Evidence map›Paper›PMID 26740912›Full record

ArticleNeuroImage. Clinical2015

Automatic segmentation of the hippocampus for preterm neonates from early-in-life to term-equivalent age.

Ting Guo, Julie L Winterburn, Jon Pipitone, Emma G Duerden, Min Tae M Park, Vann Chau, Kenneth J Poskitt, Ruth E Grunau, Anne Synnes, Steven P Miller and 1 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
7.5field-weighted citation impact, top 4% of its field
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

17 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Early Procedural Pain Is Associated with Regionally-Specific Alterations in Thalamic Development in Preterm Neonates.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018
    Article
  15. Article
  16. Article
  17. 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 at 4 institutions in 1 country.

Ting GuoNeurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
Julie L WinterburnInstitute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; Kimel Family Translational Imaging, Genetics Research Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.
Jon PipitoneInstitute of Medical Science, University of Toronto, Toronto, ON, Canada; Kimel Family Translational Imaging, Genetics Research Laboratory, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada.
Emma G DuerdenNeurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
Min Tae M ParkSchulich School of Medicine and Dentistry, Western University, London, ON, Canada; Cerebral Imaging Centre, Douglas Mental Health Research Institute, Verdun, QC, Canada.
Vann ChauNeurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
Kenneth J PoskittDepartment of Pediatrics, University of British Columbia and Child and Family Research Institute, Vancouver, BC, Canada.
Ruth E GrunauDepartment of Pediatrics, University of British Columbia and Child and Family Research Institute, Vancouver, BC, Canada.
Anne SynnesDepartment of Pediatrics, University of British Columbia and Child and Family Research Institute, Vancouver, BC, Canada.
Steven P MillerNeurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Paediatrics, The Hospital for Sick Children and the University of Toronto, Toronto, ON, Canada.
M Mallar ChakravartyInstitute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; Cerebral Imaging Centre, Douglas Mental Health Research Institute, Verdun, QC, Canada; Department of Psychiatry, McGill University, Montreal, QC, Canada.
University of Toronto · CAUniversity of British Columbia · CACentre for Addiction and Mental Health · CAWestern University · CA

Funding

Canadian Institutes of Health Research MOP-79262Canadian Institutes of Health Research MOP-86489
6 · The paper itself

Abstract

introductionThe hippocampus, a medial temporal lobe structure central to learning and memory, is particularly vulnerable in preterm-born neonates. To date, segmentation of the hippocampus for preterm-born neonates has not yet been performed early-in-life (shortly after birth when clinically stable). The present study focuses on the development and validation of an automatic segmentation protocol that is based on the MAGeT-Brain (Multiple Automatically Generated Templates) algorithm to delineate the hippocampi of preterm neonates on their brain MRIs acquired at not only term-equivalent age but also early-in-life.

methodsFirst, we present a three-step manual segmentation protocol to delineate the hippocampus for preterm neonates and apply this protocol on 22 early-in-life and 22 term images. These manual segmentations are considered the gold standard in assessing the automatic segmentations. MAGeT-Brain, automatic hippocampal segmentation pipeline, requires only a small number of input atlases and reduces the registration and resampling errors by employing an intermediate template library. We assess the segmentation accuracy of MAGeT-Brain in three validation studies, evaluate the hippocampal growth from early-in-life to term-equivalent age, and study the effect of preterm birth on the hippocampal volume. The first experiment thoroughly validates MAGeT-Brain segmentation in three sets of 10-fold Monte Carlo cross-validation (MCCV) analyses with 187 different groups of input atlases and templates. The second experiment segments the neonatal hippocampi on 168 early-in-life and 154 term images and evaluates the hippocampal growth rate of 125 infants from early-in-life to term-equivalent age. The third experiment analyzes the effect of gestational age (GA) at birth on the average hippocampal volume at early-in-life and term-equivalent age using linear regression.

resultsThe final segmentations demonstrate that MAGeT-Brain consistently provides accurate segmentations in comparison to manually derived gold standards (mean Dice's Kappa > 0.79 and Euclidean distance <1.3 mm between centroids). Using this method, we demonstrate that the average volume of the hippocampus is significantly different (p < 0.0001) in early-in-life (621.8 mm(3)) and term-equivalent age (958.8 mm(3)). Using these differences, we generalize the hippocampal growth rate to 38.3 ± 11.7 mm(3)/week and 40.5 ± 12.9 mm(3)/week for the left and right hippocampi respectively. Not surprisingly, younger gestational age at birth is associated with smaller volumes of the hippocampi (p = 0.001).

conclusionsMAGeT-Brain is capable of segmenting hippocampi accurately in preterm neonates, even at early-in-life. Hippocampal asymmetry with a larger right side is demonstrated on early-in-life images, suggesting that this phenomenon has its onset in the 3rd trimester of gestation. Hippocampal volume assessed at the time of early-in-life and term-equivalent age is linearly associated with GA at birth, whereby smaller volumes are associated with earlier birth.

Indexed as

Infant, PrematureAlgorithmsFemaleGestational AgeHippocampusHumansImage Processing, Computer-AssistedInfant, NewbornMagnetic Resonance ImagingMaleMonte Carlo MethodReproducibility of ResultsEarly-in-lifeHippocampusMAGeT-BrainMRIPreterm neonatesSegmentation

Identifiers

PMID26740912
PMCPMC4561668
OpenAlexW1186717344

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.