). Objectives: The aim of this study was to characterize the relationships between 5-year changes in SC-MRI with disability in MS. Methods: In total, 75 MS patients underwent 3 T SC-MRI and clinical assessment (expanded disability status scale (EDSS) and MS functional composite (MSFC)) at baseline, 2 and 5 years. SC-cross-sectional area (CSA) and diffusion-tensor indices (fractional anisotropy (FA), mean, perpendicular, parallel diffusivity (MD, λ ⊥ , λ || ) and magnetization transfer ratio (MTR)) were extracted at C3–C4. Mixed-effects regression incorporating subject-specific slopes assessed longitudinal change in SC-MRI measures. Results: SC-CSA and MTR decreased ( p = 0.009, p = 0.03) over 5.1 years. There were moderate correlations between 2- and 5-year subject-specific slopes of SC-MRI indices and follow-up EDSS scores (Pearson’s r with FA = −0.23 ( p < 0.001); MD = 0.31 ( p < 0.001); λ ⊥ = 0.34 ( p < 0.001); λ || = −0.12 ( p = 0.05), MTR = −0.37 ( p < 0.001); SC-CSA = −0.47 ( p < 0.001) at 5 years); MSFC showed similar trends. The 2- and 5-year subject-specific slopes were robustly correlated ( r = 0.93–0.97 for FA, λ ⊥ , SC-CSA and MTR, all ps < 0.001). Conclusion: In MS, certain quantitative SC-MRI indices change over 5 years, reflecting ongoing tissue changes. Subject-specific trajectories of SC-MRI index change at 2 and 5 years are strongly correlated and highly relevant to follow-up disability. These findings suggest that individual dynamics of change should be accounted for when interpreting longitudinal SC-MRI measures and that measuring short-term change is predictive of long-term clinical disability.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".