Topographic Distribution of Amyloid-β, Tau, and Atrophy in Patients With Behavioral/Dysexecutive Alzheimer Disease
Bibliographic record
Abstract
<h3>Objective</h3> To determine the associations between amyloid-PET, tau-PET, and atrophy with the behavioral/dysexecutive presentation of Alzheimer disease (AD), how these differ from amnestic AD, and how they correlate to clinical symptoms. <h3>Methods</h3> We assessed 15 patients with behavioral/dysexecutive AD recruited from a tertiary care memory clinic, all of whom had biologically defined AD. They were compared with 25 patients with disease severity– and age-matched amnestic AD and a group of 131 cognitively unimpaired (CU) elderly individuals. All participants were evaluated with amyloid-PET with [<sup>18</sup>F]AZD4694, tau-PET with [<sup>18</sup>F]MK6240, MRI, and neuropsychological testing. <h3>Results</h3> Voxelwise contrasts identified patterns of frontal cortical tau aggregation in behavioral/dysexecutive AD, with peaks in medial prefrontal, anterior cingulate, and frontal insular cortices in contrast to amnestic AD. No differences were observed in the distribution of amyloid-PET or atrophy as determined by voxel-based morphometry. Voxelwise area under the receiver operating characteristic curve analyses revealed that tau-PET uptake in the medial prefrontal, anterior cingulate, and frontal insular cortices were best able to differentiate between behavioral/dysexecutive and amnestic AD (area under the curve 0.87). Voxelwise regressions demonstrated relationships between frontal cortical tau load and degree of executive dysfunction. <h3>Conclusions</h3> Our results provide evidence of frontal cortical involvement of tau pathology in behavioral/dysexecutive AD and highlight the need for consensus clinical criteria in this syndrome.
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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".