Relationship between Proton Magnetic Resonance Spectroscopy of Frontoinsular Gray Matter and Neurodevelopmental Outcomes in Very Low Birth Weight Children at the Age of 4.
Wojciech DurlakIzabela Herman-SucharskaAndrzej UrbanikMałgorzata KlimekPaulina KarczGrażyna DutkowskaMagdalena NiteckaPrzemko KwintaPublished in: PloS one (2016)
Very low birth weight is associated with long term neurodevelopmental complications. Macroscopic brain abnormalities in prematurity survivors have been investigated in several studies. However, there is limited data regarding local cerebral metabolic status and neurodevelopmental outcomes. The purpose of this study was to characterize the relationship between proton magnetic resonance spectra in basal ganglia, frontal white matter and frontoinsular gray matter, neurodevelopmental outcomes assessed with the Leiter scale and the Developmental Test of Visual Perception and selected socioeconomic variables in a cohort of very low birth weight children at the age of four. Children were divided in three groups based on the severity of neurodevelopmental impairment. There were no differences in spectroscopy in basal ganglia and frontal white matter between the groups. Lower concentrations of N-acetylaspartate (NAA), choline (Cho) and myoinositol (mI) were observed in the frontoinsular cortex of the left hemisphere in children with neurodevelopmental impairment compared to children with normal neurodevelopmental outcomes. Higher parental education, daycare attendance and breastfeeding after birth were associated with more favorable neurodevelopmental prognosis, whereas rural residence was more prevalent in children with moderate and severe impairment. Our study demonstrates the role of long term neurometabolic disruption in the left frontoinsular cortex and selected socioeconomic variables in determination of neurodevelopmental prognosis in prematurity survivors.
Keyphrases
- low birth weight
- preterm infants
- young adults
- white matter
- human milk
- magnetic resonance
- preterm birth
- functional connectivity
- congenital heart disease
- machine learning
- skeletal muscle
- high resolution
- risk factors
- pregnant women
- mass spectrometry
- high intensity
- resting state
- artificial intelligence
- subarachnoid hemorrhage
- density functional theory
- big data
- deep learning
- tandem mass spectrometry
- solid state
- data analysis