Investigating Individual Sensitivity To Propofol Using Brain Functional Network

Careful management of anesthetic dosage during general anesthesia is the key to reduce the incidence of intraoperative awareness and anesthesia-related complications.How to accurately determine the necessary dosage for a given patient is important in clinical anesthesia.However,after considering the effect of demographic characteristics such as weight,height and gender,large inter-subjects differences in sensitivity to propofol can still be observed.How to determine other factors affecting individual sensitivity to propofol before surgery is important for improving the safety of anesthesiaIn this thesis,the target-controlled infusion of propofol was employed to induce general anesthesia with a target plasma concentration of 3.0 μg/ml,while the anesthetic depth was monitored by bispectral index(BIS).The individual sensitivity to propofol was quantified by the time duration from infusion onset to a specific BIS.Resting state EEG data was recorded at awake sate and during anesthesia.In the first study,an undirected weighted brain function network was constructed based on EEG data recorded from awake state.Graph measures which represent functional integration and segregation capability of a brain network were selected as features for constructing a linear discriminate classifier.The performance of the trained classifier was evaluated by using the leave-one-out cross-validation method.In the second work,the high-order brain networks was tailored to suit for the analysis of EEG signals.To do so,we first extracted the source activity from EEG signal using Brainstorm.After selecting ROIs from the source space of EEG,a collection of temporal low-order networks were construed.Furthermore,the obtained lower order networks were then clustered into sub-networks.Finally,a high-order brain network with each cluster as node was constructed.Based on the calculated high-order network characteristics,we constructed a prediction model of individual sensitivity to propofol.In the third study,s LORETA was used to calculate current density values of different cortex regions for different EEG rhythms.The paired sample t-test was performed at voxel level for all subjects.The changes of brain activity at different anesthetic depths were analyzed with the target to identify the effect-site of Propofol.The results showed that subjects response differently to propofol,and they can be further divided into High-sensitivity group and Low-sensitivity group according to their induction time when BIS reaches 60.Graph measures representing the global functional integration and local functional segregation were significantly correlated with induction time of each subject.Furthermore,a linear discriminate classifier trained on the alpha band graph measures was shown to have an accuracy of 90% for predicting individual sensitivity to propofol.Based on the constructed classification model of high-order brain network,we shown that the interactions between sensorimotor cortex and visual cortex,between brain regions in the visual cortex,play a critical role in predicting individual sensitivity to propofol.Transition from awake state to mild anesthesia and deep anesthesia,the brain activity of whole cerebral area in delta rhythm increased significantly.While occipital lobe activity in alpha rhythm is significantly reduced,but the brain activity of frontal lobe,limbic lobe,insular,and temporal lobe rises.Our results shed light on the role of the cerebral cortex on individual sensitivity to propofol.Hence,the titration of propofol should take the pre-operative brain function status into consideration.