Evidence map›Paper›PMID 27242423›Full record

ArticleFrontiers in neuroscience2016

Parcellation of the Healthy Neonatal Brain into 107 Regions Using Atlas Propagation through Intermediate Time Points in Childhood.

Manuel Blesa, Ahmed Serag, Alastair G Wilkinson, Devasuda Anblagan, Emma J Telford, Rozalia Pataky, Sarah A Sparrow, Gillian Macnaught, Scott I Semple, Mark E Bastin and 1 more

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Observational
  2. A detailed spatiotemporal atlas of the white matter tracts for the fetal brain.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Article
  4. Article
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  6. White matter tract crossing and bottleneck regions in the fetal brain.bioRxiv : the preprint server for biology · 2024
    Article
  7. Article
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  10. Review
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  12. Article
  13. Article
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  15. Article
  16. Article
  17. Article
  18. Article
  19. A Multi-Atlas Label Fusion Tool for Neonatal Brain MRI Parcellation and Quantification.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2019
    Article
  20. 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

11 authors.

Manuel BlesaMRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK.
Ahmed SeragMRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK.
Alastair G WilkinsonDepartment of Radiology, Royal Hospital for Sick Children Edinburgh, UK.
Devasuda AnblaganMRC Centre for Reproductive Health, University of EdinburghEdinburgh, UK; Centre for Clinical Brain Sciences, University of EdinburghEdinburgh, UK.
Emma J TelfordMRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK.
Rozalia PatakyMRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK.
Sarah A SparrowMRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK.
Gillian MacnaughtClinical Research Imaging Centre, University of Edinburgh Edinburgh, UK.
Scott I SempleClinical Research Imaging Centre, University of Edinburgh Edinburgh, UK.
Mark E BastinCentre for Clinical Brain Sciences, University of Edinburgh Edinburgh, UK.
James P BoardmanMRC Centre for Reproductive Health, University of EdinburghEdinburgh, UK; Centre for Clinical Brain Sciences, University of EdinburghEdinburgh, UK.

Funding

Medical Research Council G0701127Medical Research Council MR/K026992/1
6 · The paper itself

Abstract

Neuroimage analysis pipelines rely on parcellated atlases generated from healthy individuals to provide anatomic context to structural and diffusion MRI data. Atlases constructed using adult data introduce bias into studies of early brain development. We aimed to create a neonatal brain atlas of healthy subjects that can be applied to multi-modal MRI data. Structural and diffusion 3T MRI scans were acquired soon after birth from 33 typically developing neonates born at term (mean postmenstrual age at birth 39(+5) weeks, range 37(+2)-41(+6)). An adult brain atlas (SRI24/TZO) was propagated to the neonatal data using temporal registration via childhood templates with dense temporal samples (NIH Pediatric Database), with the final atlas (Edinburgh Neonatal Atlas, ENA33) constructed using the Symmetric Group Normalization (SyGN) method. After this step, the computed final transformations were applied to T2-weighted data, and fractional anisotropy, mean diffusivity, and tissue segmentations to provide a multi-modal atlas with 107 anatomical regions; a symmetric version was also created to facilitate studies of laterality. Volumes of each region of interest were measured to provide reference data from normal subjects. Because this atlas is generated from step-wise propagation of adult labels through intermediate time points in childhood, it may serve as a useful starting point for modeling brain growth during development.

Indexed as

atlasbrainMRIneonatalparcellation

Identifiers

PMID27242423
PMCPMC4871889

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.