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Neuroimage. 2016 Jan 15;125:456-478. doi: 10.1016/j.neuroimage.2015.10.047. Epub 2015 Oct 21.

Regional growth and atlasing of the developing human brain.

Author information

1
Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, United Kingdom; Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London SE1 7EH, United Kingdom.
2
Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London SE1 7EH, United Kingdom.
3
Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, United Kingdom.
4
Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London SE1 7EH, United Kingdom; Clinic of Pediatrics I, Department of Neonatology, University Hospital Essen, D-45122 Essen, Germany.
5
Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London SE1 7EH, United Kingdom. Electronic address: serena.counsell@kcl.ac.uk.

Abstract

Detailed morphometric analysis of the neonatal brain is required to characterise brain development and define neuroimaging biomarkers related to impaired brain growth. Accurate automatic segmentation of neonatal brain MRI is a prerequisite to analyse large datasets. We have previously presented an accurate and robust automatic segmentation technique for parcellating the neonatal brain into multiple cortical and subcortical regions. In this study, we further extend our segmentation method to detect cortical sulci and provide a detailed delineation of the cortical ribbon. These detailed segmentations are used to build a 4-dimensional spatio-temporal structural atlas of the brain for 82 cortical and subcortical structures throughout this developmental period. We employ the algorithm to segment an extensive database of 420 MR images of the developing brain, from 27 to 45weeks post-menstrual age at imaging. Regional volumetric and cortical surface measurements are derived and used to investigate brain growth and development during this critical period and to assess the impact of immaturity at birth. Whole brain volume, the absolute volume of all structures studied, cortical curvature and cortical surface area increased with increasing age at scan. Relative volumes of cortical grey matter, cerebellum and cerebrospinal fluid increased with age at scan, while relative volumes of white matter, ventricles, brainstem and basal ganglia and thalami decreased. Preterm infants at term had smaller whole brain volumes, reduced regional white matter and cortical and subcortical grey matter volumes, and reduced cortical surface area compared with term born controls, while ventricular volume was greater in the preterm group. Increasing prematurity at birth was associated with a reduction in total and regional white matter, cortical and subcortical grey matter volume, an increase in ventricular volume, and reduced cortical surface area.

PMID:
26499811
PMCID:
PMC4692521
DOI:
10.1016/j.neuroimage.2015.10.047
[Indexed for MEDLINE]
Free PMC Article

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