Bibliographic record
Abstract
BACKGROUND: MRI provides an excellent tool in assessing cerebrovascular function and presents an important opportunity for the development of biomarkers in vascular contributions to cognitive impairment and dementia (VCID). In this work, we will review recent development in MRI-based biomarkers of cerebrovascular physiology and their potential role in VCID. METHOD: This work will discuss 3 important parameters related to cerebrovascular function, measured with MRI (Figure 1). Section 1 will describe cerebral blood flow (CBF). CBF (Figure 1a) of the brain can be measured with a non-contrast MRI technique referred to as arterial spin labeling (ASL). Section 2 will discuss oxygen extraction fraction (OEF). OEF (Figure 1b) reflects the balance between oxygen supply and consumption and is a known hallmark of ischemia. Section 3 will discuss a cerebrovascular reactivity (CVR) measure that reflects the brain's dynamic vascular function of vasodilatory capacity. CVR (Figure 1b) has been evaluated in the MarkVCID Consortium. RESULT: CBF has been investigated extensively in the context of Alzheimer's dementia. The general findings were that CBF was diminished in default model network brain regions such as posterior cingulate cortex and angular gyrus. This is thought to be related to reduced neural activity, as opposed to impaired vascular function. CBF alterations in VCID is less studied. A few studies including sporadic and genetic small vessel disease have suggested that CBF in VCID is reduced in a global fashion. OEF studies suggest that the brain's OEF is differentially affected in AD and VCID. With AD, OEF was often found to be diminished, presumably due to neurodegeneration and reduced brain metabolic rate. With VCID, OEF is elevated with higher vascular risk factors (Figure 2a) and increased faster longitudinally (Figure 2b). CVR is diminished in impaired individuals and is most strongly correlated with the Montreal Cognitive Assessment (MoCA) score (Figure 3). This association was found to be independent of AD pathological measures such as a-beta42, tau, and ptau. CVR was also associated with executive function. CONCLUSION: Several MRI-based cerebrovascular measures have shown strong promises as biomarkers in cognitive impairment and dementia, especially for VCID where available biomarkers are relatively scarce.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".