Limited utility of adding 3T cervical spinal cord MRI to monitor disease activity in multiple sclerosis
Bibliographic record
Abstract
Background: Performing routine brain magnetic resonance imaging (MRI) is widely accepted as the standard of care for disease monitoring in multiple sclerosis (MS), but the utility of performing routine spinal cord (SC) MRI for this purpose is still debatable. Objective: This study aimed to measure the frequency of new isolated cervical spinal cord lesions (CSLs) in people with MS (pwMS) undergoing routine brain and cervical SC-MRI for disease monitoring and determine the factors associated with the development of new CSLs and their prognostic value. Methods: We retrospectively identified 1576 pwMS who underwent follow-up 3T brain and cervical SC-MRI over a 9-month period. MRI was reviewed for the presence of new brain lesions (BLs) and CSLs. Clinical records were reviewed for interval relapses between sequential scans and subsequent clinical relapse and disability worsening after the follow-up MRI. Results: In 1285 pwMS (median interval: 13–14 months) who were clinically stable with respect to relapses, 73 (5.7%) had new CSLs, of which 49 (3.8%) had concomitant new BLs and 24 (1.9%) had new isolated CSLs only. New asymptomatic CSLs were associated with ⩾ 3 prior relapses ( p = 0.04), no disease-modifying therapy (DMT) use ( p = 0.048), and ⩾ 3 new BLs ( p < 0.001); ⩾ 3 new BLs (OR: 7.11, 95% CI: 4.3–11.7, p < 0.001) remained independently associated with new CSLs on multivariable analysis. Having new asymptomatic CSLs was not independently associated with subsequent relapse or disability worsening after the follow-up MRI (median follow-up time of 26 months). Conclusion: Routine brain and cervical SC-MRI detected new isolated CSLs in only < 2% of clinically stable pwMS. Developing new asymptomatic CSLs was associated with concomitant new BLs and did not confer an independent increased risk of relapse or disability worsening. Performing SC-MRI may not be warranted for routine monitoring in most pwMS, and performing only brain MRI may be sufficient to capture the vast majority of clinically silent disease activity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".