Is there a role for magnetoencephalography in pre-surgical RNS implantation in drug-resistant temporal lobe epilepsy?

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Objective: To study the utility of Magnetoencephalography (MEG) in patients undergoing evaluation for Responsive Neuro stimulation (RNS) for drug-resistant temporal lobe epilepsy.

Background: RNS was approved as an adjunctive therapy for drug-resistant focal-onset epilepsy in the USA in November 2013. The success of epilepsy surgery, including RNS, is highly dependent on localization of the epileptogenic zone. MEG, in combination with coherence source imaging (CSI; a measure of oscillating neuronal activity), can be useful in precise surgical mapping. The aim of the present study was to determine whether epileptogenic regions detected by MEG can provide accurate locations for the RNS leads in patients with drug-refractory epilepsy.

Design/Methods: Retrospective analysis of patients with drug resistant temporal lobe epilepsy (TLE) who eventually received RNS and MEG at our center was performed. Data collected as part of the pre-surgical epilepsy work up also included scalp video EEG, MRI, SPECT, PET scan, Phase II EEG monitoring and Wada testing, as appropriate. Postoperative outcome was assessed after one year using Engel classification. Resting-state 15-minute MEG scans filtered 3–50 Hz were analyzed with ECD and CSI. Engel outcomes were compared in patients with and without concordance between localization assessed by MEG-CSI and RNS electrode implantation.

Results: A total of 10 patients with RNS implantation in our study underwent pre-surgical MEG. Compared to patients with non-concordant MEG based localization and RNS placement, patients with concordant data had the following outcomes: Engel IV (33.3% vs 50%), Engel III (33.3% vs 25%), Engel II (16.7% vs 25%) and Engel 1 (16.7% vs 0%).

Conclusions: Our study with a small sample size demonstrates a trend towards better outcomes in patients with concordant MEG and RNS data, thereby suggesting a greater role for MEG in pre-surgical mapping for RNS placement. A larger sample size would provide further clarity to this crucial question.




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