Assessing Electrical Activity during Anaesthesia

Dr Hugo Vereecke, Ghent, Belgium

Many devices have become available for measuring the hypnotic component of anaesthesia, based on information from the spontaneous electroencephalogram (EEG) and the mid-latency auditory evoked potentials (MLAEP).(1) The complex changes of both neurophysiologic signals during anaesthesia are reduced to a single number (or index) in order to cope with the potential observers bias of anaesthesiologists, without specific background on the subject. However, the rather complex mathematical algorithms used, might hamper the ability of the clinical anaesthesiologist to evaluate whether a resulting index is trustworthy or rather based on artefacts. Therefore, every commercialized EEG and MLAEP derived monitor should provide adequate information on signal quality, in order to allow a safe clinical applicability.

In this lecture a short review is provided on potential causes of conflicting measurements, with an emphasis on the effects of the electromyogram, ketamine, neuromuscular blocking agents and burst suppression patterns.(2-4)

As the MLAEP signal is 10 to 100 fold smaller compared to the spontaneous EEG,  it appears to be more vulnerable to measurement interferences. This characteristic of MLAEP measurements is a potential cause of the poor pharmacodynamic performance of the A-Line® Auditory Evoked Potential Index (AAI) (Danmeter, Odense, Denmark), a fast extracted MLAEP derived index. The quantification of the awake or lightly sedated population is characterized by an excessive variability. Moreover, the index has a low capacity for differentiating deep levels of anaesthesia.(1) In order to optimize the correlation between the AAI and a wide range of cerebral drug effects, it appeared necessary to combine MLAEP with information from the spontaneous EEG. Moreover, in the algorithm for this new composite AAI, the signal quality of the MLAEP is the major trigger whether EEG derived information will be included in the final AAI calculation.(5)

This commercially available algorithm demonstrates the importance of sustained research to better comprehend the underlying mechanisms of poor signal quality and artefacts. Such research eventually results in algorithms and noise reduction technology that allows more adequate monitoring of the clinical relevant hypnotic drug effects during anaesthesia. 

References:

1.  Vanluchene AL, Vereecke H, Thas O, Mortier EP, Shafer SL, Struys MM. Spectral entropy as an electroencephalographic measure of anesthetic drug effect: a comparison with bispectral index and processed midlatency auditory evoked response. Anesthesiology 2004;101:34-42.

2.  Vereecke HE, Struys MM, Mortier EP. A comparison of bispectral index and ARX-derived auditory evoked potential index in measuring the clinical interaction between ketamine and propofol anaesthesia. Anaesthesia 2003;58:957-61.

3.  Vereecke HE, Vanluchene AL, Mortier EP, Everaert K, Struys MM. The effects of ketamine and rocuronium on the A-Line auditory evoked potential index, Bispectral Index, and spectral entropy monitor during steady state propofol and remifentanil anesthesia. Anesthesiology 2006;105:1122-34.

4.  Bruhn J. Burst suppression ratio is the only determinant for BIS values below 30. Can J Anaesth 2002;49:755-6; author reply 6.

5.  Vereecke HE, Vasquez PM, Jensen EW, Thas O, Vandenbroecke R, Mortier EP, Struys MM. New Composite Index Based on Midlatency Auditory Evoked Potential and Electroencephalographic Parameters to Optimize Correlation with Propofol Effect Site Concentration: Comparison with Bispectral Index and Solitary Used Fast Extracting Auditory Evoked Potential Index. Anesthesiology 2005;103:500-7.