Structural connectivity relates to perinatal factors and functional impairment at 7years in children born very
Deanne K Thompson1, Jian Chen2, Richard Beare2
1Murdoch Childrens Research Institute, 50 Flemington Road, Parkville, VIC 3052, Australia; Florey Institute of Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, 50 Flemington Road, Parkville, VIC 3052, Australia.
Insights
Children born very preterm exhibit less complex brain networks compared to full-term peers. Perinatal factors impact white matter connectivity, affecting cognitive and motor functions in these children.
Area of Science:
- Neuroscience
- Developmental Biology
- Medical Imaging
Background:
- Very preterm birth is associated with neurodevelopmental challenges.
- Understanding brain network development in preterm infants is crucial for early intervention.
Purpose of the Study:
- Compare brain networks in very preterm and typically developing children.
- Investigate links between perinatal factors and brain networks.
- Correlate brain network characteristics with functional impairments in preterm children.
Main Methods:
- Utilized T1 and diffusion-weighted imaging in 7-year-olds (107 very preterm, 26 full-term).
- Constructed global white matter fiber networks using advanced tractography.
- Analyzed graph theory metrics and regional networks, assessing cognitive and motor function.
Main Results:
- Very preterm children showed reduced network density and global efficiency, but higher local efficiency.
- Lower gestational age, infection, and neonatal brain abnormalities correlated with reduced connectivity.
- Widespread network connectivity predicted IQ, while parietal/temporal lobe connectivity related to motor skills.
Conclusions:
- Children born very preterm have less connected and complex brain networks than term-born children.
- Adverse perinatal factors disrupt white matter connectivity, impacting functional outcomes.
- Established novel structure-function relationships in very preterm children's neurodevelopment.
Objective:
To use structural connectivity to (1) compare brain networks between typically and atypically developing (very preterm) children, (2) explore associations between potential perinatal developmental disturbances and brain networks, and (3) describe associations between brain networks and functional impairments in very preterm children.
Methods:
26 full-term and 107 very preterm 7-year-old children (born <30weeks' gestational age and/or <1250g) underwent T1- and diffusion-weighted imaging. Global white matter fibre networks were produced using 80 cortical and subcortical nodes, and edges were created using constrained spherical deconvolution-based tractography. Global graph theory metrics were analysed, and regional networks were identified using network-based statistics. Cognitive and motor function were assessed at 7years of age.
Results:
Compared with full-term children, very preterm children had reduced density, lower global efficiency and higher local efficiency. Those with lower gestational age at birth, infection or higher neonatal brain abnormality score had reduced connectivity. Reduced connectivity within a widespread network was predictive of impaired IQ, while reduced connectivity within the right parietal and temporal lobes was associated with motor impairment in very preterm children.
Conclusions:
This study utilised an innovative structural connectivity pipeline to reveal that children born very preterm have less connected and less complex brain networks compared with typically developing term-born children. Adverse perinatal factors led to disturbances in white matter connectivity, which in turn are associated with impaired functional outcomes, highlighting novel structure-function relationships.
