Associations between MRI-visible perivascular spaces, brain atrophy, white matter hyperintensities, and speeded executive function, in neurodegenerative and cerebrovascular diseases.
Bibliographic record
Abstract
MRI-visible perivascular spaces (PVS) are a neuroimaging feature of cerebral small vessel disease and are commonly observed in patients with cerebrovascular and neurodegenerative disease. However, it is unclear whether PVS burden is associated with cognition. The aim of this study was to investigate the potential associations between PVS volumes, brain atrophy, white matter hyperintensities (WMH), and speeded executive function, in patients from the Ontario Neurodegenerative Disease Research Initiative (ONDRI). ONDRI participants (n=333) clinically diagnosed with Alzheimer's disease/mild cognitive impairment (ADMCI), frontotemporal dementia (FTD), and cerebrovascular diseases (CVD), with clinical, neuropsychological, MRI, plasma biomarkers (glial fibrillary acidic protein (GFAP); neurofilament light, (NfL); p-tau181; Aβ42/40), and available apolipoprotein E epsilon 4 (APOE E4) status, were included in this analysis. MRI-based measurements for brain parenchymal fraction (BPF), lacunes, PVS and WMH were extracted using the ONDRI imaging pipeline. The neuropsychological test scores were standardized (z-transformed), speeded executive function z- scores were computed as the mean of digit symbol modalities test and trail making test part B timed z-scores. The variables selected in bivariate analysis (p<0.2) were introduced in a linear regression model with speeded executive function as the dependent variable, with and without BPF and WMH. To assess the effect of PVS volumes on processing speed through BPF and WMH volumes, a mediation analysis was applied. Speeded executive function was significantly associated with PVS (β=-0.115, p=0.04), GFAP (β standardized effect=-0.231, p=0.002), and the clinical diagnostic cohort (β=-0.160, p=0.004), the adjusted R2 of the model was 0.104 (p<0.001). However, it was not significantly associated with PVS (p=0.691) when BPF and WMH volumes were included in the model, suggesting the relationship was mediated by these factors. In the mediation analysis, the total model effect of PVS on speeded executive function was significant (effect=-0.1067, p=0.042), due to an indirect effect of PVS, mediated by BPF (effect=-0.0718) and WMH (effect=-0.0256). Our preliminary results suggest that the relationship between PVS volume and speeded executive function is mediated by global atrophy and WMH in neurodegenerative and cerebrovascular disease. Future analyses will further examine the role of plasma biomarkers and other imaging markers such as cerebral microbleeds.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".