Microstructural Hippocampal Alterations in Alzheimer's Disease: A Systematic Review and Meta‐Analysis of Diffusion Kurtosis Imaging
Bibliographic record
Abstract
ABSTRACT Background The hippocampus is highly vulnerable in Alzheimer's disease (AD), with early microstructural changes potentially detectable via diffusion kurtosis imaging (DKI). Previous studies report promising DKI findings in AD, necessitating systematic evaluation. To compare hippocampal DKI metrics, particularly mean kurtosis (MK), between AD patients and healthy controls (HCs) and explore factors influencing these differences. Methods Following PRISMA guidelines, PubMed, Scopus, Web of Science, and Embase were searched until November 2024. Two reviewers independently extracted hippocampal MK values. Risk of bias was evaluated using the Newcastle–Ottawa Scale. Meta‐analysis employed random‐effects models (STATA v17). Subgroup analyses (sex, age, magnetic resonance imaging [MRI] parameters) and sensitivity and trim‐and‐fill assessments were conducted. Standardized mean difference (SMD), I 2 for heterogeneity, and Egger's/Begg's tests for publication bias (significance: p < 0.05). Results Ten studies (215 AD patients, 217 HCs; mean age: 65–75 years) using 3.0 T MRI were included. Eight articles were included in the meta‐analysis to compare MK between groups. AD patients exhibited significantly reduced bilateral hippocampal MK compared to HCs (left: SMD = −1.32, 95% confidence interval [95% CI] [−1.97 to −0.66]; right: SMD = −1.22 [−1.88 to −0.56]; both p < 0.001), indicating compromised microstructural complexity. Subgroup analyses revealed more pronounced MK reductions in studies with higher male ratios (>42%; left: SMD = −1.87; right: SMD = −1.91; p < 0.05). Age, echo time, repetition time, and diffusion directions did not significantly influence effect sizes. Sensitivity analyses confirmed robustness, and publication bias was detected, but trim‐and‐fill analyses revealed no missing studies. Conclusion Reduced hippocampal MK in AD reflects microstructural degeneration, with sex‐related differences in effect magnitude.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".