Evidence map›Paper›PMID 37060450›Full record

ArticleEuropean radiology2023

Aging-related volume changes in the brain and cerebrospinal fluid using artificial intelligence-automated segmentation.

Shigeki Yamada, Tomohiro Otani, Satoshi Ii, Hiroto Kawano, Kazuhiko Nozaki, Shigeo Wada, Marie Oshima, Yoshiyuki Watanabe

Open access · hybridAbstract read
In one paragraph

Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
7.4field-weighted citation impact, top 2% of its field
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

33 citing papers in PubMed, 50 citations in OpenAlex.

  1. Trial
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  6. Ventricular CSF-to-blood water transport kinetics in adult hydrocephalus.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
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  18. Plasma protein risk scores for mild cognitive impairment and Alzheimer's disease in the Framingham heart study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
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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

8 authors at 4 institutions in 1 country.

Shigeki YamadaDepartment of Neurosurgery, Nagoya City University Graduate School of Medical Science, 1 Kawasumi, Mizuho-cho, Mizuho-ku, NagoyaNagoya, Aichi, 467-8601, Japan. shigekiyamada393@gmail.com.ORCID http://orcid.org/0000-0001-7158-5569
Tomohiro OtaniDepartment of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan.
Satoshi IiFaculty of System Design, Tokyo Metropolitan University, Hachioji, Tokyo, Japan.
Hiroto KawanoDepartment of Neurosurgery, Shiga University of Medical Science, Ōtsu, Shiga, Japan.
Kazuhiko NozakiDepartment of Neurosurgery, Shiga University of Medical Science, Ōtsu, Shiga, Japan.
Shigeo WadaDepartment of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan.
Marie OshimaInterfaculty Initiative in Information Studies / Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.
Yoshiyuki WatanabeDepartment of Radiology, Shiga University of Medical Science, Ōtsu, Shiga, Japan.
Shiga University of Medical Science · JPThe University of Osaka · JPThe University of Tokyo · JPTokyo Metropolitan University · JP

Funding

Japan Society for the Promotion of Science London 21K09098Japan Society for the Promotion of Science London 22H00190Japan Society for the Promotion of Science London 22H03020Japan Society for the Promotion of Science London 22K09289
6 · The paper itself

Abstract

objectivesTo verify the reliability of the volumes automatically segmented using a new artificial intelligence (AI)-based application and evaluate changes in the brain and CSF volume with healthy aging.

methodsThe intracranial spaces were automatically segmented in the 21 brain subregions and 5 CSF subregions using the AI-based application on the 3D T1-weighted images in healthy volunteers aged > 20 years. Additionally, the automatically segmented volumes of the total ventricles and subarachnoid spaces were compared with the manually segmented volumes of those extracted from 3D T2-weighted images using the intra-class correlation and Bland-Altman analysis.

resultsIn this study, 133 healthy volunteers aged 21-92 years were included. The mean intra-class correlations between the automatically and manually segmented volumes of the total ventricles and subarachnoid spaces were 0.986 and 0.882, respectively. The increase in the CSF volume was estimated to be approximately 30 mL (2%) per decade from 265 mL (18.7%) in the 20s to 488 mL (33.7%) in ages above 80 years; however, the increase in the volume of total ventricles was approximately 20 mL (< 2%) until the 60s and increased in ages above 60 years.

conclusionsThis study confirmed the reliability of the CSF volumes using the AI-based auto-segmentation application. The intracranial CSF volume increased linearly because of the brain volume reduction with aging; however, the ventricular volume did not change until the age of 60 years and above and then gradually increased. This finding could help elucidate the pathogenesis of chronic hydrocephalus in adults. KEY POINTS: • The brain and CSF spaces were automatically segmented using an artificial intelligence-based application. • The total subarachnoid spaces increased linearly with aging, whereas the total ventricle volume was around 20 mL (< 2%) until the 60s and increased in ages above 60 years. • The cortical gray matter gradually decreases with aging, whereas the subcortical gray matter maintains its volume, and the cerebral white matter increases slightly until the 40s and begins to decrease from the 50s.

Indexed as

Artificial IntelligenceMagnetic Resonance ImagingAdultAgingBrainCerebrospinal FluidHumansReproducibility of ResultsAgingArtificial intelligenceCerebral ventricleCerebrospinal fluidSubarachnoid space

Identifiers

PMID37060450
PMCPMC10511609
OpenAlexW4365811226

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.