Cerebrovascular reserve differentiates cognitively normal older adults from individuals with mild cognitive impairment
Bibliographic record
Abstract
Abstract Background Abnormal cerebral blood flow (CBF) is observed in early Alzheimer’s disease. Cerebrovascular reserve (CVR) represents the ability of the vasculature to maintain normal CBF. While CBF abnormalities can indicate a primary vascular dysfunction, it could also arise secondary to neurodegeneration and reduced metabolic demands. CVR, on the other hand, is a specific marker of vascular insufficiency. Our goal was to evaluate the associations between CVR, CBF, and cognition in older adults with and without MCI. Methods 70 older adults (>65 years 77.3 ± 8.32 years old, 42F, 46 controls i.e., NC and 24 MCI) were scanned in compliance with Institutional Review Board guidelines. Besides a T1 scan, we performed pCASL to quantify baseline CBF and a breath‐hold BOLD fMRI experiment to quantify CVR. We use a mixed‐effects model in FSL to test CVR and CBF differences between groups as well as association with cognitive tests, i.e., Montreal Cognitive Assessment (MoCA), Immediate and Delayed recall (CRAFTi/d) and Trails‐B, using Gaussian random field theory for a cluster‐wise threshold of p = 0.05. All comparisons were adjusted for age and gender. Results Only CVR was significantly (p<0.05) different between NC and MCI (Figure 1). While there was no group difference in CBF, the group difference between CVR was no longer significant when adjusted for baseline CBF. Investigating further, high CBF was significantly associated with lower CVR in the MCI group only. A high CBF was very weakly related to high CVR in NC (Figure 2). A high CVR was associated with a high MoCA score (Figure 3) and CRAFTi/d (Figure 4). Conclusion We demonstrated the utility of a simple breath‐hold based CVR measurement in understanding the association between vascular mechanisms and cognition. It is likely that CBF is not different between groups because MCI participants utilize their vascular reserve to maintain baseline CBF. Consequently, an additional vascular challenge results in a lower CVR measurement. Furthermore, a higher CVR in MCI subjects such as that seen in association with cognitive tests could be a result steal phenomenon to redirect perfusion from degenerating tissue to viable tissue. However, these mechanisms need to be further investigated.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".