Cholinergic Subcortical Hyperintensities in Alzheimer's Disease Patients from the Sunnybrook Dementia Study: Relationships with Cognitive Dysfunction and Hippocampal Atrophy
Bibliographic record
Abstract
BACKGROUND: Subcortical hyperintensities within the cholinergic fiber projections (chSH) on MRI are believed to reflect cerebral small vessel disease (SVD) which may adversely impact cognition. Additionally, hippocampal atrophy represents a commonly used biomarker to support the diagnosis of Alzheimer's disease (AD). OBJECTIVE: To examine potential differences in neuropsychological test performance between AD patients (n = 234) with high and low chSH volumes and whether these differences corresponded to hippocampal atrophy. METHODS: A modified version of Lesion Explorer was used to volumetrically quantify chSH severity. The Sunnybrook Hippocampal Volumetry Tool was applied to obtain hippocampal volumes. Composite z-scores to assess executive, memory, and visuospatial functioning were generated from standardized neuropsychological test performance scores. RESULTS: Inter-method technique validation demonstrated a high degree of correspondence with the Cholinergic Pathways Hyperintensities Scale (n = 40, ρ = 0.84, p < 0.001). After adjusting for brain atrophy, disease severity, global SH volumes, and demographic variables, multivariate analyses revealed a significant group difference, with the high chSH group demonstrating poorer memory function compared to the low chSH group (p = 0.03). A significant difference was found between low and high chSH groups in total (p < 0.05) and left (p < 0.01) hippocampal volume. CONCLUSION: These results suggest degradation of the cholinergic projections due to strategic SVD may independently contribute to memory dysfunction and hippocampal atrophy. Future studies examining subcortical vasculopathy in the cholinergic pathways may have implications on the development of therapeutic strategies for dementia and SVD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".