P2‐100: Relationship between collagenosis of the deep medullary veins and periventricular white matter hyperintensities on magnetic resonance imaging in Alzheimer's disease: Does one size fit all?
Bibliographic record
Abstract
Incidental white matter hyperintensities (WMH), prevalent in patients with Alzheimer's disease (AD), are usually attributed to occlusive ischemic arteriolar disease. However, periventricular venous collagenosis (VC) (Moody&Brown1995) has also been identified in WMH. This study investigated relationships of WMH on MRI with VC involving venules of different sizes, arteriolosclerosis and other white matter (WM) abnormalities on histopathology. 14 AD patients (age = 62-81 years; Braak/Braak stage IV-VI; no strokes) with varying degrees of WMH were included from a longitudinal dementia study. Using archived CNS autopsy tissue, coronal sections of periventricular WM (frontal, middle and posterior) were blocked and re-examined microscopically by one neuropathologist blinded to imaging. For each region (total = 42), VC of small-size (<20um) (S-VC) and medium-size (50-150um) (M-VC) venules were rated 0-to-3 based on severity of wall-thickening or stenosis on Masson trichrome staining; three larger veins (>200um) (external and lumen diameters) were measured, and average percent of stenosis (L-VC) was calculated; other pathologies including clasmatodendrosis, myelin loss, and granular ependymitis were rated. Arteriolosclerosis (yes/no) was rated globally. MRI coronal slices corresponding to the pathology were created in pre-mortem 3D-T1 and proton density MRI. WMH were rated 0-to-3 or dichotomized to low (score = 0-1) or high (score = 2-3) scores using the Fazekas scale at each region. WMH volumes using Lesion-Explorer (Ramirez, 2011) were quantified blinded to histopathology. Prevalence of S-VC and M-VC was 71% and 55% respectively in all regions, and arteriolosclerosis was present in 50%. Frequency of VC or arteriolosclerosis did not differ (P>0.05) in the groups with high and low WMH scores in X 2 -analysis. However, the high Fazekas group had greater L-VC than low Fazekas group (t(2,40) = 2.06, p<0.05). L-VC did not differ between those with and without arteriolosclerosis. In linear regression of all subjects with these vascular pathologies included, only L-VC predicted WMH volume (R 2 -change = 0.335, p<0.05). Collagenosis of large periventicular veins correlated with WMH, but small venular collagenosis or arteriolosclerosis did not. Venous resistance from larger-sized collagenous venulopathy may increase blood-brain barrier leakage or decrease interstitial fluid absorption, resulting in vasogenic edema, which appears hyperintense on MRI. Further investigations are warranted for the exact correlates, given the ubiquity of WMH with aging and AD.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".