Methodological and clinical aspects of ictal and interictal MEG

During the last years magnetoencephalography (MEG), has become an important part of the pre-surgical epilepsy workup. Interictal activity is usually recorded. Nevertheless, the technological advances now enable ictal MEG recordings as well. The records of 26 pharmaco-resistant focal epilepsy patients, who underwent ictal MEG and epilepsy surgery, were reviewed. In 12 patients prediction of ictal onset zone (IOZ) localization by ictal and interictal MEG was compared with ictal intracranial EEG (icEEG). On the lobar surface level the sensitivity of ictal MEG in IOZ location was 0.71 and the specificity 0.73. The sensitivity of the interictal MEG was 0.40 and specificity 0.77. The records of 34 operated epilepsy patients with focal cortical dysplasia (FCD) were retrospectively evaluated. The resected proportion of the source cluster related to interictal MEG was evaluated in respect to postoperative seizure outcome. 17 out of 34 patients with FCD (50%) achieved seizure freedom. The seizure outcome was similar in patients with MR-invisible and MR-visible FCD. With MEG source clusters and favorable seizure outcome (Engel class I and II) the proportion of the cluster volume resection was 49% - significantly higher (p=0.02) than with MEG clusters but unfavorable outcome (5.5% of cluster volume resection). Median nerve somatosensory evoked MEG responses were processed by movement compensation based on signal space separation (MC-SSS) and on spatio-temporal signal space separation (MC-tSSS). MEG was recorded in standard and deviant head positions. With up to 5 cm head displacement, MC-SSS decreased the mean localization error from 3.97 to 2.13 cm, but increased noise of planar gradiometers from 3.4 to 5.3 fT/cm. MC-tSSS reduced noise from 3.4 to 2.8 fT/cm and reduced the mean localization error from 3.91 to 0.89 cm. The MEG data containing speech-related artifacts and data containing alpha rhythm were processed by tSSS with different correlation limits. The speech artifact was progressively suppressed with the decreasing tSSS correlation limit. The optimal artifact suppression was achieved at correlation of 0.8. The randomly distributed source current (RDCS), and auditory and somatosensory evoked fields (AEFs and SEFs) were simulated. The information was calculated employing Shannon's theory of communication for a standard 306-sensor MEG device and for a virtual MEG helmet (VMH), which was constructed based on simulated MEG measurements in different head positions. With the simulation of 360 recorded events using RDCS model the maximum Shannon's number was 989 for single head position in standard MEG array and 1272 in VMH (28.6% additional information). With AEFs the additional contribution of VMH was 12.6% and with SEFs only 1.1%. To conclude, ictal MEG predicts IOZ location with higher sensitivity than interictal MEG. Resection of larger proportion of the MEG source cluster in patients with FCD is associated with a better seizure outcome, however, complete resection of MEG source cluster is often not required for achievement of favorable seizure outcome. The seizure outcome is similar in patients having MR-positive and MR-negative FCD. MC-tSSS decreases the source localization error to less than 1 cm, when the head is displaced up to 5 cm; however, it is reasonable to limit use of movement compensation for no more than 3-cm head displacement to keep the head inside sensor helmet. The optimization of the tSSS correlation limit to about 0.8 can improve the artifact suppression in MEG without substantial change of brain signals. MEG recording of the same brain activity in different head positions with subsequent construction of VMH can improve the information content of the data.Magnetoenkefalografia (MEG) on menetelmä, jolla mitataan aivojen tuottamia heikkoja magneettikenttiä. Yksi menetelmän tärkeimmistä kliinisistä käyttö-tarkoituksista on paikantaa epilepsiapesäkkeitä aivoissa. Tämä on tärkeää epilepsiakirurgian suunnittelussa. Potilaan liikkeet mittauksen aikana ovat aiheuttaneet epätarkkuutta pesäkkeiden paikannukseen ja häiriösignaaleja mittauksiin. Ongelma on ollut erityisen korostunut lasten mittauksissa ja epileptisten kohtausten rekisteröinneissä. Useimmissa potilaissa MEG-paikannus onkin perustunut kohtausten välisten epileptiformisten aivosähköilmiöiden paikannukseen. Pitkät MEG-rekisteröinnit ovat myös olleet haastavia koska yhteistyökykyisten potilaidenkin on vaikea olla liikkumatta pitkiä aikoja. Viime vuosien tekninen kehitys on mahdollistanut MEG-mittaukset myös pään liikkeiden aikana. Myös aivosignaalien ja kehossa olevien magneettisten materiaalien (esim hammaspaikat, sydämen tahdistimet tai aivostimulaattorit) aiheuttamien magneettisten häiriöiden erottaminen on nykyisin toteutettavissa. Tämä kehitys on mahdollistanut MEG-mittaukset potilailla, joilla aiemmin ei ollut mahdollisuutta hyötyä MEG-paikannuksista ja myös MEG-mittaukset epileptisten kohtausten aikana. Tärkeä osa väitöskirjaa on epilepsiakohtausten aikaisten MEG-mittausten kliinisen hyödyn arviointi. Tulokset osoittavat, että kohtauksenaikaiset MEG-mittaukset paikantavat herkemmin epilepsiakohtauksen lähdealueen aivoissa kuin kohtausten välisten epilepsiailmiöiden lähdepaikannus. Lähdealueiden paikannus on yhtä tarkka sekä aivokuoren pinnalla että 4 cm syvyydessä aivouurteissa. Pää ei kuitenkaan saisi liikkua 3 cm enempää MEG-mittauksen aikana, ja menetelmän herkkyys paranee oilennaisesti magneettikenttien matemaattiseen mallinnukseen perustuvalla magneettisten liikehäiriöiden poistolla. Väitöskirja tutkii lisäksi aivokuoren rakennemuutosten (paikallinen aivokuoridysplasia) aiheuttaman epilepsian kohtausten välisiä MEG-mittauksia. Päinvastoin kuin aiemmin on väitetty, ei aina ole tarpeen poistaa koko epileptisia lähdealueita sisältävää aivojen aluetta hyvän leikkaustuloksen saamiseksi. Väitöskirja esittelee myös laskennallisen MEG-anturiston määritysmenetelmän , joka lisää MEG-mittausten informaatiosisältöä huomioimalla pään liikkeet tulosten analyysissä

Virtual MEG Helmet : Computer Simulation of an Approach to Neuromagnetic Field Sampling

Head movements during an MEG recording are commonly considered an obstacle. In this computer simulation study, we introduce an approach, the virtual MEG helmet (VMH), which employs the head movements for data quality improvement. With a VMH, a denser MEG helmet is constructed by adding new sensors corresponding to different head positions. Based on the Shannon's theory of communication, we calculated the total information as a figure of merit for comparing the actual 306-sensor Elekta Neuromag helmet to several types of the VMH. As source models, we used simulated randomly distributed source current (RDSC), simulated auditory and somatosensory evoked fields. Using the RDSC model with the simulation of 360 recorded events, the total information (bits/sample) was 989 for the most informative single head position and up to 1272 for the VMH (addition of 28.6%). Using simulated AEFs, the additional contribution of a VMH was 12.6% and using simulated SEF only 1.1%. For the distributed and bilateral sources, a VMH can provide a more informative sampling of the neuromagnetic field during the same recording time than measuring the MEG from one head position. VMH can, in some situations, improve source localization of the neuromagnetic fields related to the normal and pathological brain activity. This should be investigated further employing real MEG recordings.Peer reviewe

Dual array EEG-fMRI : An approach for motion artifact suppression in EEG recorded simultaneously with fMRI

Objective: Although simultaneous recording of EEG and MRI has gained increasing popularity in recent years, the extent of its clinical use remains limited by various technical challenges. Motion interference is one of the major challenges in EEG-fMRI. Here we present an approach which reduces its impact with the aid of an MR compatible dual-array EEG (daEEG) in which the EEG itself is used both as a brain signal recorder and a motion sensor. Methods: We implemented two arrays of EEG electrodes organized into two sets of nearly orthogonally intersecting wire bundles. The EEG was recorded using referential amplifiers inside a 3 T MR-scanner. Virtual bipolar measurements were taken both along bundles (creating a small wire loop and therefore minimizing artifact) and across bundles (creating a large wire loop and therefore maximizing artifact). Independent component analysis (ICA) was applied. The resulting ICA components were classified into brain signal and noise using three criteria: 1) degree of two-dimensional spatial correlation between ICA coefficients along bundles and across bundles; 2) amplitude along bundles vs. across bundles; 3) correlation with ECG. The components which passed the criteria set were transformed back to the channel space. Motion artifact suppression and the ability to detect interictal epileptic spikes following daEEG and Optimal Basis Set (OBS) procedures were compared in 10 patients with epilepsy. Results: The SNR achieved by daEEG was 11.05 +/- 3.10 and by OBS was 8.25 +/- 1.01 (p <0.00001). In 9 of 10 patients, more spikes were detected after daEEG than after OBS (p <0.05). Significance: daEEG improves signal quality in EEG-fMRI recordings, expanding its clinical and research potential. (C) 2016 Elsevier Inc. All rights reserved.Peer reviewe