Reliability of Central Vein Sign Imaging With 3T FLAIR* in a Multicenter Study
Bibliographic record
Abstract
ABSTRACT Background and Purpose The central vein sign (CVS) is a diagnostic imaging biomarker for multiple sclerosis (MS). FLAIR* is a combined MRI contrast that provides high conspicuity for CVS at 3 Tesla (3T), enabling its sensitive and accurate detection in clinical settings. This study evaluated whether CVS conspicuity of 3T FLAIR* is reliable across imaging sites and MRI vendors and whether gadolinium (Gd) contrast increases CVS conspicuity. Methods A cross‐sectional, multicenter study recruited adults referred for possible diagnosis of MS at 10 sites. FLAIR* contrast was generated using high‐resolution T2*‐weighted (acquired pre‐ and post‐injection of Gd) and T2‐weighted fluid‐attenuated inversion recovery (T2‐FLAIR) brain images at 3T from two MRI vendors. Lesions and veins were segmented to compute lesion‐to‐vein contrast‐to‐noise ratio (CNR lesion‐to‐vein ), a quantitative measure of CVS conspicuity. CNR lesion‐to‐vein measures for pre‐ and post‐Gd FLAIR* were compared across sites and vendors. Results Eighty‐seven participants from nine sites were included in the analysis. There was no significant difference in mean CNR lesion‐to‐vein between sites for pre‐Gd ( p ‐value = 0.07) or post‐Gd ( p ‐value = 0.27) FLAIR*. There were also no significant differences between vendors for pre‐Gd ( p ‐value = 0.10) or post‐Gd ( p ‐value = 0.31) FLAIR*. Patient‐level pairwise differences in CNR lesion‐to‐vein between pre‐Gd and post‐Gd FLAIR* revealed a significant increase for post‐Gd FLAIR* ( p ‐value < 0.001). Conclusions CVS conspicuity on 3T FLAIR* is consistent across imaging sites and MRI vendors. Moreover, Gd‐based contrast agent significantly improved CVS conspicuity on 3T FLAIR*. These findings support the implementation of FLAIR* in clinical settings for 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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".