P3‐254: Perivascular Distribution and Variable Progression of Focal White Matter Hyperintensities in Alzheimer’S Disease
Bibliographic record
Abstract
The origin(s) of white matter hyperintensities (WMH) in Alzheimer’s disease (AD) is not fully understood. Previous studies suggest that parenchymal cerebral vessels (eg arteries and veins) play a role not only in blood circulation, but also in homeostasis of interstitial fluid and toxic metabolite clearance. Specifically the perivascular spaces along the vessels may serve as cerebral lymphatics, and WMH may signify brain lymphatic dysfunction. The purpose of this study was to investigate whether focal WMH were spatially related to intramedullary vessels, and to track their dynamic characteristics by observing any change over one year on MRI. Focal WMH in periventricular and deep white matter were evaluated in 40 AD (age=75) and 20 healthy elderly (age=72) using co-registered 3D-T1 and T2-weighted MR images. A focal WMH was considered as perivascular if it was centered around or overlapped with an intramedullary vessel (Fig1). Intramedullary vessels were defined as linear hypointense signals on appropriately windowed 3D-T1 images. Based on the intramedullary vascular anatomy, a vessel was classified as arteriolar if it was near the cortex or as venular if it connected to the lateral ventricles. Each focal WMH was classified as (enlarging, shrinking or unchanged) between time1 and time 2 (mean 1.3 year apart). A total of 758 focal WMH were identified on the baseline scans from all subjects. 715 (94.3%) focal WMH were perivascular, including 206(28.8%) arteriolar-related and 403(56.4%) venular-related. Of the 715 perivascular focal WMH in the baseline, 209(29.2%) increased, 49(6.9%) decreased and 457(63.9%) were unchanged in size at follow-up (Fig2). These characteristics did not differ between AD and healthy elderly. Focal non-lacunar WMH were mostly centered around intramedullary vessels, suggesting perivascular distribution and were more often associated with venules, than arterioles. The change in size over time raises the possibility the focal WMH may represent perivascular edema/leakage, reflecting underlying dysfunction of perivascular lymphatic drainage. Based on the known increase in arteriolosclerosis and venous collagenosis in aging, we suggest that in aging and dementia small vessel disease may be damaging not only from vascular occlusion but also dysfunction of perivascular clearance of fluid and toxic metabolites. Spatial relationship of focal WMH with intramedullary vessels in MRI Focal WMH change over time T1 and T2 MRI co-registered in the same space showing focal WMH overlapped with intramedullary vessels. Foci can not only increase (A), but also decrease (B) in size over time.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".