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Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging

BACKGROUND: It remains unclear whether very preterm (VP) infants have the same level of brain structure and function as full-term (FT) infants. In addition, the relationship between potential differences in brain white matter microstructure and network connectivity and specific perinatal factors has...

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Autores principales: Liu, Ying, Nie, Binbin, Wang, Yituo, He, Fang, Ma, Qiaozhi, Han, Tao, Mao, Guangjuan, Liu, Jiqiang, Zu, Haiping, Mu, Xuetao, Wu, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101202/
https://www.ncbi.nlm.nih.gov/pubmed/37065913
http://dx.doi.org/10.3389/fnins.2023.1137559
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author Liu, Ying
Nie, Binbin
Wang, Yituo
He, Fang
Ma, Qiaozhi
Han, Tao
Mao, Guangjuan
Liu, Jiqiang
Zu, Haiping
Mu, Xuetao
Wu, Bing
author_facet Liu, Ying
Nie, Binbin
Wang, Yituo
He, Fang
Ma, Qiaozhi
Han, Tao
Mao, Guangjuan
Liu, Jiqiang
Zu, Haiping
Mu, Xuetao
Wu, Bing
author_sort Liu, Ying
collection PubMed
description BACKGROUND: It remains unclear whether very preterm (VP) infants have the same level of brain structure and function as full-term (FT) infants. In addition, the relationship between potential differences in brain white matter microstructure and network connectivity and specific perinatal factors has not been well characterized. OBJECTIVE: This study aimed to investigate the existence of potential differences in brain white matter microstructure and network connectivity between VP and FT infants at term-equivalent age (TEA) and examine the potential association of these differences with perinatal factors. METHODS: A total of 83 infants were prospectively selected for this study: 43 VP infants (gestational age, or GA: 27–32 weeks) and 40 FT infants (GA: 37–44 weeks). All infants at TEA underwent both conventional magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Significant differences in white matter fractional anisotropy (FA) and mean diffusivity (MD) images between the VP and FT groups were observed using tract-based spatial statistics (TBSS). The fibers were tracked between each pair of regions in the individual space, using the automated anatomical labeling (AAL) atlas. Then, a structural brain network was constructed, where the connection between each pair of nodes was defined by the number of fibers. Network-based statistics (NBS) were used to examine differences in brain network connectivity between the VP and FT groups. Additionally, multivariate linear regression was conducted to investigate potential correlations between fiber bundle numbers and network metrics (global efficiency, local efficiency, and small-worldness) and perinatal factors. RESULTS: Significant differences in FA were observed between the VP and FT groups in several regions. These differences were found to be significantly associated with perinatal factors such as bronchopulmonary dysplasia (BPD), activity, pulse, grimace, appearance, respiratory (APGAR) score, gestational hypertension, and infection. Significant differences in network connectivity were observed between the VP and FT groups. Linear regression results showed significant correlations between maternal years of education, weight, the APGAR score, GA at birth, and network metrics in the VP group. CONCLUSIONS: The findings of this study shed light on the influence of perinatal factors on brain development in VP infants. These results may serve as a basis for clinical intervention and treatment to improve the outcome of preterm infants.
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spelling pubmed-101012022023-04-14 Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging Liu, Ying Nie, Binbin Wang, Yituo He, Fang Ma, Qiaozhi Han, Tao Mao, Guangjuan Liu, Jiqiang Zu, Haiping Mu, Xuetao Wu, Bing Front Neurosci Neuroscience BACKGROUND: It remains unclear whether very preterm (VP) infants have the same level of brain structure and function as full-term (FT) infants. In addition, the relationship between potential differences in brain white matter microstructure and network connectivity and specific perinatal factors has not been well characterized. OBJECTIVE: This study aimed to investigate the existence of potential differences in brain white matter microstructure and network connectivity between VP and FT infants at term-equivalent age (TEA) and examine the potential association of these differences with perinatal factors. METHODS: A total of 83 infants were prospectively selected for this study: 43 VP infants (gestational age, or GA: 27–32 weeks) and 40 FT infants (GA: 37–44 weeks). All infants at TEA underwent both conventional magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Significant differences in white matter fractional anisotropy (FA) and mean diffusivity (MD) images between the VP and FT groups were observed using tract-based spatial statistics (TBSS). The fibers were tracked between each pair of regions in the individual space, using the automated anatomical labeling (AAL) atlas. Then, a structural brain network was constructed, where the connection between each pair of nodes was defined by the number of fibers. Network-based statistics (NBS) were used to examine differences in brain network connectivity between the VP and FT groups. Additionally, multivariate linear regression was conducted to investigate potential correlations between fiber bundle numbers and network metrics (global efficiency, local efficiency, and small-worldness) and perinatal factors. RESULTS: Significant differences in FA were observed between the VP and FT groups in several regions. These differences were found to be significantly associated with perinatal factors such as bronchopulmonary dysplasia (BPD), activity, pulse, grimace, appearance, respiratory (APGAR) score, gestational hypertension, and infection. Significant differences in network connectivity were observed between the VP and FT groups. Linear regression results showed significant correlations between maternal years of education, weight, the APGAR score, GA at birth, and network metrics in the VP group. CONCLUSIONS: The findings of this study shed light on the influence of perinatal factors on brain development in VP infants. These results may serve as a basis for clinical intervention and treatment to improve the outcome of preterm infants. Frontiers Media S.A. 2023-03-30 /pmc/articles/PMC10101202/ /pubmed/37065913 http://dx.doi.org/10.3389/fnins.2023.1137559 Text en Copyright © 2023 Liu, Nie, Wang, He, Ma, Han, Mao, Liu, Zu, Mu and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Liu, Ying
Nie, Binbin
Wang, Yituo
He, Fang
Ma, Qiaozhi
Han, Tao
Mao, Guangjuan
Liu, Jiqiang
Zu, Haiping
Mu, Xuetao
Wu, Bing
Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging
title Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging
title_full Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging
title_fullStr Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging
title_full_unstemmed Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging
title_short Correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging
title_sort correlation of abnormal brain changes with perinatal factors in very preterm infants based on diffusion tensor imaging
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101202/
https://www.ncbi.nlm.nih.gov/pubmed/37065913
http://dx.doi.org/10.3389/fnins.2023.1137559
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