EEG in epilepsy

William O Tatum IV DO FACNS (Dr. Tatum of Mayo Clinic has no relevant financial relationships to disclose.)
Jason Siegel MD (Dr. Siegel of Mayo Clinic has no relevant financial relationships to disclose.)
John M Stern MD, editor. (Dr. Stern, Director of the Epilepsy Clinical Program at the University of California in Los Angeles, received honorariums from Sunovion and UCB as an advisor and from Cyberonics, Eisai, Lundbeck, and UCB as a lecturer.)
Originally released November 10, 2008; last updated December 2, 2016; expires December 2, 2019

Overview

Electroencephalogram is the most useful test when evaluating possible epilepsy. It may provide specific neurophysiological information to support the clinical diagnosis, and based on the type of interictal epileptiform discharges, it can identify the seizure type or epilepsy syndrome. EEG findings can guide medical management, from directing antiseizure drug treatment to localizing an epileptogenic zone for neurosurgical treatment. Furthermore, it is an important adjunct to the clinical examination in the critically ill for diagnosing and treating unrecognized seizures and nonconvulsive status epilepticus. The usefulness of EEG has extended from a widely available, versatile, portable electrophysiological study to a sophisticated computer-based clinical and research metric that is elemental in exploring fundamental brain function.

Key points

 

• EEG is the diagnostic test of choice when evaluating a patient with seizures and epilepsy.

 

• Epilepsy is a clinical diagnosis that is supported by interictal epileptiform discharges on the EEG and confirmed by appropriate changes on EEG obtained during a seizure.

 

• EEG may help classify seizures and epilepsy syndromes by the distribution of epileptiform abnormalities and quantify the frequency of seizure occurrence.

 

• Misdiagnosis of nonepileptic events as seizures is probably not rare due to EEG misinterpretation.

 

• The surgical treatment of epilepsy relies on ictal EEG to characterize the electroclinical localization of the epileptogenic zone.

 

• Special waveforms, recording conditions, and new techniques are expanding EEG usefulness beyond the application in epilepsy.

Historical note and terminology

Historical note. In his seminal work “Uber das Elektroenkephalogram des Menschen” (“On the EEG of Man”), Hans Berger pioneered the discovery of human EEG, first recorded in 1929 (Berg et al 2009). The practical usefulness of EEG became apparent in the 1930s after interictal discharges were demonstrated first by Fisher and Lowenback and later by Gibbs, David, and Lennox in the United States. In 1936, W Gray Walter demonstrated that this technology could aid in the diagnosis of tumors, stroke, and other focal brain disorders. For 40 years, EEG was the cornerstone to the diagnosis and treatment of seizures and epilepsy, and until the advent of CT and MRI, it was the first-line neurodiagnostic test for these structural brain disorders.

EEG data were analyzed by visual inspection until the 1960s. With the introduction of digital equipment in the 1960s and 1970s and the application of Fourier analysis to computer-based EEG algorithms, spectral analysis and quantitative EEG became a reality. Despite the innovation of neuroimaging, EEG continues to have a vital role in the evaluation of neurologic disease, expanding from use in seizures and epilepsy to also include encephalopathy, traumatic brain injury, sleep disorders, coma, and brain death.

Terminology. In 2010, the International League Against Epilepsy (ILAE) further standardized terminology for seizure classification. In broad terms, epilepsy syndromes are classified as generalized, focal, or unknown with an etiology of genetic, structural-metabolic, or unknown (Berg et al 2010). The new terminology correlates to older language (Table 1), which is still often used clinically.

Table 1. Comparison of Old and New Terminology Set Forth by the ILAE in 2010

Characteristic

New terminology

Old terminology

Type of seizure and origin of onset

   

Originating within, and rapidly engaging, bilaterally distributed networks

Generalized

Generalized

Originating within networks limited to one hemisphere

Focal

Partial

Descriptors of focal seizures

   

Without impairment of consciousness or awareness

With observable motor or autonomic components

Simple partial

 

Involving subjective sensory or psych phenomena only

Aura

With impairment of consciousness or awareness

Dyscognitive

Complex partial

Evolving to a bilateral, convulsive seizure

---

Secondarily generalized seizure

Seizure etiology

   

Epilepsy as a direct result of a known or presumed genetic defect in which seizures are the core symptom of the disorder

Genetic

Idiopathic

Distinct structural or metabolic condition or disease that substantially increases epilepsy risk

Structural/metabolic

Symptomatic

Nature of underlying cause is unknown

Unknown

Cryptogenic

The application of the routine scalp EEG in epilepsy has relied on the electrocerebral activity between the 1 to 30 Hz bandwidth (ie, Berger's bandwidth). Filter settings are increasingly being “opened” during video epilepsy monitoring to obtain full-band EEG, providing a more comprehensive approach (Tatum 2014a). Newer applications of frequencies are now being explored to enhance disclosure of brain regions and the networks that are involved in seizure genesis (Table 2).

Table 2. Bandwidth and Interpretation of EEG Waveform Frequencies

Frequency (Hz)

Bandwidth

Normal

Pathological

0.0 - 0.5

Infraslow activity*

Artifacts

Onset of focal seizures

0.5 - 3.5

Delta

Sleep, HV, PSWY, elderly

Encephalopathy, white matter lesion

>3.5 - <8.0

Theta

Drowsiness, children, elderly

Encephalopathy, white matter lesion

8 - 13

Alpha

PDR, mu rhythm, “third” rhythm

Ictal rhythm in seizure, alpha coma

13 - 30

Beta

Medication, drowsiness

Breach rhythm, drug overdose, ictal rhythm

30 - 80

Gamma*

Voluntary motor movement, learning/memory

Seizures

80 - 250

Ripples*

Cognitive processing/memory

Interictal and ictal seizure frequency, possible epileptogenesis

250 - 500

Fast ripples*

?

Focal seizures

500 - 1000

Very fast ripples*

Acquisition of sensory information

Seizures

* = Expanded frequencies currently under investigation

The characteristic EEG features of epilepsy are spikes (20 to 70 msec) and sharp waves (70 to 200 msec) when displayed on a review monitor at a display speed of 30 mm/second.

Image: Epilepsy’s characteristic EEG features
Pathological discharges are distinguished from the background and contain a sharp contour, physiological field, rapid rise, and brief duration, occasionally with an after-going slow wave. Spikes and sharp waves can present in isolation or as polyspikes or polysharp waves.
Image: Juvenile absence epilepsy EEG features
Spikes and sharp waves possess the same potential for seizure genesis independent of morphology.

Each type of EEG recording in epilepsy has its own advantages and disadvantages. Routine scalp EEG recordings, short-term EEG, computer-assisted ambulatory EEG (CAA-EEG), and in-patient continuous video EEG monitoring (VEM) are different types of EEG recordings (Leach et al 2006), each with different clinical benefits and limitations (Table 3).

Table 3. Comparison of EEG Methods Used in the Evaluation of Patients with Paroxysmal Neurologic Events

Variable

Routine

Short-term

CAA-EEG

Epilepsy Monitoring

Time to complete
Availability
Yield of recording
Natural conditions
Cost of study
Reimbursement

30 - 60 minutes
+++
+
++
$
$

4 - 24 hours
++
++
++
$$
$$

24 - 48 hours
+ / ++
++ / +++
+++
$$ / $$$
$$ / $$$

1 - 7 days
+
+++
+
$$$
$$$

Notes: The “plus rating” and “dollar sign” are used to identified relative relationships. A 1-plus (“+”) rating has the lowest and 3-plus (“+++”)the highest association with the feature. * Short-term EEG is based on a mean of 4 hours of recording. CAA-EEG = computer-assisted ambulatory EEG.

Routine outpatient scalp EEG is the simplest, least expensive, most practical, and most commonly performed method. A routine scalp EEG is a brief 20- to 30-minute recording (up to 60 minutes in some cases), with or without capturing sleep. It is, therefore, inadequate for capturing infrequent paroxysmal neurologic events and abnormalities (Benbadis et al 2004). Prolonged EEG is better able to capture seizures and neurologic events. One 5-year study of 175 outpatient short-term EEGs (shorter than 24 hours) found that 7% yielded seizures (Seneviratne et al 2012b). A higher diagnostic yield (40%) was found in children when EEG monitoring was longer than 6 hours (Srikumar et al 2000). Prolonged EEG via either CAA-EEG or inpatient video EEG monitoring offers distinct advantages. The yield of identifying epileptiform discharges to support a clinical diagnosis of epilepsy has been approximately 2.0 to 2.5 times that of a routine EEG and was cost-effective when compared to the gold standard of video EEG monitoring with a yield of ambulatory-EEG greater than 70% (Bridgers and Ebersole 1985).

Another monitoring method is short-term amplitude-integrated electroencephalography (ST-aEEG). Patients with paroxysmal events that occur during sleep or with frequent daily events are the best candidates for ST-aEEG (Provini et al 1999; Terzaghi et al 2007; Derry et al 2009; Miskin et al 2015). Other practical reasons for ST-aEEG include assessment of epileptiform discharges prior to weaning antiseizure drugs from patients with prolonged seizure freedom, or considering tapering antiseizure drugs before determining whether a patient is an acceptable risk to operate a motor vehicle and should be released to driving (Anonymous 1996; Wang et al 2012).

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