A quantitative measure of choroid plexus contrast enhancement strongly relates to markers of diffuse brain tissue injury in multiple sclerosis
Bibliographic record
Abstract
Abstract Objective Recent studies suggest that disruptions of the blood–cerebrospinal fluid barrier within the choroid plexus (ChP) may contribute to MS pathogenesis. We investigated the relationship between a quantitative marker of ChP enhancement and markers of focal and diffuse brain tissue injury in multiple sclerosis (MS). Methods 34 MS participants underwent 7T MRI including MP2RAGE-based qT1 mapping pre- and post-contrast, and FLAIR acquisitions. “Delta T1” (ΔT1) maps were calculated by subtraction of post-contrast from co-registered pre-contrast qT1 maps. ChP, white matter lesions (WML), normal-appearing white matter (NAWM) and grey matter (GM) were segmented. Linear regression analyses were conducted between mean ΔT1 values of ChP and (1) WML volume, (2) pre-Gd mean qT1 of WML, (3) pre-Gd mean qT1 of NAWM, and (4) pre-Gd mean qT1 of GM. Results ΔT1 of ChP was significantly associated with pre-Gd qT1 of NAWM (β =0.20, R 2 = 0.54, p<0.001) and GM (β = 0.32, R 2 = 0.62, p<0.001). No significant associations were found between ChP ΔT1 and WML volume (p = 0.3) or WML qT1 (p = 0.05). Interpretation The strong associations we observed between the degree of ChP contrast enhancement and markers of diffuse brain tissue injury, combined with a lack of a relationship with lesion volume or qT1 within lesions, support the hypothesis that entry of toxic factors into the CSF via the ChP may constitute an additional mechanism of brain tissue injury distinct from the classic lesion-based pathology of MS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".