Evidence map›Paper›PMID 39450739›Full record

ArticleJournal of the American Heart Association2024

Structural Covariance Networks in the Fetal Brain Reveal Altered Neurodevelopment for Specific Subtypes of Congenital Heart Disease.

Siân Wilson, Daniel Cromb, Alexandra F Bonthrone, Alena Uus, Anthony Price, Alexia Egloff, Milou P M Van Poppel, Johannes K Steinweg, Kuberan Pushparajah, John Simpson and 7 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

17 authors.

Siân WilsonResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0003-4617-3583
Daniel CrombResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0002-9814-8841
Alexandra F BonthroneResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0001-5487-5564
Alena UusResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.
Anthony PriceResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.
Alexia EgloffResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.
Milou P M Van PoppelBiomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0002-1739-4726
Johannes K SteinwegBiomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0002-3366-0932
Kuberan PushparajahBiomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0003-1541-1155
John SimpsonBiomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.
David F A LloydBiomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0003-1759-6106
Reza RazaviBiomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0003-1065-3008
Jonathan O'MuircheartaighResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0002-8033-6959
A David EdwardsResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0003-4801-7066
Joseph V HajnalResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.
Mary RutherfordResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0003-3361-1337
Serena J CounsellResearch Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences King's College London London United Kingdom.ORCID 0000-0002-8033-5673

Funding

Medical Research Council MR/V002465/1Wellcome Trust
6 · The paper itself

Abstract

backgroundAltered structural brain development has been identified in fetuses with congenital heart disease (CHD), suggesting that the neurodevelopmental impairment observed later in life might originate in utero. There are many interacting factors that may perturb neurodevelopment during the fetal period and manifest as structural brain alterations, such as altered cerebral substrate delivery and aberrant fetal hemodynamics. METHODS AND

resultsWe extracted structural covariance networks from the log Jacobian determinants of 435 in utero T2 weighted image magnetic resonance imaging scans, (n=67 controls, 368 with CHD) acquired during the third trimester. We fit general linear models to test whether age, sex, expected cerebral substrate delivery, and CHD diagnosis were significant predictors of structural covariance. We identified significant effects of age, sex, cerebral substrate delivery, and specific CHD diagnosis across a variety of structural covariance networks, including primary motor and sensory cortices, cerebellar regions, frontal cortex, extra-axial cerebrospinal fluid, thalamus, brainstem, and insula, consistent with widespread coordinated aberrant maturation of specific brain regions over the third trimester.

conclusionsStructural covariance networks offer a sensitive, data-driven approach to explore whole-brain structural changes without anatomical priors. We used them to stratify a heterogenous patient cohort with CHD, highlighting similarities and differences between diagnoses during fetal neurodevelopment. Although there was a clear effect of abnormal fetal hemodynamics on structural brain maturation, our results suggest that this alone does not explain all the variation in brain development between individuals with CHD.

Indexed as

BrainHeart Defects, CongenitalMagnetic Resonance ImagingAdultCase-Control StudiesFemaleFetal DevelopmentHumansMaleNeurodevelopmental DisordersPregnancyPregnancy Trimester, Thirdbraincongenital heart diseasefetalmagnetic resonance imaging

Identifiers

PMID39450739
PMCPMC11935691

What OpenQuestion holds

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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 OpenQuestion graph.