Evidence map›Paper›PMID 42761967›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2026

Brain-age in ultra-low-field MRI: How well does it work?

Francesca Biondo, Carly Bennallick, Sophie A Martin, Lemuel Puglisi, Thomas C Booth, David A Wood, Juan Eugenio Iglesias, František Váša, James H Cole

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 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

5 · Who and what money

Authors and funding

9 authors.

Francesca BiondoUCL Hawkes Institute, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0001-9952-0249
Carly BennallickDepartment of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0009-0007-6822-777X
Sophie A MartinUCL Hawkes Institute, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0003-3819-1634
Lemuel PuglisiUniversity of Catania, Catania, Italy.ORCID https://orcid.org/0009-0003-5661-9873
Thomas C BoothSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-0984-3998
David A WoodSchool of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-3058-4871
Juan Eugenio IglesiasUCL Hawkes Institute, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0001-7569-173X
František VášaDepartment of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-6744-7139
James H ColeUCL Hawkes Institute, UCL, London, United Kingdom.ORCID https://orcid.org/0000-0003-1908-5588

Funding

Bill & Melinda Gates Foundation INV-005774Bill & Melinda Gates Foundation INV-032788Wellcome Trust
6 · The paper itself

Abstract

Brain-age estimates the brain's biological age from neuroimaging data and has been proposed as a biomarker of brain health and disease risk. While brain-age estimation commonly uses high-field (HF) magnetic resonance imaging (MRI) (

Indexed as

AgingBrainMagnetic Resonance ImagingNeuroimagingAdultAgedFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedReproducibility of ResultsYoung Adultbrain-ageFreeSurferlow field MRIopen datastructural MRISynthSR

Identifiers

PMID42761967
PMCPMC13588316

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.