Artifact

Assessment of depth of sedation using Bispectral Index™ monitoring in patients with severe traumatic brain injury in UK intensive care units

Introduction

Severe traumatic brain injury affects ∼4500 per year across the UK. Most patients undergo a period of sedation to prevent secondary brain injury, however the optimal sedation target is unclear. This study aimed to assess the relationship between the electroencephalogram (EEG)-based Bispectral Index™ (BIS™) value and the clinical sedation score, along with other clinical outcomes.

Methods

Patients with severe traumatic brain injury in four UK ICUs were recruited to have blinded BIS data collected for a 24-h period while sedated on the ICU. Drug, physiological, and outcome data were recorded from the ICU record. Sedation management was at the discretion of the ICU clinical team.

Results

Twenty-six participants were recruited to the study. The mean BIS was 38 (inter-quartile range 29-44) and there was poor correlation between BIS and sedation score as a group (correlation coefficient 0.17, 95% confidence interval 0.08-0.26), however the spread in BIS values increased with decreasing sedation score. There was no statistically significant relationship between BIS and intracranial pressure, vasopressor use, osmotherapy use, or need for an additional sedative.

Conclusion

This study supports previous work showing that BIS decreases with decreasing sedation score. However, the variation in BIS values increased with deeper levels of clinical sedation. Patients may not be benefiting from the full potential of sedation in traumatic brain injury and further studies of sedation titrated to an EEG-based parameter are needed.

Clinical trial registration

NCT03575169.

Normal variants and artifacts: Importance in EEG interpretation

Overinterpretation of EEG is an important contributor to the misdiagnosis of epilepsy. For the EEG to have a high diagnostic value and high specificity, it is critical to recognize waveforms that can be mistaken for abnormal patterns. This article describes artifacts, normal rhythms, and normal patterns that are prone to being misinterpreted as abnormal. Artifacts are potentials generated outside the brain. They are divided into physiologic and extraphysiologic. Physiologic artifacts arise from the body and include EMG, eyes, various movements, EKG, pulse, and sweat. Some physiologic artifacts can be useful for interpretation such as EMG and eye movements. Extraphysiologic artifacts arise from outside the body, and in turn can be divided into the environments (electrodes, equipment, and cellphones) and devices within the body (pacemakers and neurostimulators). Normal rhythms can be divided into awake patterns (alpha rhythm and its variants, mu rhythm, lambda waves, posterior slow waves of youth, HV-induced slowing, photic driving, and photomyogenic response) and sleep patterns (POSTS, vertex waves, spindles, K complexes, sleep-related hypersynchrony, and frontal arousal rhythm). Breach can affect both awake and sleep rhythms. Normal variants or variants of uncertain clinical significance include variants that may have been considered abnormal in the early days of EEG but are now considered normal. These include wicket spikes and wicket rhythms (the most common normal pattern overread as epileptiform), small sharp spikes (aka benign epileptiform transients of sleep), rhythmic midtemporal theta of drowsiness (aka psychomotor variant), Cigánek rhythm (aka midline theta), 6 Hz phantom spike-wave, 14 and 6 Hz positive spikes, subclinical rhythmic epileptiform discharges of adults (SREDA), slow-fused transients, occipital spikes of blindness, and temporal slowing of the elderly. Correctly identifying artifacts and normal patterns can help avoid overinterpretation and misdiagnosis. This is an educational review paper addressing a learning objective of the International League Against Epilepsy (ILAE) curriculum.

Adaptive single-channel EEG artifact removal for real-time clinical monitoring

OBJECTIVE

Electroencephalography (EEG) has become very common in clinical practice due to its relatively low cost, ease of installation, non-invasiveness, and good temporal resolution. Portable EEG devices are increasingly popular in clinical monitoring applications such as sleep scoring or anesthesia monitoring. In these situations, for reasons of speed and simplicity only few electrodes are used and contamination of the EEG signal by artifacts is inevitable. Visual inspection and manual removal of artifacts is often not possible, especially in real-time applications. Our goal is to develop a flexible technique to remove EEG artifacts in these contexts with minimal supervision.

METHODS

We propose here a new wavelet-based method which allows to remove artifacts from single-channel EEGs. The method is based on a data-driven renormalization of the wavelet components and is capable of adaptively attenuate artifacts of different nature. We benchmark our method against alternative artifact removal techniques.

RESULTS

We assessed the performance of the proposed method on publicly available datasets comprising ocular, muscular, and movement artifacts. The proposed method shows superior performances on different kinds of artifacts and signal-to-noise levels. Finally, we present an application of our method to the monitoring of general anesthesia.

CONCLUSIONS

We show that our method can successfully attenuate various types of artifacts in single-channel EEG.

SIGNIFICANCE

Thanks to its data-driven approach and low computational cost, the proposed method provides a valuable tool to remove artifacts in real-time EEG applications with few electrodes, such as monitoring in special care units.

How to carry out and interpret EEG recordings in COVID-19 patients in ICU?

There are questions and challenges regarding neurologic complications in COVID-19 patients. EEG is a safe and efficient tool for the evaluation of brain function, even in the context of COVID-19. However, EEG technologists should not be put in danger if obtaining an EEG does not significantly advance diagnosis or change management in the patient. Not every neurologic problem stems from a primary brain injury: confusion, impaired consciousness that evolves to stupor and coma, and headaches are frequent in hypercapnic/hypoxic encephalopathies. In patients with chronic pulmonary disorders, acute symptomatic seizures have been reported in acute respiratory failure in 6%. The clinician should be aware of the various EEG patterns in hypercapnic/hypoxic and anoxic (post-cardiac arrest syndrome) encephalopathies as well as encephalitides. In this emerging pandemic of infectious disease, reduced EEG montages using single-use subdermal EEG needle electrodes may be used in comatose patients. A full 10-20 EEG complement of electrodes with an ECG derivation remains the standard. Under COVID-19 conditions, an expedited study that adequately screens for generalized status epilepticus, most types of regional status epilepticus, encephalopathy or sleep may serve for most clinical questions, using simplified montages may limit the risk of infection to EEG technologists. We recommend noting whether the patient is undergoing or has been placed prone, as well as noting the body and head position during the EEG recording (supine versus prone) to avoid overinterpretation of respiratory, head movement, electrode, muscle or other artifacts. There is slight elevation of intracranial pressure in the prone position. In non-comatose patients, the hyperventilation procedure should be avoided. At present, non-specific EEG findings and abnormalities should not be considered as being specific for COVID-19 related encephalopathy.

Artifact Mimicking Ictal Epileptiform Activity in EEG

Although the EEG is designed to record cerebral activity, it also frequently records activity from extracerebral sources, leading to artifact. Differentiating rhythmical artifact from true electrographic ictal activity remains a substantial challenge to even experienced electroencephalographers because the sources of artifact able to mimic ictal activity on EEG have continued to increase with the advent of technology. Knowledge of the characteristics of the polarity and physiologic electrical fields of the brain, as opposed to those generated by the eyes, heart, and muscles, allows the electroencephalographer to intuitively recognize noncerebrally generated waveforms. In this review, we provide practical guidelines for the EEG interpreter to correctly identify physiologic and nonphysiologic artifacts capable of mimicking electrographic seizures. In addition, we further elucidate the common pitfalls in artifact interpretation and the costly impact of epilepsy misdiagnosis due to artifact.

American Clinical Neurophysiology Society Guideline 6: Minimum Technical Standards for EEG Recording in Suspected Cerebral Death

This revision to the EEG Guidelines is an update incorporating current EEG technology and practice. The role of the EEG in making the determination of brain death is discussed as are suggested technical criteria for making the diagnosis of electrocerebral inactivity.

Train of four stimulation artifact mimicking a seizure during computerized automated ICU EEG monitoring

A 54-year-old man was admitted to the intensive care unit with an aneurysmal subarachnoid hemorrhage and subsequently underwent mechanical ventilation and received neuromuscular blocking drugs to control refractory elevated intracranial pressure. During quantitative EEG monitoring, an automated alert was triggered by the train of four peripheral nerve stimulation artifacts. Real-time feedback was made possible due to remote monitoring. This case illustrates how computerized, automated artificial intelligence algorithms can be used beyond typical seizure detection in the intensive care unit for remote monitoring to benefit patient care.

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ICU EEG provides an emerging opportunity for seizure detection (ictal) and interictal monitoring in the ICU setting.

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Artifacts are plentiful in the ICU EEG setting.

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Quantitative EEG (QEEG) with artificial neural-networks can be programmed to generate interesting artifacts that are not seizures, as the current example.

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Such artifacts while not being epileptiform in nature, may still have clinical context such as moving the patient, suctioning intubated patients, being disconnected to go for CT scan, or in this case checking neuromuscular stimulation for neuromuscular blockade level.

American Clinical Neurophysiology Society Guideline 6: Minimum Technical Standards for EEG Recording in Suspected Cerebral Death

This revision to the EEG Guidelines is an update incorporating current EEG technology and practice. The role of the EEG in making the determination of brain death is discussed as are suggested technical criteria for making the diagnosis of electrocerebral inactivity.

The Texting Rhythm: A Novel EEG Waveform Using Smartphones

INTRODUCTION

We report a unique EEG phenomenon in patients with paroxysmal neurological events undergoing video EEG monitoring.

METHODS

Two epilepsy centers analyzed the interictal scalp EEG in patients using personal electronic devices during epilepsy monitoring. The texting rhythm (TR) was defined as a reproducible, stimulus-evoked, generalized frontocentral monomorphic burst of 5-6 Hz theta consistently induced by active text messaging. An independent prospective and retrospective cohort was analyzed and compared from two sites in Florida and Illinois. We assessed age, gender, diagnosis, epilepsy classification, MRI, and EEG to compare patients with a TR. Analysis was performed with statistical significance set at P < 0.05.

RESULTS

We identified 24 of 98 evaluable patients with a TR in a prospective arm at one center and 7 of 31 patients in a retrospective arm at another totaling 31/129 (24.0%). The waveform prevalence was similar at both centers independent of location. TR was highly specific to active texting. A similar waveform during independent cognitive, speech or language, motor activation and audio cellular telephone use was absent (P < 0.0001). It appeared to be increased in patients with epilepsy in one cohort (P = 0.03) and generalized seizures in the other (P = 0.025). Age, gender, epilepsy type, MRI results, and EEG lateralization in patients with focal epileptic seizures did not bear a relationship to the presence of a TR in either arm of the study (P = NS).

CONCLUSIONS

The TR is a novel waveform time-locked to text messaging and associated with active use of smartphones. Electroencephalographers should be aware of the TR to separate it from an abnormality in patients undergoing video EEG monitoring. Larger sample sizes and additional research may help define the significance of this unique cognitive-visual-cognitive-motor network that is technology-related and task-specific with implications in communication research and transportation safety.

Evaluation of Dry Sensors for Neonatal EEG Recordings

PURPOSE

Neonatal seizures are a common neurologic diagnosis in neonatal intensive care units, occurring in approximately 14,000 newborns annually in the United States. Although the only reliable means of detecting and treating neonatal seizures is with an electroencephalography (EEG) recording, many neonates do not receive an EEG or experience delays in getting them. Barriers to obtaining neonatal EEGs include (1) lack of skilled EEG technologists to apply conventional wet electrodes to delicate neonatal skin, (2) poor signal quality because of improper skin preparation and artifact, and (3) extensive time needed to apply electrodes. Dry sensors have the potential to overcome these obstacles but have not previously been evaluated on neonates.

METHODS

Sequential and simultaneous recordings with wet and dry sensors were performed for 1 hour on 27 neonates from 35 to 42.5 weeks postmenstrual age. Recordings were analyzed for correlation and amplitude and were reviewed by neurophysiologists. Performance of dry sensors on simulated vernix was examined.

RESULTS

Analysis of dry and wet signals showed good time-domain correlation (reaching >0.8), given the nonsuperimposed sensor positions and similar power spectral density curves. Neurophysiologist reviews showed no statistically significant difference between dry and wet data on most clinically relevant EEG background and seizure patterns. There was no skin injury after 1 hour of dry sensor recordings. In contrast to wet electrodes, impedance and electrical artifact of dry sensors were largely unaffected by simulated vernix.

CONCLUSIONS

Dry sensors evaluated in this study have the potential to provide high-quality, timely EEG recordings on neonates with less risk of skin injury.

Comparing the Performance of Popular MEG/EEG Artifact Correction Methods in an Evoked-Response Study

We here compared results achieved by applying popular methods for reducing artifacts in magnetoencephalography (MEG) and electroencephalography (EEG) recordings of the auditory evoked Mismatch Negativity (MMN) responses in healthy adult subjects. We compared the Signal Space Separation (SSS) and temporal SSS (tSSS) methods for reducing noise from external and nearby sources. Our results showed that tSSS reduces the interference level more reliably than plain SSS, particularly for MEG gradiometers, also for healthy subjects not wearing strongly interfering magnetic material. Therefore, tSSS is recommended over SSS. Furthermore, we found that better artifact correction is achieved by applying Independent Component Analysis (ICA) in comparison to Signal Space Projection (SSP). Although SSP reduces the baseline noise level more than ICA, SSP also significantly reduces the signal—slightly more than it reduces the artifacts interfering with the signal. However, ICA also adds noise, or correction errors, to the waveform when the signal-to-noise ratio (SNR) in the original data is relatively low—in particular to EEG and to MEG magnetometer data. In conclusion, ICA is recommended over SSP, but one should be careful when applying ICA to reduce artifacts on neurophysiological data with relatively low SNR.

Cortical processing during smartphone text messaging

OBJECTIVE

The objective of this study was to report the EEG features of text messaging using smartphones.

METHODS

One hundred twenty-nine patients were prospectively evaluated during video-EEG monitoring (VEM) over 16months. A reproducible texting rhythm (TR) present during active text messaging with a smartphone was compared with passive and forced audio telephone use, thumb/finger movements, cognitive testing/calculation, scanning eye movements, and speech/language tasks in patients with and without epilepsy. Statistical significance was set at p<0.05.

RESULTS

Twenty-seven patients with a TR were identified from a cohort of 129 (93 female, mean age: 36; range: 18-71) unselected VEM patients. Fifty-three out of 129 patients had epileptic seizures (ES), 74/129 had nonepileptic seizures (NES), and 2/129 were dual-diagnosed. A reproducible TR was present in 27/129 (20.9%) specific to text messaging (p<0.0001) and present in 28% of patients with ES and 16% of patients with NES (p=NS). The TR was absent during independent tasks and audio cellular telephone use (p<0.0001). Age, gender, epilepsy type, MRI results, and EEG lateralization in patients with focal seizures were unrelated (p=NS).

CONCLUSIONS

Our results suggest that the TR on scalp EEG represents a novel technology-specific neurophysiological alteration of brain networks. We propose that cortical processing in the contemporary brain is uniquely activated by the use of PEDs.

SIGNIFICANCE

These findings have practical implications that could impact industry and research in nonverbal communication.

Consensus statement on continuous EEG in critically ill adults and children, part II: personnel, technical specifications, and clinical practice

INTRODUCTION

Critical Care Continuous EEG (CCEEG) is a common procedure to monitor brain function in patients with altered mental status in intensive care units. There is significant variability in patient populations undergoing CCEEG and in technical specifications for CCEEG performance.

METHODS

The Critical Care Continuous EEG Task Force of the American Clinical Neurophysiology Society developed expert consensus recommendations on the use of CCEEG in critically ill adults and children.

RECOMMENDATIONS

The consensus panel describes the qualifications and responsibilities of CCEEG personnel including neurodiagnostic technologists and interpreting physicians. The panel outlines required equipment for CCEEG, including electrodes, EEG machine and amplifier specifications, equipment for polygraphic data acquisition, EEG and video review machines, central monitoring equipment, and network, remote access, and data storage equipment. The consensus panel also describes how CCEEG should be acquired, reviewed and interpreted. The panel suggests methods for patient selection and triage; initiation of CCEEG; daily maintenance of CCEEG; electrode removal and infection control; quantitative EEG techniques; EEG and behavioral monitoring by non-physician personnel; review, interpretation, and reports; and data storage protocols.

CONCLUSION

Recommended qualifications for CCEEG personnel and CCEEG technical specifications will facilitate standardization of this emerging technology.

Respiratory artifact on EEG independent of the respirator

Recognizing EEG artifacts is important to correctly interpret and avoid unnecessary intervention. EEG artifacts from mechanical ventilation have been described as periodic, frontally maximal high amplitude waveforms, occurring at the same rate as the ventillator. Here, we describe a non-periodic respiratory artifact that was independent of the ventilator rate. The concomitant use of audio was helpful in identifying this artifact.

The spatial and signal characteristics of physiologic high frequency oscillations

OBJECTIVES

To study the incidence, spatial distribution, and signal characteristics of high frequency oscillations (HFOs) outside the epileptic network.

METHODS

We included patients who underwent invasive evaluations at Yale Comprehensive Epilepsy Center from 2012 to 2013, had all major lobes sampled, and had localizable seizure onsets. Segments of non-rapid eye movement (NREM) sleep prior to the first seizure were analyzed. We implemented a semiautomated process to analyze oscillations with peak frequencies >80 Hz (ripples 80-250 Hz; fast ripples 250-500 Hz). A contact location was considered epileptic if it exhibited epileptiform discharges during the intracranial evaluation or was involved ictally within 5 s of seizure onset; otherwise it was considered nonepileptic.

RESULTS

We analyzed recordings from 1,209 electrode contacts in seven patients. The nonepileptic contacts constituted 79.1% of the total number of contacts. Ripples constituted 99% of total detections. Eighty-two percent of all HFOs were seen in 45.2% of the nonepileptic contacts (82.1%, 47%, 34.6%, and 34% of the occipital, parietal, frontal, and temporal nonepileptic contacts, respectively). The following sublobes exhibited physiologic HFOs in all patients: Perirolandic, basal temporal, and occipital subregions. The ripples from nonepileptic sites had longer duration, higher amplitude, and lower peak frequency than ripples from epileptic sites. A high HFO rate (>1/min) was seen in 110 nonepileptic contacts, of which 68.2% were occipital. Fast ripples were less common, seen in nonepileptic parietooccipital regions only in two patients and in the epileptic mesial temporal structures.

CONCLUSIONS

There is consistent occurrence of physiologic HFOs over vast areas of the neocortex outside the epileptic network. HFOs from nonepileptic regions were seen in the occipital lobes and in the perirolandic region in all patients. Although duration of ripples and peak frequency of HFOs are the most effective measures in distinguishing pathologic from physiologic events, there was significant overlap between the two groups.