V. Pedapati, K. Du, A. Mina, A. Bradley, J. Espino, K. Batmanghelich, P. Thirumala, S. Visweswaran
{"title":"颈动脉内膜切除术后脑电图定量变化与缺血的相关性","authors":"V. Pedapati, K. Du, A. Mina, A. Bradley, J. Espino, K. Batmanghelich, P. Thirumala, S. Visweswaran","doi":"10.1109/SPMB55497.2022.10014953","DOIUrl":null,"url":null,"abstract":"Continuous intraoperative monitoring with electroencephalography (EEG) is routinely used in carotid endarterectomy (CEA) to detect cerebral ischemia [1]. Visually observed changes in EEG related to ischemia include an ipsilateral decrease in amplitude of faster frequencies or an ipsilateral increase in activity of slower frequencies. In the literature, significant EEG change has been defined as a decrease in the amplitude in the alpha frequency band by 50% or greater or an increase in activity in the theta or delta frequency band by 50% or greater [2], [3]. Compared to raw EEG, quantitative EEG (QEEG) parameters can enhance visual EEG review. QEEG parameters are derived by applying Fourier transformation to raw EEG signals to generate power spectra [4]. Examples of QEEG parameters include delta, theta, alpha, beta, gamma power values, alpha power to delta power ratio (ADR), beta power to delta power ratio (BDR), alpha-plus-beta power to delta-plus-theta power ratio (ABDTR), spectral edge frequency 90% (SEF90) and amplitude-integrated EEG (aEEG). QEEG parameters have been previously investigated in detecting ischemia in a relatively small number of patients undergoing CEA [5]. In this study, we report on the analyses of QEEG parameters in a large population of patients who underwent CEA with EEG monitoring.","PeriodicalId":261445,"journal":{"name":"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Quantitative EEG Changes in Carotid Endarterectomy Correlated with Ischemia\",\"authors\":\"V. Pedapati, K. Du, A. Mina, A. Bradley, J. Espino, K. Batmanghelich, P. Thirumala, S. Visweswaran\",\"doi\":\"10.1109/SPMB55497.2022.10014953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Continuous intraoperative monitoring with electroencephalography (EEG) is routinely used in carotid endarterectomy (CEA) to detect cerebral ischemia [1]. Visually observed changes in EEG related to ischemia include an ipsilateral decrease in amplitude of faster frequencies or an ipsilateral increase in activity of slower frequencies. In the literature, significant EEG change has been defined as a decrease in the amplitude in the alpha frequency band by 50% or greater or an increase in activity in the theta or delta frequency band by 50% or greater [2], [3]. Compared to raw EEG, quantitative EEG (QEEG) parameters can enhance visual EEG review. QEEG parameters are derived by applying Fourier transformation to raw EEG signals to generate power spectra [4]. Examples of QEEG parameters include delta, theta, alpha, beta, gamma power values, alpha power to delta power ratio (ADR), beta power to delta power ratio (BDR), alpha-plus-beta power to delta-plus-theta power ratio (ABDTR), spectral edge frequency 90% (SEF90) and amplitude-integrated EEG (aEEG). QEEG parameters have been previously investigated in detecting ischemia in a relatively small number of patients undergoing CEA [5]. In this study, we report on the analyses of QEEG parameters in a large population of patients who underwent CEA with EEG monitoring.\",\"PeriodicalId\":261445,\"journal\":{\"name\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPMB55497.2022.10014953\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPMB55497.2022.10014953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantitative EEG Changes in Carotid Endarterectomy Correlated with Ischemia
Continuous intraoperative monitoring with electroencephalography (EEG) is routinely used in carotid endarterectomy (CEA) to detect cerebral ischemia [1]. Visually observed changes in EEG related to ischemia include an ipsilateral decrease in amplitude of faster frequencies or an ipsilateral increase in activity of slower frequencies. In the literature, significant EEG change has been defined as a decrease in the amplitude in the alpha frequency band by 50% or greater or an increase in activity in the theta or delta frequency band by 50% or greater [2], [3]. Compared to raw EEG, quantitative EEG (QEEG) parameters can enhance visual EEG review. QEEG parameters are derived by applying Fourier transformation to raw EEG signals to generate power spectra [4]. Examples of QEEG parameters include delta, theta, alpha, beta, gamma power values, alpha power to delta power ratio (ADR), beta power to delta power ratio (BDR), alpha-plus-beta power to delta-plus-theta power ratio (ABDTR), spectral edge frequency 90% (SEF90) and amplitude-integrated EEG (aEEG). QEEG parameters have been previously investigated in detecting ischemia in a relatively small number of patients undergoing CEA [5]. In this study, we report on the analyses of QEEG parameters in a large population of patients who underwent CEA with EEG monitoring.