Comparison of Visual Rating Scale Based on Brain 18F-FDG-PET and Montreal Cognitive Assessment Test in Probable Alzheimer’s Disease
Bibliographic record
Abstract
Objecives: Recently, imaging biomarkers like flouro-deoxi-glucose positron emission tomography (FDG-PET) become even more important for evaluation probable AD. The aim of this study was to evaluate the possible correlation between Montreal Cognitive Assessment Test (MoCA) and metabolic function of brain regions determined by FDG-PET in patients with probable AD. Materials and methods: Thirty seven (37) patients who had diagnosis of probable AD were included. MoCA test and metabolic measurements of brain regions by FDG-PET were performed in all patients. A visual scoring was performed to obtain the rates of hypometabolism in brain regions. Results: Median age of the patients was 77 (minimum 65-maximum 83) years. On the right hemisphere, MOCA test score decreased according to visual FDG-PET score of parietal lobe (15±5.1, 11.8±8.4 and 8.5±5.9; p=0.032). MOCA test score was 16±5.8, 13.1±7.6 and 9.1±6.1 in patients with left temporal lobe and 15.2±5.2, 11.8±7.8 and 8.5±5.9 in patients with left parietal lobe according to visual FDG-PET scores respectively (p=0.035; p=0.02). The comparison of the other right and left hemisphere regions and MOCA test scores were not significant. Conclusion: The present study is emphasized that the MoCA test which is easily applied in outpatient clinics can be demonstrated the hypometabolism of bilateral parietal and left temporal brain regions related with pathophysiology 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".