Validation of Criteria for Identification of Epileptiform Discharges in EEG Recordings of Patients With Epilepsy

Epilepsy affects 50 million people of all ages. It is the most common neurologic disorder across the lifespan, and has been found to be associated with an increased risk of mortality compared to the general population. EEG is an important tool in the diagnostic work-up of patients with suspected epilepsy. The presence of epileptiform EEG discharges (EDs) confirm the diagnosis and provides important information that helps in classifying epilepsy. EDs are visually identified by experts with training in reading EEG. Although EDs were defined in the previous edition of the IFCN glossary of terms, that definition was conceptual, and the inter-rater agreement for identifying EDs was only moderate. Recently, the IFCN suggested the following operational definition for EDs: Transients distinguishable from background activity with a characteristic morphology; EDs have to fulfill at least 4 of the following 6 criteria: 1. Di- or tri-phasic waves with sharp or spiky morphology (i.e. pointed peak). 2. Different wave-duration than the ongoing background activity: either shorter or longer. 3. Asymmetry of the waveform: a sharply rising ascending phase and a more slowly decaying descending phase, or vice versa. 4. The transient is followed by an associated slow after-wave. 5. The background activity surrounding epileptiform discharges is disrupted by the presence of the epileptiform discharges. 6. Distribution of the negative and positive potentials on the scalp suggests a source of the signal in the brain, corresponding to a radial, oblique or tangential orientation of the source. This is best assessed by inspecting voltage maps constructed using common-average reference. However, these criteria are largely based on expert opinion. Data from clinical validation studies are lacking, thus it is not known what the sensitivity and specificity of these methods are. The threshold of four fulfilled criteria was arbitrary, and it is not sure whether it yields the optimal accuracy (sensitivity and specificity). Furthermore, since each criterion is based on visual evaluation, it is not known whether all experts would reach the same conclusion. The IFCN criteria were developed for identifying EDs using the traditional way of inspecting EEG, in the channels of the recording electrodes (sensor space). However, advances in signal analysis made possible to reproduce the electric currents in the brain regions, using a spatial filtering method (source space). The objective of this study are: 1. To determine the inter-rater agreement for the IFCN criteria 2. To determine the number of criteria and their combination that yields the highest diagnostic accuracy 3. To determine the accuracy of identifying EDs in source space. Raters with experience in clinical EEG will inspect 100 anonymized EEG samples, from consecutive patients with epilepsy and consecutive patients with non-epileptic paroxysmal episodes. All 100 patients have a reference standard for their condition, derived from analysis of their video-EEG recordings of their habitual clinical episode. Patients with both focal and generalized epilepsy, as well as non-epileptic paroxysmal episodes (psychogenic non-epileptic seizures, sleep-disorders, movement disorders, convulsive syncope) are included. Each EEG sample contains a sharp transient that is either epileptiform or not. EEGs were recoded using the IFCN electrode array of 25 electrodes (including the ones in the inferior temporal chain). The samples were randomized twice, resulting in two series containing the same set of 100 samples, though with different codes and in different order of presentation. The raters will inspect the two series separately. In the first session the raters will inspect samples in sensor space, using traditional EEG montages (longitudinal and transversal bipolar; common average) and voltage maps. For each sample, they will score the presence or absence of each IFCN criterion. In the second session, the raters will inspect the EEG samples in source space and voltage maps, and will conclude on the presence / absence of EDs. The performance of these methods will be compared with unrestricted scorings based on the experts´ evaluation.