To date, source imaging (SI) has been performed using epileptiform discharges (ED) detected by magnetoencephalography (MEG) or electroencephalography (EEG). A few case studies has combined MEG and EEG recordings and performed electromagnetic source imaging (cEMSI). This study tries to elucidate the role of cEMSI in presurgical evaluation. A MEG whole-head 306-channel Elekta Neuromag® system, and simultaneous high density EEG (70 electrodes, range 58–80) using a non-magnetic cap (EASYCAP) were recorded in 141 consecutive patients. Fifty patients were operated and had one year follow up. MEG-EEG was inspected for EDs. Signals were analyzed using CURRY 7 Neuroimaging Suite. For each cluster, using the visually detected EDs as templates, automated algorithms scanned the recordings, and detected EDs were visually checked. To improve the signal-to-noise ratio, EDs with similar topography were averaged. Two different inverse solutions were applied: equivalent current dipole (ECD) and a distributed source model (DSM): sLORETA. We performed electric SI, magnetic SI, and cEMSI. All analyses were performed using individual head models from the patients’ MRIs. We calculated the odds ratio (OR) of becoming seizure-free when operation was concordant vs discordant with the localization of the SI. Combining both EEG and MEG signals (cEMSI) gave an OR of 5.8 for ECD and 19.2 for DSM. OR of cEMSI using DSM was significantly higher than both ESI (p = 0.02) and MSI (p = 0.03). Combined EMSI achieved significantly higher odds ratio for becoming seizure-free compared to electric SI and magnetic SI.

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 EEG and performed EMSI, comprising electric source imaging, magnetic source imaging, and analysis of combined MEG-EEG datasets, using 2 different software packages. As reference standard for irritative zone (IZ) and seizure onset zone (SOZ), we used intracranial recordings and for localization accuracy, outcome 1 year after operation. Results We included 141 consecutive patients. EMSI showed localized epileptiform discharges in 94 patients (67%). Most of the epileptiform discharge 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% to 89% with IZ and 35% to 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%). Combined EMSI achieved significantly higher odds ratio compared to electric source imaging and magnetic source imaging. Conclusion 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 epileptic focus as compared with intracranial recordings-IZ and SOZ, respectively.

The greatest challenge in epilepsy surgery lies in the presurgical evaluation. On their own, none of the diagnostic methods can identify the epileptogenic zone. Therefore, a multimodal approach is used. Over the last decades, advances in recording techniques and in signal analysis made it possible to estimate the source of the epileptiform discharges recorded by electroencephalography (EEG source imaging: ESI) and magnetoencephalography (MEG source imaging: MSI). This prospective study investigates the role of electromagnetic source imaging (EMSI) as a non-invasive tool to guide the multidisciplinary epilepsy surgery team. MEG (306 channels) and simultaneous high-density EEG was recorded in 85 consecutive patients with refractory focal epilepsy, referred for conventional non-invasive presurgical evaluation. EMSI, comprising of electric, magnetic source imaging and analysis of combined MEG-EEG datasets, using commercially available software (BESA and CURRY) was used. The Danish epilepsy surgery team evaluated the patients first blinded to EMSI and then including the data from EMSI. At both sessions the multidisciplinary team (MDT) determined the presumed localisation of the epileptogenic zone and decided on location of surgery, intracranial registration (ICR) placement, or not offering epilepsy surgery. The clinical utility of EMSI was defined as the proportion of patients in whom EMSI changed the decision of the MDT. A change was defined useful as follows: (a) change from stop to ICR: the ICR localized the source; (b) change in implantation strategy: the electrode(s) implanted based on the EMSI identified the source; and (c) change from implantation to operation: the patient became seizure-free. The impact of EMSI on patient management-plan was assessed in 85 patients (50 men) in whom EMSI was part of the decision-making process. The age of these patients was between 10 and 70 years (median: 32 years). Thirty-eight patients were MRI negative; in the remaining patients, there were discordance between MRI and data from long-term video-EEG monitoring (semiology and EEG). EMSI changed the management plan in 28/85 patients (33%). For 16.5% (14/85) of the patients the ICR plan changed (additional structures were implanted). For 7% (6/85) of the patients, in whom neither operation nor ICR was suggested, after discussing the EMSI results, ICR was offered. For 9.4% (8/85) of the patients ICR was suggested prior to EMSI; after EMSI these patients skipped ICR and went directly to operation. Finally, for one patient it was decided not to offer operation, after discussing the EMSI. At one-year follow-up 80% (16/20) of these changes proved to be useful, meaning that the EMSI changes located the seizure onset zone, irritative zone or the patient became seizure free. Electromagnetic source imagening provides clinically relevant information that supplements the decision-making process in presurgery evaluation for epilepsy surgery.

09.30-10.30 Aalto University presentations Risto Ilmoniemi: Towards better accuracy and reliability: Hybrid MEG–MRI technology 
 Matti Stenroos: Forward and inverse models for MEG signal interpretation 
 Lauri Parkkonen: High-resolution, real-time and hyperscanning MEG 
 Riitta Salmelin: MEG of language function: beyond univariate analysis of evoked responses 
 Hanna Renvall: MEG signals as probes of genetic functions 
 Mia Liljeström: Large-scale functional networks underlying language and speech 
 Linda Henriksson: Relating MEG signals to behavior and computational models

Evidence for seizure-induced cardiac dysrhythmia leading to sudden unexpected death in epilepsy (SUDEP) has been elusive. We present a patient with focal cortical dysplasia who has had epilepsy for 19 years and was undergoing presurgical evaluation. The patient did not have any cardiologic antecedents. During long-term video-electroencephalography (EEG) monitoring, following a cluster of secondarily generalized tonicclonic seizures (GTCS), the patient had prolonged postictal generalized EEG suppression, asystole, followed by arrhythmia, and the patient died despite cardiopulmonary resuscitation. Analysis of heart rate variability showed a marked increase in the parasympathetic activity during the period preceding the fatal seizures, compared with values measured 1 day and 7 months before, and also higher than the preictal values in a group of 10 patients with GTCS without SUDEP. The duration of the QTc interval was short (335-358 msec). This unfortunate case documented during video-EEG monitoring indicates that autonomic imbalance and seizure-induced cardiac dysrhythmias contribute to the pathomechanisms leading to SUDEP in patients at risk (short QT interval).

Summary: Epilepsy is the third most common neurologic disorder in the elderly and, combined with the progressive aging of the population, this high incidence will lead to an increasing number of elderly patients who require epilepsy care. Treatment of epilepsy in elderly patients is often complicated by the physiologic changes that occur in old age, e.g., reduced absorption, slower metabolism, and deterioration of liver and renal function. Another consideration is that elderly patients are most likely to be suffering from other diseases, necessitating multiple therapies. The potential for drug interactions is therefore high. Because of these factors, traditional antiepileptic drug (AED) therapies are associated with a higher incidence of adverse effects in elderly patients than in younger patients. Tiagabine (TGB) is one of a family of new AEDs recently developed. The newer AEDs tend to have a comparable antiepileptic efficacy and a lower potential for toxicity compared with the traditional AEDs. Clinical studies have shown that age appears to have no effect on the pharmacokinetics of TGB and that there is little difference in the incidence of adverse events between elderly and young patients. Although clinical experience with TGB in the elderly is still limited, TGB shows promise for treatment of epilepsy in the elderly population.