Accelerated Small-World Property of Structural Brain Networks in Preterm Infants at Term-Equivalent Age

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Background: The prediction of neurodevelopmental outcomes in preterm infants is one of the clinical challenges of pediatrics. Despite the recent interest in brain development and white matter connectivity using a network-based analysis, very little is known about the brain network of at term-equivalent age in preterm infants. Objective: We aimed to investigate the structural brain network using diffusion MRI following preterm delivery at term-equivalent age compared with term infants and explored the influence of gestational age (GA) and clinical factors. Method: Diffusion tensor imaging data were acquired prospectively from 55 preterm neonates without apparent brain abnormalities (mean gestational age: 29.43 weeks) and 21 full-term infants at term-equivalent age. The global structural brain networks were produced by probabilistic white matter tractography in combination with the Johns Hopkins University neonate atlas to quantify connectivity between different cortical regions. Results: Compared with full-term infants, preterm infants had significantly lower global efficiency (p = 0.048) and increased small worldness (p = 0.012) after correcting for sex and age at MRI scan. The increased small worldness in the brain network at term-equivalent age was significantly linearly correlated with lower GA after adjusting for sex and the effects of postmenstrual age at MRI scan on the data in preterm infants (β = -0.020, p = 0.037). In multivariate analysis, infants with chronic lung disease had significantly decreased changes in clustering (p = 0.014) and local efficiency (p = 0.027). Conclusion: The accelerated small worldness in preterm infants suggests that the structural brain network after preterm birth is reorganized in maximizing integrated and segregated processing, implying resilience against prematurity-associated pathology.

Original languageEnglish
Pages (from-to)99-107
Number of pages9
JournalNeonatology
Volume115
Issue number2
DOIs
StatePublished - 2019 Feb 1

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Premature Infants
Brain
Gestational Age
Magnetic Resonance Imaging
Newborn Infant
Diffusion Magnetic Resonance Imaging
Diffusion Tensor Imaging
Atlases
Age Factors
Premature Birth
Lung Diseases
Cluster Analysis
Chronic Disease
Multivariate Analysis
Pediatrics
Pathology

Keywords

  • Clinical variables
  • Connectivity networks
  • Diffusion tensor imaging
  • Gestational age
  • Preterm infants

Cite this

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title = "Accelerated Small-World Property of Structural Brain Networks in Preterm Infants at Term-Equivalent Age",
abstract = "Background: The prediction of neurodevelopmental outcomes in preterm infants is one of the clinical challenges of pediatrics. Despite the recent interest in brain development and white matter connectivity using a network-based analysis, very little is known about the brain network of at term-equivalent age in preterm infants. Objective: We aimed to investigate the structural brain network using diffusion MRI following preterm delivery at term-equivalent age compared with term infants and explored the influence of gestational age (GA) and clinical factors. Method: Diffusion tensor imaging data were acquired prospectively from 55 preterm neonates without apparent brain abnormalities (mean gestational age: 29.43 weeks) and 21 full-term infants at term-equivalent age. The global structural brain networks were produced by probabilistic white matter tractography in combination with the Johns Hopkins University neonate atlas to quantify connectivity between different cortical regions. Results: Compared with full-term infants, preterm infants had significantly lower global efficiency (p = 0.048) and increased small worldness (p = 0.012) after correcting for sex and age at MRI scan. The increased small worldness in the brain network at term-equivalent age was significantly linearly correlated with lower GA after adjusting for sex and the effects of postmenstrual age at MRI scan on the data in preterm infants (β = -0.020, p = 0.037). In multivariate analysis, infants with chronic lung disease had significantly decreased changes in clustering (p = 0.014) and local efficiency (p = 0.027). Conclusion: The accelerated small worldness in preterm infants suggests that the structural brain network after preterm birth is reorganized in maximizing integrated and segregated processing, implying resilience against prematurity-associated pathology.",
keywords = "Clinical variables, Connectivity networks, Diffusion tensor imaging, Gestational age, Preterm infants",
author = "Lee, {Joo Young} and Park, {Hyun Kyung} and Lee, {Hyun Ju}",
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Accelerated Small-World Property of Structural Brain Networks in Preterm Infants at Term-Equivalent Age. / Lee, Joo Young; Park, Hyun Kyung; Lee, Hyun Ju.

In: Neonatology, Vol. 115, No. 2, 01.02.2019, p. 99-107.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Accelerated Small-World Property of Structural Brain Networks in Preterm Infants at Term-Equivalent Age

AU - Lee, Joo Young

AU - Park, Hyun Kyung

AU - Lee, Hyun Ju

PY - 2019/2/1

Y1 - 2019/2/1

N2 - Background: The prediction of neurodevelopmental outcomes in preterm infants is one of the clinical challenges of pediatrics. Despite the recent interest in brain development and white matter connectivity using a network-based analysis, very little is known about the brain network of at term-equivalent age in preterm infants. Objective: We aimed to investigate the structural brain network using diffusion MRI following preterm delivery at term-equivalent age compared with term infants and explored the influence of gestational age (GA) and clinical factors. Method: Diffusion tensor imaging data were acquired prospectively from 55 preterm neonates without apparent brain abnormalities (mean gestational age: 29.43 weeks) and 21 full-term infants at term-equivalent age. The global structural brain networks were produced by probabilistic white matter tractography in combination with the Johns Hopkins University neonate atlas to quantify connectivity between different cortical regions. Results: Compared with full-term infants, preterm infants had significantly lower global efficiency (p = 0.048) and increased small worldness (p = 0.012) after correcting for sex and age at MRI scan. The increased small worldness in the brain network at term-equivalent age was significantly linearly correlated with lower GA after adjusting for sex and the effects of postmenstrual age at MRI scan on the data in preterm infants (β = -0.020, p = 0.037). In multivariate analysis, infants with chronic lung disease had significantly decreased changes in clustering (p = 0.014) and local efficiency (p = 0.027). Conclusion: The accelerated small worldness in preterm infants suggests that the structural brain network after preterm birth is reorganized in maximizing integrated and segregated processing, implying resilience against prematurity-associated pathology.

AB - Background: The prediction of neurodevelopmental outcomes in preterm infants is one of the clinical challenges of pediatrics. Despite the recent interest in brain development and white matter connectivity using a network-based analysis, very little is known about the brain network of at term-equivalent age in preterm infants. Objective: We aimed to investigate the structural brain network using diffusion MRI following preterm delivery at term-equivalent age compared with term infants and explored the influence of gestational age (GA) and clinical factors. Method: Diffusion tensor imaging data were acquired prospectively from 55 preterm neonates without apparent brain abnormalities (mean gestational age: 29.43 weeks) and 21 full-term infants at term-equivalent age. The global structural brain networks were produced by probabilistic white matter tractography in combination with the Johns Hopkins University neonate atlas to quantify connectivity between different cortical regions. Results: Compared with full-term infants, preterm infants had significantly lower global efficiency (p = 0.048) and increased small worldness (p = 0.012) after correcting for sex and age at MRI scan. The increased small worldness in the brain network at term-equivalent age was significantly linearly correlated with lower GA after adjusting for sex and the effects of postmenstrual age at MRI scan on the data in preterm infants (β = -0.020, p = 0.037). In multivariate analysis, infants with chronic lung disease had significantly decreased changes in clustering (p = 0.014) and local efficiency (p = 0.027). Conclusion: The accelerated small worldness in preterm infants suggests that the structural brain network after preterm birth is reorganized in maximizing integrated and segregated processing, implying resilience against prematurity-associated pathology.

KW - Clinical variables

KW - Connectivity networks

KW - Diffusion tensor imaging

KW - Gestational age

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SP - 99

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JO - Neonatology

JF - Neonatology

SN - 1661-7800

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