IC‐P‐142: SURFACE‐BASED MULTIMODAL CLUSTER ANALYSIS REVEALS TOPOGRAPHICAL HETEROGENEITY OF ALZHEIMER'S DISEASE
Bibliographic record
Abstract
The clinical presentation and atrophy pattern of Alzheimer's disease (AD) dementia is known to be heterogeneous. To address the topographical heterogeneity of the AD, we developed a cortical surface-based cluster analysis framework by combining multimodal imaging such as PET and MRI. We collected THK-5351-PET (tau), 1⁸F-flutemetamol-PET (amyloid-β), and T1-weighted-MRI (T1w) from 60 normal controls and 83 patients (Clinical Dementia Rating≤1). We co-registered each of the two PET modalities into the T1w. We reconstructed cortical surfaces using the CIVET pipeline. Partial-volume effects of PET were corrected. We precisely mapped cortical thickness, tau-SUVR and amyloid-β-SUVR of each subject at each vertex coordinates on mid-cortical surfaces (Figure1). The features were 20mm smoothed and normalized by z-score. We performed agglomerative hierarchical clustering analysis (Figure2). The identified subtypes were compared with the normal controls using a general linear model adjusting for age, sex, years of education. Intracranial volume was included in the cortical thickness analysis. We mapped effect size within significant cortical regions reaching random field theory corrected p-vertex<0.05. Surface-based multimodal feature extraction. Agglomerative hierarchical cluster analysis. The AD dementia patients were subcategorized into three subtypes (Figure3): medial temporal-dominant subtype (MT, n=44), parietal-dominant subtype (P, n=19), and diffuse atrophy subtype (D, n=20). The demographics (Table1) and neuropsychological test results (Table2) showed distinct features among each subtype. In the MT subtype, the patients were older than other subtypes and the female percentage was outnumbered, and this might result from an age-related reduction of estrogen. The patients in the P subtype had the earliest onset-age and were the youngest among subtypes, and the worst scored on most neuropsychological tests, and this might result from the dysfunction of parietal and dorsolateral prefrontal cortex region. The patients in the D subtype had the most education years, and neuropsychological profiles were in between MT and P subtypes. Topographical atrophy of AD subtypes. Our surface-based multimodal cluster analysis framework has revealed three distinct subtypes among AD patients in terms of distribution of cortical atrophy, amyloid plaques, and neurofibrillary tangles, and demographical/neuropsychological profile. Consideration of the heterogeneous atrophy patterns may be important when planning future preventative and treatment strategies because the AD subtypes may have different responses to treatment and different courses of disease progression.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".