Abstract

In neonates with hypoxic ischemic encephalopathy, the computation of wavelet coherence between electroencephalogram (EEG) power and regional cerebral oxygen saturation (rSO2) is a promising method for the assessment of neurovascular coupling (NVC), which in turn is a promising marker for brain injury. However, instabilities in arterial oxygen saturation (SpO2) limit the robustness of previously proposed methods. Therefore, we propose the use of partial wavelet coherence, which can eliminate the influence of SpO2. Furthermore, we study the added value of the novel NVC biomarkers for identification of brain injury compared to traditional EEG and NIRS biomarkers. 18 neonates with HIE were monitored for 72 h and classified into three groups based on short-term MRI outcome. Partial wavelet coherence was used to quantify the coupling between C3–C4 EEG bandpower (2–16 Hz) and rSO2, eliminating confounding effects of SpO2. NVC was defined as the amount of significant coherence in a frequency range of 0.25–1 mHz. Partial wavelet coherence successfully removed confounding influences of SpO2 when studying the coupling between EEG and rSO2. Decreased NVC was related to worse MRI outcome. Furthermore, the combination of NVC and EEG spectral edge frequency (SEF) improved the identification of neonates with mild vs moderate and severe MRI outcome compared to using EEG SEF alone. Partial wavelet coherence is an effective method for removing confounding effects of SpO2, improving the robustness of automated assessment of NVC in long-term EEG-NIRS recordings. The obtained NVC biomarkers are more sensitive to MRI outcome than traditional rSO2 biomarkers and provide complementary information to EEG biomarkers.

Details

Title
Partial wavelet coherence as a robust method for assessment of neurovascular coupling in neonates with hypoxic ischemic encephalopathy
Author
Hermans, Tim 1 ; Carkeek, Katherine 2 ; Dereymaeker, Anneleen 3 ; Jansen, Katrien 4 ; Naulaers, Gunnar 3 ; Van Huffel, Sabine 1 ; De Vos, Maarten 5 

 STADIUS, KU Leuven, Department of Electrical Engineering (ESAT), Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884) 
 KU Leuven, Department of Development and Regeneration, Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884); UZ Leuven, Neonatal Intensive Care Unit, Leuven, Belgium (GRID:grid.410569.f) (ISNI:0000 0004 0626 3338); Cliniques Universitaires Saint Luc, Neonatal Intensive Care Unit, Brussels, Belgium (GRID:grid.48769.34) (ISNI:0000 0004 0461 6320) 
 KU Leuven, Department of Development and Regeneration, Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884); UZ Leuven, Neonatal Intensive Care Unit, Leuven, Belgium (GRID:grid.410569.f) (ISNI:0000 0004 0626 3338) 
 KU Leuven, Department of Development and Regeneration, Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884); UZ Leuven, Child Neurology, Leuven, Belgium (GRID:grid.410569.f) (ISNI:0000 0004 0626 3338) 
 STADIUS, KU Leuven, Department of Electrical Engineering (ESAT), Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884); KU Leuven, Department of Development and Regeneration, Leuven, Belgium (GRID:grid.5596.f) (ISNI:0000 0001 0668 7884) 
Pages
457
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2763170773
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.