Lobar distribution of white matter abnormalities in Alzheimer’s, vascular and mixed dementias
Bibliographic record
Abstract
Abstract Background Vascular dementia (VaD) is often difficult to distinguish from Alzheimer’s disease (AD).[O’Brien_2015] Areas of cognitive/clinical decline due to cerebrovascular diseases depend on the frequency and location of the lesions, and may overlap with those found in AD.[Suri_2014] Moreover, AD and cerebrovascular diseases frequently occur simultaneously, leading to heterogeneous ‘mixed dementia (MixD)’.[Wang_2012][Langa_2004] It is unclear whether the presence of both neurodegenerative and cerebrovascular pathologies further aggravates dementia‐related imaging abnormalities. We investigated whether the lobar distribution of white matter hyperintensities (WMHs) on MRI differed among AD, VaD and MixD. Method N=17 participants (cross‐sectional; subtypes:7 MixD/5 Subcortical VaD/5 AD; Sex: 11M/6F; Age: 75±8yrs) were scanned on a 3T Philips Achieva. T1‐weighted MP‐RAGE images were processed with Freesurfer 6.0. Areas of WMHs were segmented on Fluid Attenuated Inversion Recovery (3D‐FLAIR) images using a combination of intensity thresholding and manual correction. Left and right frontal, temporal, occipital and parietal lobes plus basal ganglia volumes were constructed using the Freesurfer segmentation outputs. Individual WMH masks were transformed to their respective T1‐weighted spaces, and the ratios of WMH volumes to different lobar volumes were calculated. Result Average WMH volumes were (mean±SD) AD: 5191±4693mm3, MixD: 34680±17059mm3 (sig. greater than AD), SVaD: 20896±14920mm3 (n.s. from MixD or AD). We used a linear model to predict the ratios of WMH to lobar volumes from the diagnosis subtypes, adjusting for age and sex. A significant diagnosis‐subtype effect was found in both the left and right frontal lobes. (p=0.012 and 0.045, respectively). In the left frontal lobe, the proportion of WMHs was significantly greater in the MixD subgroup compared to the AD (p=0.0045) or the VaD (p=0.026) subtypes. In the right frontal lobe, the proportion was greater in the MixD subtype compared to the AD (p=0.018) but not compared to VaD (p=0.074) subtype. AD vs. VaD were not significantly different in either sides (p=0.5). Conclusion The MixD subtype of our pilot study cohort was characterized by a significantly greater presence of WMHs in the frontal lobar areas. Future studies are warranted to investigate the characteristics of underlying tissue abnormalities that could be specific to the diagnosis subtypes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".