P2‐252: Cerebral blood flow changes in early Alzheimer's disease: A high‐field arterial spin labeling perfusion MRI study
Bibliographic record
Abstract
Recent research has suggested that Alzheimer's disease (AD) is associated with significant cerebral circulation abnormalities, in addition to the hallmark neurodegenerative changes. While decline in cerebral perfusion in localized brain regions has been well documented in established AD, hyperperfusion has also been observed at the early stages, which has not been well studied. We investigated both hypoperfusion and hyperperfusion perfusion changes in early AD, using arterial spin labeling perfusion MRI at high-field. Twelve patients with early AD (72.3 ± 7.9 years old; 5 women) and 12 cognitively normal older adults (CN, 73.7 ± 5.5 years old, 9 women) were scanned using 4 Tesla MRI (Varian-Oxford human imaging system). Flow-sensitive alternating inversion recovery imaging (FAIR) was acquired using the arterial spin labeling (ASL) perfusion weighted imaging method (seven interleaved axial slices, thickness = 5mm, gaP = 2mm, TR/TE/TI = 2800/3/1400ms). Subjects were asked to remain relaxed with their eyes open during a seven-minute scan. High-resolution whole brain structural images were acquired using MP-FLASH (TR/TE = 10.1/5ms, thickness = 1.2mm). Data processing included motion correction, spatial smoothing, registration of non-selective and selective slices, and brain segmentation (using FSL and SPM5). Analysis outcomes were adjusted for age, sex, education level, structural brain changes, and cognitive performance. Compared to CN, early AD patients showed significant hypoperfusion chiefly in the left precuenus, the right superior temporal cortex, and the posterior cingulate cortex. Meanwhile, relative to CN, in AD, significant hyperperfusion was found in the right dorsolateral prefrontal cortex (DLPFC) and the left anterior cingulate cortex, as well as in the left DLPFC and the ventrolateral prefrontal cortex (VLPFC). Early AD appears to be characterized by both hypoperfusion and hyperperfusion in well-defined brain regions, correlating with the underlying neuropathological processes. The increased resting-state cerebral blood flow in the DLPFC and in the VLPFC suggests a possible compensatory mechanism to maintain important neural networks, such as the attentional neural network, in early stages of AD.
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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 | 0.001 | 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 | 0.001 | 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".