Evidence map›Paper›PMID 40639266›Full record

ArticleJournal of the neurological sciences2025

Quantitative analysis of cerebral vasculature and its clinical effect on cognitive change in Alzheimer's dementia and mild cognitive impairment.

Taewon Kim, Kaiyu Zhang, Tong Zhu, In-Uk Song, Seunghee Na, Daniel S Hippe, Gador Canton, Thomas Hatsukami, Chun Yuan, Mahmud Mossa-Basha and 1 more

Abstract read
In one paragraph

Article in Journal of the neurological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Taewon KimDepartment of Neurology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Kaiyu ZhangVascular Imaging Lab, Department of Radiology, University of Washington, Seattle, WA, USA.
Tong ZhuVascular Imaging Lab, Department of Radiology, University of Washington, Seattle, WA, USA.
In-Uk SongDepartment of Neurology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Seunghee NaDepartment of Neurology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
Daniel S HippeClinical Biostatistics, Clinical Research Division, Fred Hutchison Cancer Center, Seattle, WA, USA.
Gador CantonVascular Imaging Lab, Department of Radiology, University of Washington, Seattle, WA, USA.
Thomas HatsukamiDepartment of Surgery, University of Washington, Seattle, WA, USA.
Chun YuanVascular Imaging Lab, Department of Radiology, University of Washington, Seattle, WA, USA.
Mahmud Mossa-BashaVascular Imaging Lab, Department of Radiology, University of Washington, Seattle, WA, USA.
Niranjan BaluVascular Imaging Lab, Department of Radiology, University of Washington, Seattle, WA, USA. Electronic address: ninja@uw.edu.

Funding

3D WALLI: MR intracranial vessel wall imaging for stroke preventionR01NS092207 · NINDS · UNIVERSITY OF WASHINGTON · PI MOSSA-BASHA, MAHMUD, YUAN, CHUN · 2016 to 2019
$3.1M
Quantitative model-based ESUS reclassification using cardiac and cerebral vessel wall MRIR01NS125635 · NINDS · UNIVERSITY OF WASHINGTON · PI AKOUM, NAZEM, MOSSA-BASHA, MAHMUD · 2022 to 2025
$3.0M
Automated Intracranial Vessel Wall Analysis Pipeline for Multi-contrast Multi-platform ApplicationsR01NS127317 · NINDS · UNIVERSITY OF WASHINGTON · PI MOSSA-BASHA, MAHMUD, YUAN, CHUN · 2022 to 2025
$2.2M
NINDS NIH HHS R01 NS092207NINDS NIH HHS R01 NS125635NINDS NIH HHS R01 NS127317
6 · The paper itself

Abstract

backgroundCerebrovascular disease (CVD) and Alzheimer's disease (AD) share common risk factors and often coexist. This study investigates the relationship between cerebral arterial features and cognitive decline in patients with clinical AD dementia and amnestic mild cognitive impairment (MCI) using quantitative analysis of Time-Of-Flight (TOF) magnetic resonance angiography (MRA).

methods131 patients (101 AD dementia, 30 amnestic MCI) underwent baseline TOF-MRA and cognitive assessments and 24-month follow-up cognitive tests. Total distal arterial length was measured using a custom-designed semi-automatic intracranial vascular map construction software. Associations between total distal arterial length and cognitive changes were analyzed using multiple linear regression and repeated measures analysis of covariance.

resultsShorter total distal arterial length was significantly associated with greater 2-year decline in Montreal Cognitive Assessment (MoCA) scores over 2 years (r = 0.199, p = 0.020). This association remained significant after adjusting for various confounding factors, including age, sex, education, brain parenchymal fraction, white matter hyperintensities, ApoE4 status, and vascular risk factors. Similar trends were observed for Mini-Mental State Examination (MMSE) scores, although not reaching statistical significance.

conclusionsQuantitative measurements of cerebral vasculature on TOF-MRA are independently associated with cognitive decline in patients with clinical AD dementia and amnestic MCI. This suggests that reduced cerebral blood flow may contribute to cognitive decline in these patients, highlighting the potential role of vascular factors in AD progression. These findings support the use of quantitative cerebral arterial measurements as a potential imaging biomarker for cognitive decline in AD.

Indexed as

Alzheimer DiseaseCerebral ArteriesCognitive DysfunctionAgedAged, 80 and overBrainDisease ProgressionFemaleFollow-Up StudiesHumansMagnetic Resonance AngiographyMaleMental Status and Dementia TestsMiddle AgedNeuropsychological TestsAlzheimer's diseaseCerebral vasculatureCognitive decline

Identifiers

PMID40639266
PMCPMC13419663

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.