Spin echo transverse relaxation and atrophy in multiple sclerosis deep gray matter: A two-year longitudinal study
Bibliographic record
Abstract
BACKGROUND: Deep gray matter (DGM) is affected in relapsing-remitting multiple sclerosis (RRMS) and may be studied using short-term longitudinal MRI. OBJECTIVE: To investigate two-year changes in spin-echo transverse relaxation rate (R2) and atrophy in DGM, and its relationship with disease severity in RRMS patients. METHODS: Twenty six RRMS patients and 26 matched controls were imaged at 4.7 T. Multiecho spin-echo R2 maps and atrophy measurements were obtained in DGM at baseline and two-year follow-up. Differences between MRI measures and correlations to disease severity were examined. RESULTS: After two years, mean R2 values in the globus pallidus and pulvinar increased by ~4% (p<0.001) in patients and <1.7% in controls. Two-year changes in R2 showed significant correlation to disease severity in the globus pallidus, pulvinar, substantia nigra, and thalamus. Multiple regression of the two-year R2 difference using these four DGM structures as variables, yielded high correlation with disease severity (r=0.83, p<0.001). Two-year changes in volume and R2 showed significant correlation only for the globus pallidus in multiple sclerosis (MS) (p<0.05). CONCLUSIONS: Two-year difference R2 measurements in DGM correlate to disease severity in MS. R2 mapping and atrophy measurements over two years can be used to identify changes in DGM in MS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".