Biomarkers
Bibliographic record
Abstract
BACKGROUND: Perivascular spaces (PVS), when enlarged, become visible and quantifiable on brain magnetic resonance images (MRI). PVS visibility in MRI has been found to be associated with ageing, hypertension, sleep disorders, and cerebral small vessel disease, but their relationship with cognition in adults remains unclear. METHOD: Here, we aimed to determine whether PVS volumes were associated with cognitive performance, using MRI and cognitive data from 14 different cohorts on ageing, dementia, and cerebrovascular disease. We computationally segmented PVS and estimated PVS volumes within the basal ganglia (BG-PVS) and cerebral white matter, primarily including the centrum semiovale (CSO-PVS) regions-of-interest. We then performed cross-sectional and longitudinal meta-analyses, both accounting for random effects. The cross-sectional meta-analysis employed a linear mixed model to relate PVS volumes to cognitive performance scores (Montreal Cognitive Assessment, MoCA or, Toronto Cognitive Assessment, TorCA) divided by the maximum in each cohort. The longitudinal meta-analysis used logistic regression to predict cognitive status, either remaining cognitively normal or developing impairment over time, from PVS volumes as a percentage in the respective regions-of-interest. RESULT: Cross-sectional meta-analysis (n = 17771). Individuals with higher fractional PVS volumes had lower cognitive performance scores. This observation was consistent across multiple studies and remained significant after adjusting for age, sex, white matter hyperintensities, and years of education. A 10% change in CSO-PVS volume would estimate a 2% reduction in cognitive score. Longitudinal meta-analysis (n = 2447). Higher fractional PVS volumes tended to predict a greater likelihood of any cognitive impairment, although this relationship varied according to the participant populations (healthy aging, stroke, memory clinic) and/or other long-term brain changes (e.g., atrophy, worsening WMH), and variation in duration of follow-up. CONCLUSION: The volume of MRI-visible PVS impacts ageing, vascular or neurogenerative processes leading to cognitive decline. More longitudinal data are needed to confirm the association. Other PVS measures should be assessed as these may be more sensitive to cognitive decline.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".