Neonatal brain network integration trajectories predict neurodevelopment in congenital heart disease

Background Infants with critical congenital heart disease (CHD) are at high risk for abnormal brain development and later neurodevelopmental impairment. We hypothesized that the trajectory of perioperative whole-brain network development would predict neurodevelopmental outcomes in early childhood. Methods This prospective longitudinal cohort of neonates with critical CHD ( n = 97) underwent preoperative and/or postoperative brain MRI with diffusion imaging. Whole-brain network measures were derived from structural connectomes from 80 infants, and 50 had neurodevelopment assessed at 1–4 years using the Bayley Scales of Infant and Toddler Development. Results White matter injury was associated with a slower perioperative increase in global efficiency ( p = 0.013), a measure of network integration, whereas cardiac physiology was not associated with network development. Infants with greater perioperative increases in global efficiency had higher cognitive ( p = 0.001), language ( p < 0.001), and motor ( p = 0.008) scores. For each 1-standard deviation increase in the trajectory of global efficiency, cognitive scores increased by 8.2 points (95% CI: 3.64–12.78), independent of brain injury and socioeconomic factors. Conclusion In infants with critical CHD, longitudinal whole-brain network development was associated with neurodevelopment across multiple domains. Early network development may serve as a biomarker of neurodevelopmental risk and resilience in this population. Impact In infants with critical congenital heart disease, perioperative increase in whole-brain network integration was associated with cognitive, language, and motor outcomes in early childhood. White matter injury was associated with a slower increase in network integration, whereas cardiac physiology subtype was not associated with network development. This study extends prior work by showing that a longitudinal measure of neonatal whole-brain network development, rather than a single imaging timepoint, predicts neurodevelopment across multiple domains. These findings identify early network development as a potential biomarker of neurodevelopmental risk and resilience, and support future risk-stratification and intervention studies in this population.