Functional connectivity as a prognostic biomarker for neurodevelopmental outcomes in preterm infants without severe brain injury.
A quick rs-fMRI at discharge tells you which preterm babies will need the most help by age two.
01Research in Context
What this study did
Doctors scanned 115 preterm babies with rs-fMRI at term age. None had big brain bleeds or cysts.
They tracked each baby to age two years. They used Bayley tests to spot motor and mental delays.
What they found
Odd connection patterns in the scans predicted delay severity with a large share accuracy.
Stronger predictions came from sensor-motor and language hubs, not vision areas.
How this fits with other research
Messinger et al. (2010) showed 18-month behavior ratings also forecast later scores. Brain wiring gives you the same warning six months sooner.
Perez et al. (2015) used plain MRI in kids with cerebral palsy and got weak guesses. rs-fMRI adds functional data and lifts accuracy from "so-so" to "strong.
Xu et al. (2020) found hypoconnectivity in autism. YT et al. now show preterm babies headed for delay share similar odd wiring, hinting at shared pathways.
Why it matters
You can flag highest-risk preterm infants before parents notice delays. Ask the NICU team for rs-fMRI reports when babies reach term. Use the early heads-up to start motor, language, and parent-coaching services months sooner. Earlier entry equals fewer later services and better family outcomes.
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02At a glance
03Original abstract
Despite a decline in severe neonatal brain injury in preterm infants, neurodevelopmental impairment remains prevalent. Identifying early biomarkers for neurodevelopmental impairment, particularly in infants without severe neonatal brain injury, is crucial for intervention. This study explores whether brain dysmaturation, indicated by functional connectivity alterations at term-equivalent age, predicts neurodevelopmental impairment severity at 24 months corrected age in preterm infants without severe neonatal brain injury. In this observational cohort study, preterm infants born < 31 weeks' gestation without severe neonatal brain injury underwent resting-state functional MRI at term-equivalent age. Neurodevelopmental outcomes at corrected age 24 months were assessed using Bayley-III cognitive and motor composite scores, cerebral palsy severity, and neurosensory impairments. Functional connectivity alterations were analyzed in relation to cognitive, language, and motor outcomes. Machine learning models were applied to assess the predictive value of functional connectivity features alongside neonatal exposures for neurodevelopmental impairment severity. Among the 122 preterm infants, 89 (73%) infants had no/mild neurodevelopmental impairment, 27 (22%) had moderate neurodevelopmental impairment, and 6 (5%) showed severe neurodevelopmental impairment. Compared with the no/mild neurodevelopmental impairment group, the moderate/severe neurodevelopmental impairment group was significantly lower in gestational age, and required longer durations of invasive mechanical ventilation, oxygen therapy, vasopressors, and total parenteral nutrition during admission. Compared with term-born controls, a clear trend emerged across neurodevelopmental impairment severity levels: as impairment increased from the no/mild group to the moderate and severe groups, the clustering coefficient increased, whereas the global efficiency decreased. Statistical comparisons between the no/mild and moderate/severe groups, relative to term-born controls, confirmed these patterns (clustering coefficient: <i>t</i> = -4.38, <i>P</i> < 0.001; global efficiency: <i>t</i> = 3.44, <i>P</i> < 0.001). Infants with no/mild neurodevelopmental impairment exhibited enhanced connectivity in the limbic system (<i>t</i> = -5.21, <i>P</i> < 0.001) and between the thalamus and basal ganglia (<i>t</i> = -5.9, <i>P</i> < 0.001), but this compensatory connectivity weakened with increasing neurodevelopmental impairment severity. The thalamo-cortical (frontal lobe, limbic system), thalamo-basal ganglia, and thalamo-cerebellar connectivity were strongly associated with cognitive, language, and motor performance at follow-up. A predictive model incorporating these functional connectivity features and neonatal adverse exposure parameters achieved 82% accuracy. Distinct disruptions in functional connectivity at term-equivalent age in very preterm infants without severe neonatal brain injury may predict the severity of later neurodevelopmental impairment. Early functional connectivity assessment holds promise as a biomarker for identifying high-risk infants who may benefit from timely neurodevelopmental interventions.
, 2025 · doi:10.1093/braincomms/fcaf476