Evidence map›Paper›PMID 41730874›Full record

ArticleNature communications2026

Normative growth trajectories of fetal brain regions validated by satisfactory maturation of neurodevelopmental domains at 2 years of age.

Madeleine K Wyburd, Stephen H Kennedy, Michelle Fernandes, Nicola K Dinsdale, Linde S Hesse, Robert B Gunier, Leila Cheikh Ismail, Eric O Ohuma, Michael G Gravett, Manorama Purwar and 16 more

Abstract read
In one paragraph

Article in Nature communications, 2026. 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

26 authors.

Madeleine K Wyburd *Oxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, United Kingdom. madeleine.wyburd@cs.ox.ac.uk.ORCID http://orcid.org/0000-0003-0991-3204
Stephen H Kennedy *Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0003-0135-9317
Michelle FernandesNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0002-0051-3389
Nicola K DinsdaleOxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, United Kingdom.
Linde S HesseOxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, United Kingdom.
Robert B GunierSchool of Public Health, University of California, Berkeley, CA, United States of America.ORCID http://orcid.org/0000-0001-5485-9919
Leila Cheikh IsmailDepartment of Clinical Nutrition and Dietetics, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates.
Eric O OhumaFaculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID http://orcid.org/0000-0002-3116-2593
Michael G GravettDepartments of Obstetrics and Gynecology and of Global Health, University of Washington, Seattle, WA, United States of America.
Manorama PurwarNagpur INTERGROWTH-21st Research Centre, Ketkar Hospital, Nagpur, India.
Wu QingqingSchool of Public Health, Peking University, Beijing, China.
Adele WinseyNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.
Enrico BertinoDipartimento di Scienze Pediatriche e dell'Adolescenza, SCDU Neonatologia, Universita di Torino, Turin, Italy.
Yasmin JafferDepartment of Family and Community Health, Ministry of Health, Muscat, Sultanate of Oman.
Maria CarvalhoDepartment of Obstetrics and Gynaecology, Faculty of Health Sciences, Aga Khan University Hospital, Nairobi, Kenya.ORCID http://orcid.org/0000-0002-2371-890X
Fernando C BarrosPost-graduate Course in Health in the Life Cycle, Universidade Católica de Pelotas, Pelotas, Brazil.
Alan SteinBlavatnik School of Government, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0001-8207-2822
Alison J NobleDepartment of Engineering Science, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0002-3060-3772
Zoltán MolnárDepartment of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0002-6852-6004
Mark JenkinsonOxford Centre for Integrative Neuroimaging (OxCIN), FMRIB Centre, Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford, JR Hospital, Oxford, United Kingdom.ORCID http://orcid.org/0000-0001-6043-0166
Thomas E NicholsOxford Centre for Integrative Neuroimaging (OxCIN), FMRIB Centre, Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford, JR Hospital, Oxford, United Kingdom.ORCID http://orcid.org/0000-0002-4516-5103
Stephen SmithOxford Centre for Integrative Neuroimaging (OxCIN), FMRIB Centre, Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford, JR Hospital, Oxford, United Kingdom.
Zulfiqar A BhuttaCenter for Global Child Health, Hospital for Sick Children, Toronto, Ontario, Canada.ORCID http://orcid.org/0000-0003-0637-599X
Aris T PapageorghiouNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0001-8143-2232
Jose VillarNuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, United Kingdom.ORCID http://orcid.org/0000-0002-2834-4038
Ana I L NambureteOxford Machine Learning in Neuroimaging Laboratory, Department of Computer Science, University of Oxford, Oxford, United Kingdom. ana.namburete@cs.ox.ac.uk.ORCID http://orcid.org/0000-0002-9119-436X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We previously constructed a qualitative, 3D ultrasound derived atlas of the normative spatiotemporal dynamics of fetal brain maturation. Here, using the same healthy multi-national cohort, we applied deep learning methods to 4205 fetal brain scans from 18-27 weeks' gestation, to produce an extensive, quantitative description of the growth of 16 fetal brain structures associated with satisfactory domain-specific neurodevelopmental scores at 2 years of age. The methodology, which is publicly available, takes less than 10 seconds per scan. We define 28 region-specific, functionally relevant, normative growth trajectories, a ratio between the relative volumes of the insular (rILV) and parietal (rPLV) lobes reflecting asynchronous maturation of fetal brain regions, and introduce a fetal brain maturation index that quantifies biological age and deviations from chronological age. Finally, the very low percentage of variance explained by between site differences (0.6% to 5.8% of the total variance) reinforces a fundamental biological principle: fetal growth and development across populations with diverse ancestries is similar provided that environmental constraints on growth are minimal.

Indexed as

BrainFetal DevelopmentFetusChild, PreschoolDeep LearningFemaleGestational AgeHumansNeurodevelopmentPregnancyUltrasonography, Prenatal

Identifiers

PMID41730874
PMCPMC13040065

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.