Development of White Matter Hyperintensity Is Preceded by Reduced Cerebrovascular Reactivity
Bibliographic record
Abstract
OBJECTIVE: White matter hyperintensities (WMH) observed on neuroimaging of elderly individuals are associated with cognitive decline and disability. However, the pathogenesis of WMH remains poorly understood. We observed that regions of reduced cerebrovascular reactivity (CVR) in the white matter of young individuals correspond to the regions most susceptible to WMH in the elderly. This finding prompted us to consider that reduced CVR may play a role in the pathogenesis of WMH. We hypothesized that reduced CVR precedes development of WMH. METHODS: We examined 45 subjects (age range = 50-91 years; 25 males) with moderate-severe WMH, and measured their baseline CVR using the blood oxygen level-dependent magnetic resonance imaging signal response to a standardized step change in the end-tidal partial pressure of carbon dioxide. Diffusion tensor imaging and transverse relaxation time (T2) relaxometry were performed at baseline and 1-year follow-up, with automated coregistration between time points. Baseline fractional anisotropy (FA), mean diffusivity (MD), T2, and CVR were measured in areas that progressed from normal-appearing white matter (NAWM) to WMH over the 1-year period. RESULTS: CVR and FA values in baseline NAWM that progressed to WMH were lower by mean (standard deviation) = 26.5% (23.2%) and 11.0% (7.2%), respectively, compared to the contralateral homologous NAWM that did not progress (p < 0.001). T2 and MD were higher by 8.7% (7.9%) and 17.0% (8.5%), respectively, compared to the contralateral homologous NAWM (p < 0.001). INTERPRETATION: Areas of reduced CVR precede the progression from NAWM to WMH, suggesting that hemodynamic impairment may contribute to the pathogenesis and progression of age-related white matter disease. Ann Neurol 2016;80:277-285.
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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 | 0.000 | 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) | 0.001 | 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".