Evidence map›Paper›PMID 40531396›Full record

ArticleJapanese journal of radiology2025

Altered connectivity among the triple brain networks in patients with mild cognitive impairment: a source-based morphometry study with a large elderly population.

Chihiro Yotsuya, Keita Watanabe, Sera Kasai, Yoshihito Umemura, Tomohiro Shintaku, Yuka Ishimoto, Miho Sasaki, Haruka Nagaya, Soichiro Tatsuo, Tatsuya Mikami and 4 more

Abstract read
In one paragraph

Article in Japanese journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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

14 authors.

Chihiro YotsuyaDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Keita WatanabeDepartment of Radiology, Kyoto Prefectural University of Medicine, 465 Kajiimachi, Jokyo-Ku, Kyoto, 602-8566, Japan. kw0928@koto.kpu-m.ac.jp.ORCID http://orcid.org/0000-0001-9592-8802
Sera KasaiDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Yoshihito UmemuraDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Tomohiro ShintakuDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Yuka IshimotoDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Miho SasakiDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Haruka NagayaDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Soichiro TatsuoDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Tatsuya MikamiInnovation Center for Health Promotion, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.
Yoshinori TamadaDepartment of Medical Data Intelligence, Research Center for Health-Medical Data Science, Graduate School of Medicine, Hirosaki University, 5 Zaifu-cho, Hirosaki, Aomori, 036-8562, Japan.
Satoru IdeDepartment of Radiology, School of Medicine, University of Occupational and Environmental Health, 1-1, Iseigaoka, Yahatanishi-Ku Kitakyushu, Fukuoka, 807-8555, Japan.
Masahiko TomiyamaDepartment of Neurology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-cho, Hirosaki, Aomori, 036-8562, Japan.
Shingo KakedaDepartment of Radiology, Graduate School of Medicine, Hirosaki University, 5 Zaifu-Cho, Hirosaki, Aomori, 036-8562, Japan.

Funding

AMED JP16dk0207025Japan Agency for Medical Research and Development JP21dk0207053JSPS KAKENHI 24K10915
6 · The paper itself

Abstract

purposePrevious research indicates brain network alterations in the default mode network (DMN), salience network (SN), and central-executive network (CEN) in individuals with mild cognitive impairment (MCI). However, replication has been inconsistent due to small, varied samples. We aimed to explore intra- and inter-networks alternations among DMN, SN, and CEN in individuals with MCI using multivariate source-based morphometry (SBM) with a larger, population-based sample. MATERIALS AND

methodsThis cross-sectional study included 1,997 participants (median age: 69 years; 61.9% female) who underwent three-dimensional (3D) T1-weighed imaging with 3 T magnetic resonance imaging (MRI). They were classified into 1,236 healthy controls (HC) and 761 individuals with MCI. SBM was used to extract triple brain networks as structural networks, and Z-scores were calculated. Intra-network comparisons of DMN, SN, and CEN between HC and MCI groups were conducted using logistic regression analysis. Inter-network comparisons among the triple brain networks were performed using structural equation modeling (SEM).

resultsConnectivity (median Z score) of each network was lower in the MCI group than in the HC group: DMN (0.08 vs. - 0.12), SN (0.08 vs. - 0.23), and CEN (0.07 vs. - 0.06). Logistic regression showed significant association of SN connectivity with MCI (odds ratio 0.862, p < 0.05). SEM analysis revealed a significant group difference in the model where SN mediated input from CEN to DMN.

conclusionWe found altered network patterns in individuals with mild cognitive impairment, suggesting a transformation in network connectivity among DMN, SN, and CEN, particularly compensating for degraded SN connectivity.

Indexed as

BrainCognitive DysfunctionMagnetic Resonance ImagingNerve NetAgedAged, 80 and overCross-Sectional StudiesDefault Mode NetworkFemaleHumansImaging, Three-DimensionalMaleMiddle AgedBrain networksMagnetic resonance imagingMild cognitive impairmentSource-based morphometryStructural network

Identifiers

PMID40531396
PMCPMC12397200

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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.