Clinical Validation of the Champagne Algorithm for Epilepsy Spike Localization.

Frontiers in Human Neuroscience
Chang CaiSrikantan S Nagarajan

Abstract

Magnetoencephalography (MEG) is increasingly used for presurgical planning in people with medically refractory focal epilepsy. Localization of interictal epileptiform activity, a surrogate for the seizure onset zone whose removal may prevent seizures, is challenging and depends on the use of multiple complementary techniques. Accurate and reliable localization of epileptiform activity from spontaneous MEG data has been an elusive goal. One approach toward this goal is to use a novel Bayesian inference algorithm-the Champagne algorithm with noise learning-which has shown tremendous success in source reconstruction, especially for focal brain sources. In this study, we localized sources of manually identified MEG spikes using the Champagne algorithm in a cohort of 16 patients with medically refractory epilepsy collected in two consecutive series. To evaluate the reliability of this approach, we compared the performance to equivalent current dipole (ECD) modeling, a conventional source localization technique that is commonly used in clinical practice. Results suggest that Champagne may be a robust, automated, alternative to manual parametric dipole fitting methods for localization of interictal MEG spikes, in addition to its previ...Continue Reading

References

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Oct 16, 2014·Lancet Neurology·Philippe RyvlinSylvain Rheims
Jul 1, 2017·Epilepsia·Birgit FrauscherJean Gotman
Jul 31, 2018·NeuroImage·Chang CaiSrikantan S Nagarajan
Jul 26, 2019·Nature Reviews. Neurology·Maeike ZijlmansNicole van Klink
Aug 6, 2019·IEEE Transactions on Medical Imaging·Chang CaiSrikantan S Nagarajan
Jun 20, 2020·Epileptic Disorders : International Epilepsy Journal with Videotape·Imte KosterAlbert J Colon
Aug 10, 2020·Brain Topography·Gianvittorio LuriaFerruccio Panzica

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