Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/119204
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Type: Journal article
Title: Characterisation of brain volume and microstructure 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.J.
Matthews, L.G.
Anderson, P.J.
Doyle, L.W.
Cheong, J.L.Y.
Spittle, A.J.
Citation: NeuroImage: Clinical, 2019; 21:654-663
Publisher: Elsevier
Issue Date: 2019
ISSN: 2213-1582
2213-1582
Statement of
Responsibility: 
Deanne K.Thompson, Claire E.Kelly Jian Chen, Richard Beare, Bonnie Alexander, Marc L.Seal, Katherine J.Lee, Lillian G.Matthews, Peter J.Anderson, Lex W.Doyle, Jeanie L.Y.Cheong, Alicia J.Spittle
Abstract: Background: Risk of morbidity differs between very preterm (VP; <32 weeks' gestational age (GA)), moderate preterm (MP; 32–33 weeks' GA), late preterm (LP; 34–36 weeks' GA), and full-term (FT; ≥37 weeks' GA) infants. However, brain structure at term-equivalent age (TEA; 38–44 weeks) remains to be characterised in all clinically important GA groups. We aimed to compare global and regional brain volumes, and regional white matter microstructure, between VP, MP, LP and FT groups at TEA, in order to establish the magnitude and anatomical locations of between-group differences. 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 (CSF), subcortical grey matter, brainstem and cerebellum. Global tissue volumes were analysed, and additionally, cortical grey matter and white matter volumes were analysed at the regional level 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. Statistical analyses involved examining the overall effect of GA group on global volumes (using linear regressions) and regional volumes and microstructure (using non-parametric permutation testing), as well performing post-hoc comparisons between the GA sub-groups. Results: On global analysis, cerebrospinal fluid (CSF) volume was larger in all preterm sub-groups compared with the FT group. On regional analysis, volume was smaller in parts of the temporal cortical grey matter, and parts of the temporal white matter and corpus callosum, in all preterm sub-groups compared with the FT group. FA was lower, and RD and MD were higher in voxels located in much of the white matter in all preterm sub-groups compared with the FT group. The anatomical locations of group differences were similar for each preterm vs. FT comparison, but the magnitude and spatial extent of group differences was largest for the VP, followed by the MP, and then the LP comparison. Comparing within the preterm groups, the VP sub-group had smaller frontal and temporal grey and white matter volume, and lower FA and higher MD and RD within voxels in the approximate location of the corpus callosum compared with the MP sub-group. There were few volume and microstructural differences between the MP and LP sub-groups. Conclusion: All preterm sub-groups had atypical brain volume and microstructure at TEA when compared with a FT group, particularly for the CSF, temporal grey and white matter, and corpus callosum. In general, the groups followed a gradient, where the differences were most pronounced for the VP group, less pronounced for the MP group, and least pronounced for the LP group. The VP sub-group was particularly vulnerable compared with the MP and LP sub-groups.
Keywords: Magnetic resonance imaging; diffusion weighted imaging; preterm; premature birth; neonate
Rights: © 2018 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
DOI: 10.1016/j.nicl.2018.101630
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/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
http://purl.org/au-research/grants/nhmrc/546519
http://purl.org/au-research/grants/nhmrc/1060733
Published version: http://dx.doi.org/10.1016/j.nicl.2018.101630
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