Evidence map›Paper›PMID 41695756›Full record

ArticleBrain communications2026

Mapping heterogeneous region- and tissue-specific brain ageing patterns using quantitative MRI.

Xinjie Chen, Mario Ocampo-Pineda, Po-Jui Lu, Michelle G Jansen, Kwok-Shing Chan, Marcel Zwiers, Joukje M Oosterman, David G Norris, Andre F Marquand, Lester Melie-Garcia and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Brain communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Xinjie ChenTranslational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, 4123 Allschwil, Switzerland.ORCID https://orcid.org/0000-0002-3683-6489
Mario Ocampo-PinedaTranslational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, 4123 Allschwil, Switzerland.
Po-Jui LuTranslational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, 4123 Allschwil, Switzerland.
Michelle G JansenDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, The Netherlands.
Kwok-Shing ChanAthinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129, USA.
Marcel ZwiersDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, The Netherlands.
Joukje M OostermanDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, The Netherlands.
David G NorrisDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, The Netherlands.
Andre F MarquandDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, The Netherlands.
Lester Melie-GarciaTranslational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, 4123 Allschwil, Switzerland.
Cristina GranzieraTranslational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, 4123 Allschwil, Switzerland.ORCID https://orcid.org/0000-0002-4917-8761
José P MarquesDonders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN, Nijmegen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain ageing involves microstructural changes that vary across tissue types and even within regions of those tissues, leading to functional and cognitive alterations. Quantitative MRI (qMRI) offers sensitivity to tissue properties, enabling the identification of differential ageing patterns and distinguishing physiological ageing from pathological changes. In this study, we analysed qMRI data from 293 healthy adults (median age: 52; interquartile range: 36-66; age range: 18-79 years). We applied a multiparametric qMRI approach, including longitudinal relaxation rate (

Indexed as

age modellingbrain ageinghealthy ageingmultiparametric MRInormative model

Identifiers

PMID41695756
PMCPMC12895350

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.