## Criteria for defining interictal epileptiform discharges in EEG: a clinical validation study

### Creators

Kural, Mustafa Aykut

Duez, Lene

Sejer Hansen, Vibeke

Larsson, Pål Gunnar

Rampp, Stefan

Schulz, Reinhard

Tankisi, Hatice

Wennberg, Richard

Bibby, Bo

Scherg, Michael

Beniczky, Sandor

## Description

### Objective: 

To define and validate criteria for accurate identification of EEG interictal epileptiform discharges (IEDs) using: (a) the six sensor space criteria proposed by the International Federation of Clinical Neurophysiology (IFCN), and, (b) a novel source space method. Criteria yielding high specificity are needed because EEG "over-reading" is a common cause of epilepsy misdiagnosis.

### Methods: 

Seven raters reviewed EEG segments containing sharp waveforms from 100 patients with and without epilepsy. Clinical diagnosis gold standard was video-EEG recording of habitual paroxysmal events. Raters reviewed in three separate rounds, in randomized order: 1) in sensor space, presence/absence of each IFCN criterion was scored; 2) in source space, sharp transients were classified as epileptiform or non-epileptiform; 3) in sensor space, sharp transients were classified unrestricted by any criteria (expert scoring).

### Results:

Cut-off values of 4 and 5 criteria in sensor space, and analysis in source space, provided high accuracy (91%, 88% and 90%, respectively), similar to expert scoring (92%). Two methods had specificity exceeding the desired threshold of 95%: using 5 IFCN criteria as cut-off, and analysis in source space (both 95.65%); sensitivity of these methods was 81.48% and 85.19%.

### Conclusions: 

Presence of 5 IFCN criteria in sensor space and analysis in source space are optimal for clinical implementation. By extracting these objective features, diagnostic accuracy similar to expert scorings is achieved.

### Classification of evidence: 

This study provides Class III evidence that IFCN criteria in sensor space and analysis in source space have high specificity (>95%) and sensitivity (81-85%) for identification of IEDs.

### Notes

EDF files are electroencephalography (EEG) recordings in a non-proprietary format (European Data Format).

Most EEG software can read EDF format.