P1–295: A differential pattern of hippocampal atrophy in Alzheimer's disease with coexistent small vessel disease: A multivariate shape‐based analysis
Bibliographic record
Abstract
Hippocampal volume is a sensitive marker of Alzheimer's disease (AD) progression. Previous studies in AD have demonstrated heterogeneous atrophy profiles among hippocampal subregions. Cerebral small vessel disease (SVD) often coexists with AD, and may differentially affect atrophy within sub-regions of the hippocampus compared to AD alone. Shape-based studies have traditionally used univariate methods, which independently test significance at each element of a surface/structure (vertex/voxel). Conversely, multivariate models such as Partial Least Squares (PLS) indentify significantly distributed patterns of atrophy across all structural elements. Thus, we examined with PLS, whether a differential pattern of hippocampal atrophy existed between AD, AD+SVD and normal controls (NC). Cross-sectional data were acquired from the Sunnybrook Dementia Study: AD (n=144), AD+SVD (n=47) and NC (n=95). All subjects had 1.5 Tesla T1-SPGR MRIs (Matrix=256x192; TE/TR=35ms/5ms; flip-angle=35°, in-plane resolution=0.859×0.859x1.2–1.4mm). Participants with SVD had evidence of white matter hyperintensities on PD/T2-MRI and/or evidence of subcortical lacunar infarcts. A novel surface-based technique was developed to measure hippocampal shape differences. Briefly, an average template was generated and used to align all subjects to a common space. Next, the Advanced Normalization Tools SyN algorithm was used to nonlinearly register all subjects to the template. A mesh was generated over the template hippocampi, and the inverse warp vector was indexed and multiplied by the normal vector at each mesh vertex; this provided a vertex-wise scalar value of shape difference in relation to the template surface across all subjects (Matlab-MathWorks). PLS software (http://www.rotman-baycrest.on.ca/index.php?section=84) was adapted for surface-based parametric data. Mean-centred PLS with bootstrapping(x1000) and permutation testing(x1000) was applied to detect significant patterns of atrophy between groups. Analyses were corrected for sex and age. PLS revealed a significantly different pattern of atrophy in NC versus AD and AD+SVD involving the anteriolateral CA1, medial subiculum and posteriorlateral hippocampus (p<0.05). A trend was realized for less atrophy in the left anterior-medial hippocampal region for AD+SVD versus AD, with more involvement of the left lateral subiculum in AD and left anteriolateral region in AD+SVD (p =0.06). These data suggest that a differential pattern of hippocampal atrophy may exist in AD+SVD versus AD and may provide insight into how these coexistent pathologies interact in-vivo.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".