59CHAPTER 5

Electroencephalography and Artifact in the Intensive Care Unit

Nishi Rampal, Carolina B. Maciel, and Lawrence J. Hirsch

INTRODUCTION

Monitoring the EEG in critically ill patients presents a unique set of challenges to the clinical neurophysiologist due to recording that takes place in an electrically “hostile” environment. Artifacts are numerous, occur commonly, may be generated from specialized types of machinery used in ICU, and arise from an abundance of electromechanical sources (1,2). Some artifacts are more easily identified, while others may closely mimic periodic patterns that resemble epileptiform activity or even rhythmic activity that resembles electrographic seizures. Additionally, ICU recordings often last for prolonged periods of time, increasing the likelihood that an artifact will be introduced into the recording. Therefore, there is occasionally the need for repeat continuous EEG (cEEG) monitoring. cEEG monitoring gives rise to progressive loss of electrode integrity as the duration of recording increases. This occurs in addition to concomitant exposure of the patient to procedures, treatments, and electronic machines during cEEG, all of which can create artifacts. An understanding of these pitfalls lies at the foundation of identifying electrical “fact from fiction” (3). Errors can occur at both ends of the spectrum, with artifacts causing loss of important information due to interference with interpretation and overinterpretation, resulting in adverse consequences (4–6). This chapter and its detailed figures aim to provide a framework to better identify common types of artifacts recorded in the ICU so patterns may be recognized to identify the common source of origin (Figure 5.1).

Artifacts in the ICU can be generated from three main sources: environmental, patient or patient care, and technical (6) (Tables 5.1–5.3). Environmental sources of artifacts in the ICU often result in readily identifiable artifacts (Table 5.1). These are often monomorphic oscillations that reflect their instrumental or mechanical origin. The appearance of 60-Hz artifact is a common artifact source in cEEG monitoring and is detailed in other chapters. In the ICU, unlike other recording environments, there are numerous electrical signal generators that warrant familiarity, such as bed oscillators (Figures 5.2 and 5.3), ventilators (Figures 5.4 and 5.5), temperature management devices (Figure 5.6), and hemodialysis and infusion pumps (7).

TABLE 5.1: EEG Artifact From Environmental Sources

cEEG in the ICU is subject to artifacts common to all types of EEG recordings. The presence of eye movements (Figures 5.7 and 5.8), muscle activity generating a surface electromyogram (EMG) signal (Figures 5.9–5.12), ECG, and sweat artifact (Figures 5.13 and 5.14) are produced by the patient or derived from patient care (Table 5.2). Internal electric signals generated within a patient from implanted devices such as left ventricular assist devices and pacemakers (Figures 5.15 and 5.16) may also produce artifacts. There are a host of additional artifacts that are not unique to the critically 60ill patient but are more prevalent in the ICU environment. The critically ill patient often has an EEG that lends itself to interpreter uncertainty. With critical illness and its associated encephalopathy, the expected organization, frequencies, and state-dependent characteristics of normal EEG are often lost. The resulting EEG obtained in the ICU is often chaotic, focal, or diffusely slowed background activity, with absent stages of sleep. Often, patient interaction can produce highly rhythmic, ictal-appearing patterns, particularly sternal rub (Figure 5.7) or chest percussion. At first look, identifying some types of artifact can be difficult to distinguish from true abnormality.

TABLE 5.2: EEG Artifacts From Patient or Patient Care

The EEG technologist is key to prevention, identification, and correction of artifacts, providing both routine maintenance of cEEG and technological expertise to “troubleshoot” artifact when technical sources are suspect (Table 5.3). The technologist–neurophysiologist team is crucial to interpreting ICU-EEG recordings. Entry of comments into the EEG recording by any care team member can also aid in artifact identification and source localizing information.

To further confound the issues, there is often an overlap of sources (Tables 5.1–5.3) producing artifacts, such as a patient placed on a cooling device (Figure 5.6) leading to shivering producing prominent EMG artifact and superimposed machine artifact. Add to this picture unexpected or abnormal movements, and it is easy to see how artifacts can build up to beguile and mislead the interpreter. When identified, the origin of the artifact can often be confirmed by video evaluation (an important reason to include video on all ICU recordings). This is especially true when the EEG is not attended by a technologist throughout the duration of recording to provide confirmatory steps such as moving or unplugging a device (Figure 5.6), clearing fluid from ventilator tubing (Figure 5.5), checking electrode impedances, 61and making corrections when the integrity of the recording is compromised (Figures 5.17–5.24). This creates an opportunity not only to avoid erroneous interpretation but also to allow for interventions to improve the quality of the captured recording.

TABLE 5.3: EEG Artifacts From Technical Sources

Some artifacts like 60/50 Hz are commonly encountered with or without additional types of artifact. Surprisingly, the effects of specific artifacts and the multiplicity of combinations can be seen to produce a varying array of patterns, as illustrated in Figures 5.1, 5.20, and 5.22. When approaching the spectrum of artifacts in the ICU-EEG produced by the patient, patient care, environment, or technically generated artifacts, a systematic approach is essential. In addition to the need for familiarity with common artifacts, it is essential when interpreting ICU-EEG and cEEG partially obscured by artifact to limit overuse of the digital filters. Both the use of low-frequency (high-pass) and high-frequency (low-pass) filters can adulterate the EEG and lead to misinterpretation (Figure 5.21). Similarly, use of the 60-Hz (or 50-Hz) “notch” filter, which is commonly employed, risks erroneous interpretations (Figure 5.20). Instead of relying on filters to clean up an ICU-EEG recording that is contaminated with artifact, eliminating the source by modifying technical, environmental, or patient-derived generators is always the best course of action when feasible.

Quantitative analysis (QEEG) or digital analysis, which uses algorithms to transform hours of raw EEG into single-page color images and graphs, is featured in numerous figures using digital analysis software from Persyst, Inc. (Prescott, Arizona) in this chapter. Digital analysis is useful for long-term trending of seizure detection and quantification (8–10). In addition, it has been used to detect ischemia (most commonly after subarachnoid hemorrhage), elevated intracranial pressure, rebleeding after intracerebral hemorrhage, hypoxemia, and other acute brain injuries (11,12). QEEG findings should always be corroborated by review of the underlying raw EEG data. This point cannot be overemphasized. Because QEEG uses raw EEG data, it is also subject to the same effects from artifacts. Artifacts such as the type generated by bed oscillation are easily identified on QEEG. This produces a very narrow frequency band in the spectral array derived from the fast Fourier transformation that starts and stops abruptly, unlike physiological activity. In this case, the QEEG helps to identify the artifactual nature of a rhythmic pattern (Figure 5.2D). Other commonly occurring artifacts like ventilator condensation can erroneously trigger the seizure probability index to rise (Figure 5.5B and D). These programs have attempted to combat artifact conflation by detecting specific artifacts and graphing their prominence (blinks, muscle, 60 Hz). This serves to indicate when an artifact is overwhelming the signals generated by the brain, beyond which graphic display may not be helpful, and artifact removal is required. Figure 5.12 demonstrates how artifact reduction software can produce the appearance of generalized periodic discharges (GPDs) with rhythmic delta activity (GPD+R) in EEG from widespread muscle artifact. Without reviewing the raw EEG and only assessing the QEEG, artifact might have been mistaken as a common abnormality of critical illness.

Intracortical EEG, or depth electrode placement in ICU-EEG monitoring, can provide essential information. The absence of electrographic seizures on scalp EEG does not exclude the possibility of seizures on intracortical EEG recording (13–15). Intracortical EEG is subject to a host of potential misinterpretations, as rhythms that are normally encountered on scalp EEG have a higher amplitude and sharper morphology. There is much less artifact on the intracortical EEG due to the much higher signal:noise ratio when bypassing the scalp and skull. This makes for an excellent method to detect changes in local field potentials including epileptiform activity and ischemia. However, there are still artifacts that may occur despite intracranial EEG recording. This is true due to the machinery and electrical connections (Table 5.3) that are related to movements of wires, plug-in connections, amplifiers, and even muscle artifact generated by patients, though to a lesser degree. Scalp EEG is also frequently performed in conjunction with invasive EEG, and likewise may also possess the tendency to manifest a unique type of artifact (Figure 5.22).

CONCLUSION

EEG interpretation often guides therapy in the ICU by providing real-time assessment in a critically ill population. Careful attention to artifact identification is paramount for correct interpretation of ICU-EEG and is directly tied to quality patient care. While artifacts in the ICU-EEG are numerous, they have a broad range of patterns that require a heightened index of suspicion as well as familiarity with the unique types that may occur. By using a stepwise approach to recognizing artifact focuses on identification of three main sources (environmental, patient or patient care, and technical); the EEG interpreter of ICU-EEG can safeguard against misinterpretation when elimination is not possible.

All EEG images were recorded with 21 leads with E1 (left lower canthus), E2 (right upper canthus) eye channels (blue), ECG1-ECG2 cardiac rhythm strip (red), with the following settings: LFF 1 Hz, HFF 70 Hz, Notch off, time base 30 mm/sec unless otherwise stated in the figure description. The recording reference was placed between Fz and Cz. Impedances were maintained at less than 10 kΩ, as established by the American Clinical Neurophysiology Society (ACNS) guidelines (16). New guidelines changed this from 5 to 10 kΩ to be more liberal. Many montages include one channel shown with a system reference (C3-ref, green). Most samples are shown using an anterior–posterior longitudinal bipolar montage; left hemisphere over midline and right hemisphere.

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