Document Type
Article
Publication Date
11-29-2023
Abstract
General anesthesia (GA) during surgery is commonly maintained by inhalational sevoflurane. Previous resting state functional MRI (rs-fMRI) studies have demonstrated suppressed functional connectivity (FC) of the entire brain networks, especially the default mode networks, transitioning from the awake to GA condition. However, accuracy and reliability were limited by previous administration methods (e.g. face mask) and short rs-fMRI scans. Therefore, in this study, a clinical scenario of epilepsy patients undergoing laser interstitial thermal therapy was leveraged to acquire 15 min of rs-fMRI while under general endotracheal anesthesia to maximize the accuracy of sevoflurane level. Nine recruited patients had fMRI acquired during awake and under GA, of which seven were included in both static and dynamic FC analyses. Group independent component analysis and a sliding-window method followed by k-means clustering were applied to identify four dynamic brain states, which characterized subtypes of FC patterns. Our results showed that a low-FC brain state was characteristic of the GA condition as a single featuring state during the entire rs-fMRI session; In contrast, the awake condition exhibited frequent fluctuations between three distinct brain states, one of which was a highly synchronized brain state not seen in GA. In conclusion, our study revealed remarkable dynamic connectivity changes from awake to GA condition and demonstrated the advantages of dynamic FC analysis for future studies in the assessments of the effects of GA on brain functional activities.
Recommended Citation
Miao, J.; Tantawi, M.; Alizadeh, Mahdi; Thalheimer, Sara; Vedaei, Faezeh; Romo, Victor; Mohamed, Feroze B.; and Wu, Chengyuan, "Characteristic Dynamic Functional Connectivity During Sevoflurane-Induced General Anesthesia" (2023). Department of Neurosurgery Faculty Papers. Paper 220.
https://jdc.jefferson.edu/neurosurgeryfp/220
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
38030651
Language
English
Comments
This article is the author's final published version in Scientific Reports, Volume 13, Issue 1, 2023, Article number 21014.
The published version is available at https://doi.org/10.1038/s41598-023-43832-1. Copyright © The Author(s) 2023.