Evidence map›Paper›PMID 41425259›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Contrasting neonatal brain morphometry and its impact on neurodevelopmental outcome between preterm birth and congenital heart disease.

Siân Wilson, Barat Gal-Er, Daniel Cromb, Alexandra F Bonthrone, Andrew Chew, Kuberan Pushparajah, John Simpson, Shona Falconer, Joseph V Hajnal, Tomoki Arichi and 5 more

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

15 authors.

Siân WilsonResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-4617-3583
Barat Gal-ErResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Daniel CrombResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Alexandra F BonthroneResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Andrew ChewResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Kuberan PushparajahResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
John SimpsonDepartment of Cardiovascular Imaging, King's College London, London, United Kingdom.
Shona FalconerResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Joseph V HajnalResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Tomoki ArichiResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Mary RutherfordResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Chiara NosartiResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
A David EdwardsResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Jonathan O'MuircheartaighResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Serena J CounsellResearch Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Congenital heart disease (CHD) and prematurity are leading causes of infant mortality and morbidity. Both groups of infants share certain common neurological sequalae, such as increased risk of neonatal brain injury and neurodevelopmental impairments later in life, leading to hypotheses that there may be shared underlying structural differences in the infant brain. However, there is no empirical evidence to support this, and our objective with this study was to compare and contrast neonatal brain structure between at-risk infant groups, then analyse their relationship with neurodevelopmental outcome. We carried out a retrospective, longitudinal, case-control analysis of 602 T2-weighted infant brain MRIs, acquired between 37 and 44 weeks postmenstrual age (PMA). The cohort comprised early preterm (n = 60), late preterm (n = 67), infants with congenital heart disease (CHD; n = 116), and term-born controls from the Developing Human Connectome Project (n = 360). We analyse structural covariance networks, a data-driven extraction of co-maturing neuroanatomical structures, capturing the variation in brain morphometry for each infant. We found distinct structural profiles in CHD and preterm infants, with minimal overlap observed between groups. A subset (n = 428) returned for neurodevelopmental follow-up at 18-24 months, and we explored the association with Bayley-III cognitive and motor scores. We found that variation in neonatal brain morphology is a significant predictor of toddler neurodevelopment in preterm infants and controls, but this association is absent in CHD. These findings suggest divergent neurobiological pathways may underlie adverse outcomes in these high-risk infants.

Indexed as

congenital heart diseasemorphometryMRIneurodevelopmentprematurity

Identifiers

PMID41425259
PMCPMC12713110

What OpenQuestion holds

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Read underepoch 390

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.