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Published on: November 20, 2015
Association between brain structural network efficiency at term-equivalent age and early development of cerebral
Julia E Kline1, Weihong Yuan2, Karen Harpster3
1Perinatal Institute, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave, MLC 7009, Cincinnati, OH 45229, United States.
Insights
Brain network efficiency metrics at term-equivalent age can predict cerebral palsy (CP) risk in very preterm infants. Decreased network segregation in motor and non-motor regions indicates higher CP risk, enabling earlier interventions.
Area of Science:
- Neuroscience
- Developmental Pediatrics
- Medical Imaging
Background:
- Very preterm infants (born < 32 weeks gestational age) face high risks for motor impairments like cerebral palsy (CP).
- Early brain network changes preceding CP development in infants are not well understood, hindering timely risk stratification and intervention.
- Advanced neuroimaging techniques are needed to identify subtle pathophysiological alterations indicative of CP risk.
Purpose of the Study:
- To investigate the pathophysiology of early cerebral palsy (CP) development in very preterm infants before interventions.
- To identify sensitive biomarkers for CP risk using graph theoretical analysis of brain connectomes.
- To explore the relationship between brain network organization and CP diagnosis in preterm infants.
Main Methods:
- Structural and diffusion MRI were acquired at term-equivalent age in 395 very preterm infants.
- Cortical morphometrics and brain volumes were extracted from structural MRI.
- Graph theoretical methods were applied to diffusion MRI-derived brain connectomes to analyze network organization and efficiency.
Main Results:
- Graph network metrics, including global efficiency and sensorimotor tract strength, were inversely associated with CP diagnosis.
- Decreased local efficiency in motor and novel non-motor regions was linked to early CP diagnosis.
- These associations remained significant after correcting for common motor development risk factors.
Conclusions:
- Brain network efficiency metrics at term-equivalent age serve as sensitive biomarkers for predicting CP risk in very preterm infants.
- Reduced brain network segregation, including in non-motor regions, precedes CP diagnosis and may relate to cognitive impairments.
- Advanced MRI biomarkers can aid in identifying high-risk infants for earlier, targeted interventions.
Abstract:
Very preterm infants (born at less than 32 weeks gestational age) are at high risk for serious motor impairments, including cerebral palsy (CP). The brain network changes that antecede the early development of CP in infants are not well characterized, and a better understanding may suggest new strategies for risk-stratification at term, which could lead to earlier access to therapies. Graph theoretical methods applied to diffusion MRI-derived brain connectomes may help quantify the organization and information transfer capacity of the preterm brain with greater nuance than overt structural or regional microstructural changes. Our aim was to shed light on the pathophysiology of early CP development, before the occurrence of early intervention therapies and other environmental confounders, to help identify the best early biomarkers of CP risk in VPT infants. In a cohort of 395 very preterm infants, we extracted cortical morphometrics and brain volumes from structural MRI and also applied graph theoretical methods to diffusion MRI connectomes, both acquired at term-equivalent age. Metrics from graph network analysis, especially global efficiency, strength values of the major sensorimotor tracts, and local efficiency of the motor nodes and novel non-motor regions were strongly inversely related to early CP diagnosis. These measures remained significantly associated with CP after correction for common risk factors of motor development, suggesting that metrics of brain network efficiency at term may be sensitive biomarkers for early CP detection. We demonstrate for the first time that in VPT infants, early CP diagnosis is anteceded by decreased brain network segregation in numerous nodes, including motor regions commonly-associated with CP and also novel regions that may partially explain the high rate of cognitive impairments concomitant with CP diagnosis. These advanced MRI biomarkers may help identify the highest risk infants by term-equivalent age, facilitating earlier interventions that are informed by early pathophysiological changes.
