AUTHOR=González Carmen , Garcia-Hernando Gabriel , Jensen Erik W. , Vallverdú-Ferrer Montserrat 

TITLE=Assessing rheoencephalography dynamics through analysis of the interactions among brain and cardiac networks during general anesthesia

JOURNAL=Frontiers in Network Physiology

VOLUME=Volume 2 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/network-physiology/articles/10.3389/fnetp.2022.912733

DOI=10.3389/fnetp.2022.912733

ISSN=2674-0109

ABSTRACT=Cerebral blood flow (CBF) reflects the rate of delivery of arterial blood to the brain. Since no nutrients, oxygen or water can be stored in the cranial cavity due to space and pressure restrictions, a continuous perfusion of the brain is critical for survival. Anesthetic procedures are known to affect cerebral hemodynamics, but CBF is only monitored in critical patients due, among others, to the lack of a continuous and affordable bedside monitor for this purpose. A potential solution through bioelectrical impedance technology, also known as rheoencephalography (REG), is proposed, that could fill the existing gap for a low-cost and effective CBF monitoring tool. The underlying hypothesis is that REG signals carry information on CBF that might be recovered by means of the application of advanced signal processing techniques, allowing to track CBF alterations during anesthesia. 
The initial analysis of REG signals was based on geometric features extracted from the time domain, since this is the standard processing strategy for this type of physiological data. Geometric features were tested to distinguish between different anesthetic depths, and they were capable of tracking cerebral hemodynamic changes during anesthesia. Furthermore, an approach based on Poincaré plot descriptors was proposed, where the reconstructed attractors form REG signals also showed significant differences between anesthetic states. 
Finally, the analysis of cerebral hemodynamics during anesthesia was performed, studying causal relationships between global hemodynamics, cerebral hemodynamics and EEG parameters. Interactions were detected during anesthetic drug infusion and patient positioning, providing evidence of the coupling between hemodynamics and brain activity. 
As a conclusion, the provided alternative method for REG signal processing confirmed the hypothesis that REG signals carry CBF information. The simplicity of the technology, together with its low cost and easily interpretable outcomes, should provide a new opportunity for REG to reach standard clinical practice. Moreover, causal relationships among the hemodynamic physiological signals and brain activity were assessed, suggesting that the inclusion of REG information in depth of anesthesia monitors could be of valuable use to prevent unwanted CBF alterations during anesthetic procedures.