Regional cerebral blood flow and brain atrophy in mild cognitive impairment and Alzheimer's disease
Bibliographic record
Abstract
Objectives: A decline in the regional cerebral blood flow (CBF) is proposed to be one of the initial changes in the Alzheimer's disease process. To date, there are limited data on the correlation between CBF decline and gray matter atrophy in mild cognitive impairment (MCI) and AD patients. to investigate the association between CBF with the gray matter structural parameters such as cortical volume, surface area, and thickness in AD, MCI, and healthy controls (HC). Methods: Data from three groups of participants including 39 HC, 82 MCI, and 28 AD subjects were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI). One-way ANOVA and linear regression were used to compare data and find a correlation between structural parameters such as cortical volume, surface area, and thickness and CBF which measured by arterial spin labeling (ASL)-MRI. Results: Our findings revealed a widespread significant correlation between the CBF and structural parameters in temporal, frontal, parietal, occipital, precentral gyrus, pericalcarine cortex, entorhinal cortex, supramarginal gyrus, fusiform, precuneus, and pallidum. Conclusion: CBF decline may be a useful biomarker for MCI and AD and accurately reflect the structural changes related to AD. According to the present results, CBF decline, as measured by ASL-MRI, is correlated with lower measures of structural parameters in AD responsible regions. It means that CBF decline may reflect AD-associated atrophy across disease progression and is also used as an early biomarker for AD and MCI diagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".