Influence of magnetic source imaging for planning intracranial EEG in epilepsy.

BACKGROUND: Magnetic source imaging (MSI) is used routinely in epilepsy presurgical evaluation and in mapping eloquent cortex for surgery. Despite increasing use, the diagnostic yield of MSI is uncertain, with reports varying from 5% to 35%. To add benefit, a diagnostic technique should influence decisions made from other tests, and that influence should yield better outcomes. We report preliminary results of an ongoing, long-term clinical study in epilepsy, where MSI changed surgical decisions. METHODS: We determined whether MSI changed the surgical decision in a prospective, blinded, crossover-controlled, single-treatment, observational case series. Sixty-nine sequential patients diagnosed with partial epilepsy of suspected neocortical origin had video-EEG and imaging. All met criteria for intracranial EEG (ICEEG). At a surgical conference, a decision was made before and after presentation of MSI. Cases where MSI altered the decision were noted. RESULTS: MSI gave nonredundant information in 23 patients (33%). MSI added ICEEG electrodes in 9 (13%) and changed the surgical decision in another 14 (20%). Based on MSI, 16 patients (23%) were scheduled for different ICEEG coverage. Twenty-eight have gone to ICEEG, 29 to resection, and 14 to vagal nerve stimulation, including 17 where MSI changed the decision. Additional electrodes in 4 patients covered the correct: hemisphere in 3, lobe in 3, and sublobar ictal onset zone in 1. MSI avoided contralateral electrodes in 2, who both localized on ICEEG. MSI added information to ICEEG in 1. CONCLUSION: Magnetic source imaging (MSI) provided nonredundant information in 33% of patients. In those who have undergone surgery to date, MSI added useful information that changed treatment in 6 (9%), without increasing complications. MSI has benefited 21% who have gone to surgery.

Automated interictal spike detection and source localization in magnetoencephalography using independent components analysis and spatio-temporal clustering.

OBJECTIVE: Magnetoencephalography (MEG) dipole localization of epileptic spikes is useful in epilepsy surgery for mapping the extent of abnormal cortex and to focus intracranial electrodes. Visually analyzing large amounts of data produces fatigue and error. Most automated techniques are based on matching of interictal spike templates or predictive filtering of the data and do not explicitly include source localization as part of the analysis. This leads to poor sensitivity versus specificity characteristics. We describe a fully automated method that combines time-series analysis with source localization to detect clusters of focal neuronal current generators within the brain that produce interictal spike activity. METHODS: We first use an ICA (independent components analysis) method to decompose the multichannel MEG data and identify those components that exhibit spike-like characteristics. From these detected spikes we then find those whose spatial topographies across the array are consistent with focal neural sources, and determine the foci of equivalent current dipoles and their associated time courses. We then perform a clustering of the localized dipoles based on distance metrics that takes into consideration both their locations and time courses. The final step of refinement consists of retaining only those clusters that are statistically significant. The average locations and time series from significant clusters comprise the final output of our method. RESULTS AND SIGNIFICANCE: Data were processed from 4 patients with partial focal epilepsy. In all three subjects for whom surgical resection was performed, clusters were found in the vicinity of the resectioned area. CONCLUSIONS: The presented procedure is promising and likely to be useful to the physician as a more sensitive, automated and objective method to help in the localization of the interictal spike zone of intractable partial seizures. The final output can be visually verified by neurologists in terms of both the location and distribution of the dipole clusters and their associated time series. Due to the clinical relevance and demonstrated promise of this method, further investigation of this approach is warranted.