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Record W4411901794 · doi:10.21037/qims-2025-96

Association of magnetic resonance imaging glymphatic function with gray matter volume loss and cognitive impairment in Alzheimer’s disease: a diffusion tensor image analysis along the perivascular space (DTI-ALPS) study

2025· article· en· W4411901794 on OpenAlexaboutno aff
Qian Zhang, Chaogang Wei, Chong Cui, Ting Huang, Shanwen Liu, Meng Li, Yuqi Zhi, Hua Hu, Zhen Jiang, Rong Liu

Bibliographic record

VenueQuantitative Imaging in Medicine and Surgery · 2025
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
Fundersnot available
KeywordsDiffusion MRIMagnetic resonance imagingGlymphatic systemPerivascular spaceMedicineCognitive impairmentPathologyGray (unit)Nuclear magnetic resonanceDiseaseRadiologyPhysicsCerebrospinal fluid

Abstract

fetched live from OpenAlex

Background: Diffusion tensor image analysis along the perivascular space (DTI-ALPS) has been used for diagnosing Alzheimer's disease (AD); however, few studies have examined the relationship between the DTI-ALPS index and cortical metrics, and the differentiation between AD severity levels remains unclear. This study aimed to explore the differences in DTI-ALPS index and cortex among AD patients with varying severities and to analyze the interactions between DTI-ALPS index, cortical metrics, and cognitive function. Methods: A total of 19 individuals with mild cognitive impairment (MCI), 17 individuals exhibiting mild AD, 25 individuals with moderate AD, and 28 healthy controls (HC) who were matched for age, sex, and education level were recruited. All the participants underwent diffusion tensor imaging (DTI) magnetic resonance imaging (MRI), followed by the calculation of the DTI-ALPS index to assess lymphatic system function. FreeSurfer (v7.4.1) was used to calculate thickness, volume, local gyre index, and area. One-way analysis of variance (ANOVA) was performed to compare the differences among HC, MCI, mild AD, and moderate AD groups. Pearson correlation analysis was employed to investigate the connection between the DTI-ALPS index and cognitive function, along with cortical metrics. Results: The HC, MCI, mild AD, and moderate AD groups exhibited significant differences in the DTI-ALPS index of the left hemisphere (P=0.008), whereas 13 cortical metrics revealed a statistical significance between groups (P<0.05). In the left hemisphere, the DTI-ALPS index showed a positive trend with the Montreal Cognitive Assessment (MoCA) score (r=0.397, P<0.001). Higher DTI-ALPS was also associated with an increase in 10 cortical metrics after controlling for age, sex, and education. Conclusions: There is a significant relationship between the DTI-ALPS index, cortical metrics, and cognitive function. This result may suggest that lymphatic dysfunction indicated by the DTI-ALPS index could mirror cortical structural degeneration and cognitive decline within the pathological process of AD. DTI-ALPS can be used as an indicator of structural degeneration and decline in cognitive function in AD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.283
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

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