Associations of white matter hyperintensities with cerebrovascular architecture in Alzheimer’s disease and related dementias
Bibliographic record
Abstract
Abstract Background MRI‐detected white matter hyperintensities (WMHs), a marker of cerebrovascular‐pathology, are common in Alzheimer’s disease (AD) and related dementias (ADRDs). In stroke, WMH‐volume was found to correlate most with stroke risk‐factors in the anterior cerebral arterial‐territory. Since the relationship between WMHs and arterial‐territories remains unexplored in the ADRDs, we systematically investigated WMHs’ spatial distribution (1) in 8 ADRDs relative to cognitively unimpaired (CU), and (2) across arterial‐territories per ADRD. Methods The extensive CCNA‐COMPASS‐ND cohort (N = 927) allowed us to investigate 9 clinical categories: CU, subjective (SCI) and mild (MCI) cognitive impairment, vascular MCI (V‐MCI), AD, vascular AD (V‐AD), Lewy‐body dementia (LBD), fronto‐temporal dementia (FTD), and Parkinson’s disease (PD) (Fig.1A). FLAIR and T1w MRI‐scans were used to segment WMHs (Dadar et al.,2017). Following registration to standard space, an arterial‐territory atlas (Schirmer et al.,2019) was used to calculate WMH‐volumes in 10 regions (Fig.1B). Statistical analyses were run on whole‐brain‐WMH‐volume and regional‐WMH‐ratios (region‐size‐normalized‐WMH‐volume/whole‐brain‐WMH‐volume). Data‐analyses used a series of linear models accounting for clinical category, age, and sex – followed by pairwise group‐comparisons corrected for multiple comparisons. Results 1) Relative to CU: Whole‐brain‐WMH‐volumes were higher for V‐MCI, V‐AD, and FTD. WMH‐ratios were higher in MCA and LMCA for 2 ADRDs (SCI;V‐MCI) and lower in PCA, LPCA, and RPCA for SCI. WMH‐ratios were higher in ACA or LACA and lower in PCA, LPCA, or RPCA for 4 ADRDs (V‐MCI;V‐AD;FTD;PD) (Fig.1C). Sex‐analyses: Men’s WMH‐volumes were higher in whole‐brain (CU;V‐MCI;FTD), while their WMH‐ratios were higherin LMCA (CU), but lower in ACA (SCI;MCI), LACA (MCI), and RACA (SCI). 2) MCA contained higher WMH‐ratios than ACA and PCA in all clinical categories. Relative to PCA, ACA’s WMH‐ratio was higher in 2 ADRDs (V‐MCI;V‐AD) and lower in 4 (CU;MCI;AD;PD). Pairwise‐group comparisons between all left/right arterial‐territories demonstrated consistent results (Fig.2). Asymmetry‐analyses: The right arterial side had higher WMH‐ratios in ACA (CU;V‐MCI), MCA (CU;SCI;MCI;V‐MCI;AD;V‐AD;PD), and PCA (MCI;AD). Conclusion We identified arterial‐territories of increased susceptibility to WMH‐formation per ADRD. The two most prevalent ADRDs (AD;V‐AD) were found to accumulate WMHs in a territory‐specific manner – higher WMH‐ratios in ACA for V‐AD and PCA for AD. Overall, the arterial‐territory‐specific WMH‐signatures identified may improve ADRD‐diagnosis accuracy.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".