Dataset Information

Automated cot-side tracking of functional brain age in preterm infants.

ABSTRACT:

Objective

A major challenge in the care of preterm infants is the early identification of compromised neurological development. While several measures are routinely used to track anatomical growth, there is a striking lack of reliable and objective tools for tracking maturation of early brain function; a cornerstone of lifelong neurological health. We present a cot-side method for measuring the functional maturity of the newborn brain based on routinely available neurological monitoring with electroencephalography (EEG).

Methods

We used a dataset of 177 EEG recordings from 65 preterm infants to train a multivariable prediction of functional brain age (FBA) from EEG. The FBA was validated on an independent set of 99 EEG recordings from 42 preterm infants. The difference between FBA and postmenstrual age (PMA) was evaluated as a predictor for neurodevelopmental outcome.

Results

The FBA correlated strongly with the PMA of an infant, with a median prediction error of less than 1 week. Moreover, individual babies follow well-defined individual trajectories. The accuracy of the FBA applied to the validation set was statistically equivalent to the training set accuracy. In a subgroup of infants with repeated EEG recordings, a persistently negative predicted age difference was associated with poor neurodevelopmental outcome.

Interpretation

The FBA enables the tracking of functional neurodevelopment in preterm infants. This establishes proof of principle for growth charts for brain function, a new tool to assist clinical management and identify infants who will benefit most from early intervention.

SUBMITTER: Stevenson NJ

PROVIDER: S-EPMC7318094 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Automated cot-side tracking of functional brain age in preterm infants.

Stevenson Nathan J NJ Oberdorfer Lisa L Tataranno Maria-Luisa ML Breakspear Michael M Colditz Paul B PB de Vries Linda S LS Benders Manon J N L MJNL Klebermass-Schrehof Katrin K Vanhatalo Sampsa S Roberts James A JA

Annals of clinical and translational neurology 20200505 6

<h4>Objective</h4>A major challenge in the care of preterm infants is the early identification of compromised neurological development. While several measures are routinely used to track anatomical growth, there is a striking lack of reliable and objective tools for tracking maturation of early brain function; a cornerstone of lifelong neurological health. We present a cot-side method for measuring the functional maturity of the newborn brain based on routinely available neurological monitoring ...[more]

PMID: 32368863

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Project description:BackgroundSeizures are underrecognized in preterm infants, and little is known about their impact on brain growth. We aimed to define the association between early seizures and subsequent brain growth.MethodsInfants <30 weeks gestation underwent 72 h of prospective amplitude-integrated electroencephalography (aEEG) monitoring, term-equivalent age (TEA) magnetic resonance imaging (MRI), and 2-year neurodevelopmental testing. Seizures were defined as trains of sharp waves >10 s, evolving in frequency/amplitude/morphology, and identified using automated algorithms with manual review. Using T2-weighted images, cortical surface area (CSA) and gyrification index (GI) were calculated and volumes were segmented into five tissue classes: cerebrospinal fluid, gray matter, white matter (WM), deep nuclear gray matter, and cerebellum. Correlations between total seizure burden and tissue-specific volumes were evaluated, controlling for clinical variables of interest.ResultsNinety-nine infants underwent aEEG/MRI assessments (mean GA = 26.3 weeks, birthweight = 899 g). Seizure incidence was 55% with a median of two events; median length = 66 s and mean burden = 285 s. Greater seizure burden was associated with smaller CSA and volumes across all tissue types, most prominently in WM (R2 = -0.603, p < 0.01), even after controlling for confounders. There was no association with GI.ConclusionsSeizures in preterm infants are common and associated with smaller TEA brain volumes. This relationship was strongest for WM and independent of clinical factors.ImpactSeizures in preterm infants are common. Little is known about the association between early seizures and later brain growth. Greater seizure burden is linked with smaller volumes of all brain tissue types, most prominently the WM. This relationship is true even controlling for other factors. Additional study is needed to identify the optimal EEG monitoring and seizure treatment strategy for improved brain growth and neurodevelopmental outcomes.

Project description:Preterm birth is associated with dysconnectivity of structural brain networks and is a leading cause of neurocognitive impairment in childhood. Variation in DNA methylation is associated with early exposure to extrauterine life but there has been little research exploring its relationship with brain development. Using genome-wide DNA methylation data from the saliva of 258 neonates, we investigated the impact of gestational age on the methylome and performed functional analysis to identify enriched gene sets from probes that contributed to differentially methylated probes or regions. We tested the hypothesis that variation in DNA methylation could underpin the association between low gestational age at birth and atypical brain development by linking differentially methylated probes with measures of white matter connectivity derived from diffusion MRI metrics: peak width skeletonized mean diffusivity, peak width skeletonized fractional anisotropy and peak width skeletonized neurite density index. Gestational age at birth was associated with widespread differential methylation at term equivalent age, with genome-wide significant associations observed for 8870 CpG probes (P < 3.6 × 10-8) and 1767 differentially methylated regions. Functional analysis identified 14 enriched gene ontology terms pertaining to cell-cell contacts and cell-extracellular matrix contacts. Principal component analysis of probes with genome-wide significance revealed a first principal component that explained 23.5% of the variance in DNA methylation, and this was negatively associated with gestational age at birth. The first principal component was associated with peak width of skeletonized mean diffusivity (β = 0.349, P = 8.37 × 10-10) and peak width skeletonized neurite density index (β = 0.364, P = 4.15 × 10-5), but not with peak width skeletonized fraction anisotropy (β = -0.035, P = 0.510); these relationships mirrored the imaging metrics' associations with gestational age at birth. Low gestational age at birth has a profound and widely distributed effect on the neonatal saliva methylome that is apparent at term equivalent age. Enriched gene ontology terms related to cell-cell contacts reveal pathways that could mediate the effect of early life environmental exposures on development. Finally, associations between differential DNA methylation and image markers of white matter tract microstructure suggest that variation in DNA methylation may provide a link between preterm birth and the dysconnectivity of developing brain networks that characterizes atypical brain development in preterm infants.

Project description:BackgroundThe use of functional connectivity magnetic resonance imaging (fcMRI) in research involving preterm infants is relatively new, and its feasibility in this population is not fully established. However, fcMRI images reveal functional neural connections that may be useful in establishing the mechanisms of neuroprotective interventions in preterm infants.ObjectiveThe aim of this study was to determine the feasibility of using fcMRI to measure differences in functional neural connections in nursing intervention studies.MethodsA pilot study was conducted as part of a longitudinal, randomized controlled trial (RCT) testing the effect of a feeding intervention on neurodevelopmental and clinical outcomes of preterm infants randomly assigned to one of two groups: a patterned feeding experience (PFE) group and a usual feeding care (UFC) group. The fcMRIs were done at term-equivalent age. Visual, motor, and default mode networks were analyzed.ResultsSeven infants were studied (four were in the PFE group, and three were in the UFC group). Participants were selected sequentially from the parent RCT. Clear images were obtained from all participants. Differences were noted among PFE and UFC infants: Infants receiving PFE were hyperconnective in the default mode (caudate, anterior cingulate cortex, and precuneus) and motor networks (middle temporal and middle occipital areas) and hypoconnective in others areas of the default mode (hippocampal and lingual regions) and motor networks (precentral and superior frontal cortices) relative to UFC infants. No differences were noted in visual networks.DiscussionThe feasibility of using fcMRI at term-equivalent age in preterm infants who participated in an RCT on the effect of a nursing intervention was shown. Differences in connectivity among infants by group were detected. Further research is needed to show the benefit of fcMRI in studies of preterm infants given the costs of the procedure as well as the uncertain relationship of this early outcome measure to long-term neurodevelopment.

Dataset Information

Automated cot-side tracking of functional brain age in preterm infants.

Objective

Methods

Results

Interpretation

Publications

Automated cot-side tracking of functional brain age in preterm infants.

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