P2‐010: Does variable progression of incidental white matter hyperintensities in Alzheimer's disease relate to venous insufficiency?
Bibliographic record
Abstract
Incidental white matter hyperintensities (WMH) in Alzheimer's disease (AD) are usually attributed to small arterial occlusive disease. However, variability in lesion change over time and unpredictable conditions between lesion volumes and cognition raise questions. An intraparenchymal venular disorder or CSF circulation disturbance in perivascular spaces may need to be considered to explain non-lacunar focal WMH in AD. Thirty-two AD (age=74) and 10 healthy elderly(age=72) had two high resolution MRI at 1.3 years apart. After 3D-T1, T2W and PDW images were co-registered, focal WMH were identified, and locations compared with intraparenchymal vascular anatomy (including perivascular spaces), evident as linear hypointense signals on appropriately windowed 3D-T1 images. Vessels or perivascular spaces were considered to be deep intramedullary or transcerebral venous structures if connected to the lateral ventricle (Fig1A), and overlap of focal WMH with these veins was deemed to implicate venous pathology. Change over time (enlargement, shrinkage, new appearance or disappearance) of each focal WMH was carefully analyzed. Total WMH volume and mean focal WMH count did not differ in AD vs controls. Anatomically, 94% of 561 focal WMH at baseline and 94% of 33 new focal WMH at one year overlapped with enlarged intraparenchymal vessels or perivascular spaces (see examples in Fig1B,C,D and Fig2A). Approximately 52% of these lesions overlapped the deep intramedullary or transcerebral veins. Over one year, 30% enlarged concentrically or spread along perivascular spaces (Fig2B), and 6% either shrunk or disappeared (Fig2C) at time. Most incidental WMH (i.e. non-lacunar) were associated with enlarged intraparenchymal vessels or perivascular spaces, likely to be venous-related in both AD and normal aging. Their dynamic change over time, their tendency to spread along the perivascular spaces or to disappear would be compatible with cerebral venular insufficiency (related to venous collagenosis of aging) causing leakage of fluid i.e. edema, which appears as hyperintense in T2W/PDW MRI.We suggest that small vessel disease involving both the venous and arterial sides of the cerebral occlusion may contribute to white matter disease in aging and dementia.
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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 | 0.005 |
| 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) | 0.006 | 0.002 |
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".