B Krishnan1, I Vlachos2, Z I Wang1, J Mosher1, I Najm1, R Burgess1, L Iasemidis2, A V Alexopoulos3. 1. Cleveland Clinic Epilepsy Center, Cleveland, OH, USA. 2. Biomedical Engineering, Louisiana Tech University, LA, USA. 3. Cleveland Clinic Epilepsy Center, Cleveland, OH, USA. Electronic address: alexopa@ccf.org.
Abstract
OBJECTIVE: To investigate whether epileptogenic focus localization is possible based on resting state connectivity analysis of magnetoencephalographic (MEG) data. METHODS: A multivariate autoregressive (MVAR) model was constructed using the sensor space data and was projected to the source space using lead field and inverse matrix. The generalized partial directed coherence was estimated from the MVAR model in the source space. The dipole with the maximum information inflow was hypothesized to be within the epileptogenic focus. RESULTS: Applying the focus localization algorithm (FLA) to the interictal MEG recordings from five patients with neocortical epilepsy, who underwent presurgical evaluation for the identification of epileptogenic focus, we were able to correctly localize the focus, on the basis of maximum interictal information inflow in the presence or absence of interictal epileptic spikes in the data, with three out of five patients undergoing resective surgery and being seizure free since. CONCLUSION: Our preliminary results suggest that accurate localization of the epileptogenic focus may be accomplished using noninvasive spontaneous "resting-state" recordings of relatively brief duration and without the need to capture definite interictal and/or ictal abnormalities. SIGNIFICANCE: Epileptogenic focus localization is possible through connectivity analysis of resting state MEG data irrespective of the presence/absence of spikes.
OBJECTIVE: To investigate whether epileptogenic focus localization is possible based on resting state connectivity analysis of magnetoencephalographic (MEG) data. METHODS: A multivariate autoregressive (MVAR) model was constructed using the sensor space data and was projected to the source space using lead field and inverse matrix. The generalized partial directed coherence was estimated from the MVAR model in the source space. The dipole with the maximum information inflow was hypothesized to be within the epileptogenic focus. RESULTS: Applying the focus localization algorithm (FLA) to the interictal MEG recordings from five patients with neocortical epilepsy, who underwent presurgical evaluation for the identification of epileptogenic focus, we were able to correctly localize the focus, on the basis of maximum interictal information inflow in the presence or absence of interictal epileptic spikes in the data, with three out of five patients undergoing resective surgery and being seizure free since. CONCLUSION: Our preliminary results suggest that accurate localization of the epileptogenic focus may be accomplished using noninvasive spontaneous "resting-state" recordings of relatively brief duration and without the need to capture definite interictal and/or ictal abnormalities. SIGNIFICANCE: Epileptogenic focus localization is possible through connectivity analysis of resting state MEG data irrespective of the presence/absence of spikes.
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