O De Wel1, S Van Huffel1, M Lavanga1, K Jansen2,3, A Dereymaeker3, J Dudink4, L Gui5, P S Hüppi5, L S de Vries4, G Naulaers3, M J N L Benders4, M L Tataranno6,7. 1. Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium. 2. Department of Development and Regeneration, University Hospitals Leuven, Neonatal Intensive Care Unit & Child Neurology, KU Leuven, Leuven, Belgium. 3. Department of Development and Regeneration, University Hospitals Leuven, Neonatal Intensive Care Unit, KU Leuven, Leuven, Belgium. 4. Department of Neonatology, UMC Brain Center, Wilhelmina Children's Hospital, Utrecht, The Netherlands. 5. Division of Development and Growth, Department of Pediatrics, Obstetrics & Gynaecology, University of Geneva, Geneva, Switzerland. 6. Department of Neonatology, UMC Brain Center, Wilhelmina Children's Hospital, Utrecht, The Netherlands. m.l.tataranno-2@umcutrecht.nl. 7. Department of Neonatology, University Medical Center Utrecht, KH.03.418.1, PO Box KE.04.123.1, Utrecht, The Netherlands. m.l.tataranno-2@umcutrecht.nl.
Abstract
BACKGROUND: Recent studies explored the relationship between early brain function and brain morphology, based on the hypothesis that increased brain activity can positively affect structural brain development and that excitatory neuronal activity stimulates myelination. OBJECTIVE: To investigate the relationship between maturational features from early and serial aEEGs after premature birth and MRI metrics characterizing structural brain development and injury, measured around 30weeks postmenstrual age (PMA) and at term. Moreover, we aimed to verify whether previously developed maturational EEG features are related with PMA. DESIGN/ METHODS: One hundred six extremely preterm infants received bedside aEEGs during the first 72h and weekly until week 5. 3T-MRIs were performed at 30weeks PMA and at term. Specific features were extracted to assess EEG maturation: (1) the spectral content, (2) the continuity [percentage of spontaneous activity transients (SAT%) and the interburst interval (IBI)], and (3) the complexity. Automatic MRI segmentation to assess volumes and MRI score was performed. The relationship between the maturational EEG features and MRI measures was investigated. RESULTS: Both SAT% and EEG complexity were correlated with PMA. IBI was inversely associated with PMA. Complexity features had a positive correlation with the cerebellar size at 30weeks, while event-based measures were related to the cerebellar size at term. Cerebellar width, cortical grey matter, and total brain volume at term were inversely correlated with the relative power in the higher frequency bands. CONCLUSIONS: The continuity and complexity of the EEG steadily increase with increasing postnatal age. Increasing complexity and event-based features are associated with cerebellar size, a structure with enormous development during preterm life. Brain activity is important for later structural brain development.
BACKGROUND: Recent studies explored the relationship between early brain function and brain morphology, based on the hypothesis that increased brain activity can positively affect structural brain development and that excitatory neuronal activity stimulates myelination. OBJECTIVE: To investigate the relationship between maturational features from early and serial aEEGs after premature birth and MRI metrics characterizing structural brain development and injury, measured around 30weeks postmenstrual age (PMA) and at term. Moreover, we aimed to verify whether previously developed maturational EEG features are related with PMA. DESIGN/ METHODS: One hundred six extremely preterm infants received bedside aEEGs during the first 72h and weekly until week 5. 3T-MRIs were performed at 30weeks PMA and at term. Specific features were extracted to assess EEG maturation: (1) the spectral content, (2) the continuity [percentage of spontaneous activity transients (SAT%) and the interburst interval (IBI)], and (3) the complexity. Automatic MRI segmentation to assess volumes and MRI score was performed. The relationship between the maturational EEG features and MRI measures was investigated. RESULTS: Both SAT% and EEG complexity were correlated with PMA. IBI was inversely associated with PMA. Complexity features had a positive correlation with the cerebellar size at 30weeks, while event-based measures were related to the cerebellar size at term. Cerebellar width, cortical grey matter, and total brain volume at term were inversely correlated with the relative power in the higher frequency bands. CONCLUSIONS: The continuity and complexity of the EEG steadily increase with increasing postnatal age. Increasing complexity and event-based features are associated with cerebellar size, a structure with enormous development during preterm life. Brain activity is important for later structural brain development.
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