Fractional anisotropy in white matter hyperintensities is linked to associative memory performance
Bibliographic record
Abstract
Abstract Background Alzheimer’s disease pathology commonly coexists with cerebrovascular anomalies, suggesting a strong association between cerebrovascular lesions and cognitive performance. While different types and locations of cerebrovascular lesions such as strokes and white matter hyperintensities (WMHs) may interfere with various cognitive domains, these associations are not thoroughly understood. The most common approach to characterize and evaluate cerebral lesions is with structural neuroimaging. However, diffusion tensor imaging (DTI) can assess the microstructural integrity of cerebral tissue lesions, which may directly impact neuronal communication and consequently cognitive function. This study examines the variation in DTI metrics within different cerebrovascular lesions and their association with cognition in people with cerebrovascular disease (CVD). Method The variation of DTI metrics in 10 different cerebral tissues and lesions was examined in 152 subjects (aged 55‐85 years, 32% female) with CVD, (evidenced by an ischemic stroke event documented by MRI or CT, with a modified Rankin score 0‐3) available from the Ontario Neurodegenerative Disease Research Initiative (ONDRI). Fractional anisotropy (FA) and mean diffusivity (MD) were measured using an established DTI processing pipeline from 3 Tesla DTI images (32 directions, b=1000 s/mm2). Cerebral tissue lesion masks were obtained by semi‐automated segmentation of the structural T1‐weighted images to calculate average DTI metrics in each region of interest (ROI). In addition, FA in normal appearing WM (NAWM) and WMHs were correlated with MoCA score (measure of gross cognition), Rey Auditory Verbal Learning Test Long‐Delayed Recall score (measure of episodic memory), Trail Making Test‐Part B in seconds (measure of executive function), and Face‐Name Associative Memory Test score (measure of associative memory). Result Figure 1 shows a T1‐weighted anatomical image, corresponding tissue mask identifying vascular lesions, and corresponding MD and FA maps. Fig. 2 provides the average FA and MD in different cerebral tissues/lesions. FA within WMHs was found to be significantly correlated with Face Name Associative Memory Test score (p‐value<0.01, r=0.23, Fig. 3) after Bonferroni correction. No other significant associations were identified. Conclusion Considerable heterogeneity in DTI metrics was observed between cerebral tissues and lesions. Importantly, the structural integrity within WMHs also associated with higher associative memory performance.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".