Longitudinal MR Imaging of Iron in Multiple Sclerosis: An Imaging Marker of Disease
Bibliographic record
Abstract
PURPOSE: To investigate the relationship between magnetic resonance (MR) imaging markers of iron content and disease severity in patients with multiple sclerosis (MS) over a 2-year period. MATERIALS AND METHODS: This prospective study was approved by the local ethics committee, and written informed consent was obtained from all participants. Seventeen patients with MS and 17 control subjects were examined twice, 2 years apart, by using phase imaging and transverse relaxation (R2*) mapping at 4.7 T. Quantitative differences in iron content in deep gray matter between patients and control subjects were evaluated with repeated-measures multivariate analysis of variance separately for R2* mapping and phase imaging. Multiple regression analysis was used to evaluate correlations of MR imaging measures, both 2-year-difference and single-time measurements, to baseline disease severity. RESULTS: R2* mapping using 2-year-difference measurements had the highest correlation to disease severity (r = 0.905, P < .001) compared with R2* mapping using single-time measurements (r = 0.560, P = .019) and phase imaging by using either single-time (r = 0.539, P = .026) or 2-year-difference (r = 0.644, P = .005) measurements. Significant increases in R2* occur during 2 years in the substantia nigra (P < .001) and globus pallidus (P = .035), which are both predictors of disease in regression analysis, in patients compared with control subjects. There were group differences in the substantia nigra, globus pallidus, pulvinar thalamus, thalamus, and caudate nucleus, compared with control subjects with R2* mapping (P < .05), and group differences in the caudate nucleus and pulvinar thalamus, compared with control subjects with phase imaging (P < .05). CONCLUSION: There are significant changes in deep gray matter iron content in MS during 2 years measured with MR imaging, changes that are strongly related to physical disability. Longitudinal measurements may produce a higher correlation to disease severity compared with single-time measurements because baseline iron content of deep gray matter is variable among subjects.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".