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Record W7117234860 · doi:10.1002/alz70856_104247

MRI‐based biomarkers of cerebrovascular function and their role in VCID

2025· article· en· W7117234860 on OpenAlexaboutno aff
Hanzhang Lu

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsFunction (biology)BiomarkerDiseaseCognitionCognitive impairmentStroke (engine)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.272
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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