What we can know from bispectral analysis of EEG?

What we can know from bispectral analysis of EEG?

International Congress Series 1283 (2005) 239 – 242 www.ics-elsevier.com What we can know from bispectral analysis of EEG? Satoshi Hagihira a,*, Mas...

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International Congress Series 1283 (2005) 239 – 242

www.ics-elsevier.com

What we can know from bispectral analysis of EEG? Satoshi Hagihira a,*, Masaki Takashina b, Takahiko Mori c, Hiroshi Ueyama a, Takashi Mashimo a a

Department of Anesthesiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka, 565-0871, Japan b Surgical Center, Osaka University Hospital, Japan c Department of Anesthesiology, Osaka Medical Center, Japan

Abstract. Bispectral analysis is an advanced signal processing technique that quantifies quadratic nonlinearities (phase-coupling) among the components of a signal. As bicoherence is the direct indicator of the degree of phase coupling, it is the most important element of bispectral analysis. Here we investigated the changes of EEG bicoherence induced by anesthesia or noxious stimuli. First, we investigated the changes of EEG bicoherence during isoflurane anesthesia. We found EEG bicoherence showed two peaks in fairly restricted regions of bi-frequency space and their heights were well correlated with isoflurane concentration. It is well known that EEG is influenced by noxious stimuli as well as anesthetic concentration. Then we investigated the influence of noxious stimuli on EEG bicoherence during isoflurane or sevoflurane anesthesia. Two peaks of EEG bicoherence were both diminished after skin incision, which re-emerged after fentanyl administration. On the other hand, EEG bicoherence was not changed after incision, when fentanyl was administered before incision. Their data suggested that EEG bicoherence was sensitive to noxious stimuli, which suggested that EEG bicoherence would become an indicator for adequacy of analgesia during anesthesia. In conclusion, we would be able to manage both hypnosis and analgesia during anesthesia by EEG bicoherence monitoring. D 2005 Published by Elsevier B.V. Keywords: Bispectral analysis; Bicoherence; EEG; Hypnosis; Analgesia

1. Introduction Bispectral analysis is the core technology of the BISR monitor (Aspect Medical Systems, Natick, MA, USA) [1]. However, there were no precise description of how bispectral * Corresponding author. Tel.: +81 6 6879 3133; fax: +81 6 6879 3139. E-mail address: [email protected] (S. Hagihira). 0531-5131/ D 2005 Published by Elsevier B.V. doi:10.1016/j.ics.2005.07.022

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analysis of EEG data can be useful in assessing the depth of anesthesia. To investigate this, we developed a software application named bBSAQ that runs under Microsoft Windows (Microsoft Corp, Redmond, WA, USA). The direct indicator of the degree of phase coupling is bicoherence, which is the normalized parameter of bispectrum. As bispectrum value itself is influenced by the magnitude of the original components as well as by the degree of phase coupling, we cannot directly assess the degree of phase coupling by bispectrum. That is why bicoherence is the most important element of bispectral analysis. Here we investigated the changes of EEG bicoherence during anesthesia. It is known that EEG is influenced by noxious stimuli as well as by the concentration of anesthetics. Then, we first investigated the changes of EEG bicoherence during isoflurane anesthesia. In this experiment, we used epidural anesthesia to suppress the influence of surgical stimuli on EEG bicoherence. Secondly, we investigated the influence of noxious stimuli on EEG bicoherence. 2. BSA application and EEG data collection As to the detail of our software bBSAQ, please refer our previous reports [2–4]. Before induction of anesthesia, five electrodes (A1, A2, Fp1, Fp2 and Fpz; according to the International 10–20 System) were placed. Fpz was used as the body ground. We sampled EEG data (Fp1–A1 lead) at 512 Hz. After artifact detection, wave data were down sampled at 128 Hz by averaging every four samples to improve the accuracy of data sampling. The EEG low-pass filter was set at 60 Hz and time-constant of the amplifier was set to 0.3 sec. We used 2-sec epochs and each epoch was overlapped the previous one by 75%. After applying a Blackman window function, the Fourier transform of each epoch is computed. Then, we calculated EEG bispectrum and bicoherence values from 3 min of EEG sample (360 epochs) according to the equations which we previously described [1]. 3. Bicoherence and anesthesia As our earlier trial revealed that two peaks of EEG bicoherence were emerged in rather restricted regions (one is around 4 Hz and the other is around 10 Hz on the diagonal lines

Fig. 1. Height of pBICs and isoflurane concentration (reproduced by permission of LWW Company from Ref. [3]).

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of f1 = f2) in bi-frequency space during anesthesia (Fig. 1). Then we defined those peak heights as pBIC-low and pBIC-high, respectively [2]. Then we investigated the changes of those two peak heights at awake, 0.3%, 0.5%, 0.7%, 0.9%, 1.1%, 1.3% and 1.5% of isoflurane concentrations in 32 patients [3]. In this study, we used epidural anesthesia to suppress surgical stimuli. In light of anesthetic state, EEG bicoherence values were low. pBIC-low grew higher as isoflurane concentration increased until it reached a plateau at isoflurane 0.9%. pBIC-high also became significantly higher and reached a plateau at isoflurane 0.9%; at isoflurane 1.3%, however, it slightly decreased (Fig. 1). 4. Bicoherence and noxious stimuli Then, we investigated the influence of noxious stimuli on EEG bicoherence [4]. In this experiment, we enrolled twelve patients. At first, anesthesia was maintained with isoflurane 1.0%. After confirming the steady state, we recorded baseline data. Then surgery was commenced. Five minutes after incision, we recorded second data and 3 Ag/kg of fentanyl was administered. The third data were recorded 5 min after fentanyl administration. Fig. 2 showed the changes of pBICs in three points. In all cases, pBIC-high significantly decreased and almost diminished after incision. pBIC-low also significantly decreased but still showed its peak. Both peaks returned to the pre-incisional values 5 min after fentanyl administration. In another study, we administered 3 Ag/kg of fentanyl before incision. In this case, fentanyl itself did not alter pBICs before incision but it kept pBICs at pre-incisional values even after incision. Thus, EEG bicoherence seemed to be very sensitive to noxious stimuli. 5. What do the peaks of EEG bicoherence indicate? The frequencies of two peaks of EEG bicoherence seemed to be coincidence with those of delta wave and spindle wave whose rhythms were known to be generated in the

Fig. 2. Changes of pBIC-high and pBIC-low by incision and fentanyl administration (reproduced by permission of LWW Company from Ref. [4]).

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thalamic reticular nuclei and thalamocortical loops [5]. Then, we compared EEG bicoherence obtained from Fp1–A1 (hemi-frontal) lead with that obtained from Fp1–Fp2 (bi-frontal) lead [6]. EEG bicoherence obtained from a uni-frontal lead showed two significant peaks in the low frequency region, but EEG bicoherence obtained from the bifrontal lead was quite low in all bi-frequency planes. This result suggested that the peaks of EEG bicoherence were related to some specific EEG rhythm sources which dominate both hemisphere. Thalamus is the most possible candidate of such rhythm source. 6. Summary We showed EEG bicoherence would be a good indicator for adequacy of analgesia. As EEG bicoherence also depends on the concentration of anesthetics, it would be better to maintain a uniform concentration of anesthetics to use pBIC values as an indicator of analgesia. Considering that volatile anesthetics are unable to suppress brain responses to noxious stimuli, this strategy seems rational in view of the concept of balanced anesthesia. Consequently, we can manage both hypnosis and analgesia during surgery by EEG monitoring. References [1] J.C. Sigl, N.G. Chamoun, An introduction to bispectral analysis for the electroencephalographic signals, J. Clin. Monit. 10 (1994) 392 – 404. [2] S. Hagihira, et al., Practical Issues in bispectral analysis of electroencephalographic signals, Anesth. Analg. 93 (2001) 966 – 970. [3] S. Hagihira, et al., Changes of electroencephalographic bicoherence during isoflurane anesthesia combined with epidural anesthesia, Anesthesiology 97 (2002) 1409 – 1415. [4] S. Hagihira, et al., Electroencephalographic bicoherence is sensitive to noxious stimuli during isoflurane or sevoflurane anesthesia, Anesthesiology 100 (2004) 818 – 825. [5] M. Steriade, et al., The slow (b1 Hz) oscillation in reticular thalamic and thalamocortical neurons: scenario of sleep rhythm generation in interacting thalamic and neocortical networks, J. Neurosci. 13 (1993) 3284 – 3299. [6] S. Hagihira, et al., Bispectral analysis gives us more information than power spectral-based analysis, Br. J. Anaesth. 92 (2004) 772 – 773.