Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/119305
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Type: Journal article
Title: Early life predictors of brain development at term-equivalent age in infants born across the gestational age spectrum
Author: Thompson, D.K.
Kelly, C.E.
Chen, J.
Beare, R.
Alexander, B.
Seal, M.L.
Lee, K.
Matthews, L.G.
Anderson, P.J.
Doyle, L.W.
Spittle, A.J.
Cheong, J.L.
Citation: NeuroImage, 2019; 185:813-824
Publisher: Elsevier
Issue Date: 2019
ISSN: 1053-8119
1095-9572
Statement of
Responsibility: 
Deanne K.Thompson, Claire E.Kelly, Jian Chen, Richard Beare, Bonnie Alexander, Marc L.Seal, Katherine Lee, Lillian G.Matthew, Peter J.Anderson, Lex W.Doyle, Alicia J.Spittle, Jeanie L.Y.Cheong
Abstract: Background: It is well established that preterm infants have altered brain development compared with full-term (FT; ≥37 weeks' gestational age [GA]) infants, however the perinatal factors associated with brain development in preterm infants have not been fully elucidated. In particular, perinatal predictors of brain development may differ between very preterm infants (VP; <32 weeks' GA) and infants born moderate (MP; 32–33 weeks' GA) and late (LP; 34–36 weeks' GA) preterm, but this has not been studied. This study aimed to investigate the effects of early life predictors on brain volume and microstructure at term-equivalent age (TEA; 38–44 weeks), and whether these effects differ for GA groups (VP, MP, LP or FT). Methods: Structural images from 328 infants (91 VP, 63 MP, 104 LP and 70 FT) were segmented into white matter, cortical grey matter, cerebrospinal fluid, subcortical grey matter, brainstem and cerebellum. Cortical grey matter and white matter images were analysed using voxel-based morphometry. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 361 infants (92 VP, 69 MP, 120 LP and 80 FT) were analysed using Tract-Based Spatial Statistics. Relationships between early life predictors (birthweight standard deviation score [BWSDS], multiple birth, sex, postnatal growth and social risk) and global brain volumes were analysed using linear regressions. Relationships between early life predictors and regional brain volumes and diffusion measures were analysed using voxelwise non-parametric permutation testing. Results: Male sex was associated with higher global volumes of all tissues and higher regional volumes throughout much of the cortical grey matter and white matter, particularly in the FT group. Male sex was also associated with lower FA and higher AD, RD and MD in the optic radiation, external and internal capsules and corona radiata, and these associations were generally similar between GA groups. Higher BWSDS was associated with higher global volumes of all tissues and higher regional volumes in much of the cortical grey matter and white matter in all GA groups, as well as higher FA and lower RD and MD in many major tracts (corpus callosum, optic radiation, internal and external capsules and corona radiata), particularly in the MP and LP groups. Multiple birth and social risk also showed associations with global and regional volumes and regional diffusion values which varied by GA group, but these associations were not independent of the other early life predictors. Postnatal growth was not associated with brain volumes or diffusion values. Conclusion: Early life predictors of brain volumes and microstructure at TEA include sex, BWSDS, multiple birth and social risk, which have different effects based on GA group at birth. This study improves knowledge of the perinatal factors associated with brain abnormalities in infants born across the prematurity spectrum.
Rights: © 2018 Elsevier Inc. All rights reserved.
RMID: 0030116852
DOI: 10.1016/j.neuroimage.2018.04.031
Grant ID: http://purl.org/au-research/grants/nhmrc/1028822
http://purl.org/au-research/grants/nhmrc/1024516
http://purl.org/au-research/grants/nhmrc/546519
http://purl.org/au-research/grants/nhmrc/1060733
http://purl.org/au-research/grants/nhmrc/1081288
http://purl.org/au-research/grants/nhmrc/1053787
http://purl.org/au-research/grants/nhmrc/1053767
http://purl.org/au-research/grants/nhmrc/1012236
http://purl.org/au-research/grants/nhmrc/1108714
http://purl.org/au-research/grants/nhmrc/1085754
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