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.

Objective: To determine the diagnostic accuracy and clinical utility of electromagnetic source imaging (EMSI) in presurgical evaluation of patients with epilepsy. Methods: We prospectively recorded magnetoencephalography (MEG) simultaneously with electroencephalography (EEG) and performed EMSI, comprising electric (ESI), magnetic source imaging (MSI) and analysis of combined MEG-EEG datasets (cEMSI), using two different software packages. As reference standard for irritative zone (IZ) and seizure onset zone (SOZ) we used intracranial recordings and for localization accuracy, outcome one year after operation. Results: We included 141 consecutive patients. EMSI showed localized epileptiform discharges (ED) in 94 patients (67%). Most of the ED-clusters (72%) were identified by both modalities, 15% only by EEG and 14% only by MEG. Agreement was substantial between inverse solutions and moderate between software packages. EMSI provided new information that changed the management plan in 34% of the patients, and these changes were useful in 80%. Depending on the method, EMSI had a concordance of 53-89% with IZ and 35%-73% with SOZ. Localization accuracy of EMSI was between 44% and 57%, which was not significantly different from MRI (49-76%) and PET (54-85%). cEMSI achieved significantly higher odds ratio compared to ESI and MSI. Conclusions: EMSI has accuracy similar to established imaging methods and provides clinically useful, new information in 34% of the patients. Classification of Evidence: This study provides Class IV evidence that EMSI had a concordance of 53-89% and 35%-73% (depending on analysis) for the localization of epilepsy as compared with intracranial recordings - IZ zone and SOZ respectively.