Comparison of magnetic source estimation to intracranial EEG, resection area, and seizure outcome

Magnetoencephalography (MEG) is used to guide intracranial electroencephalography (ICEEG) monitoring and determine areas for resection. The purpose of this retrospective cross-sectional study was to report our experience using dipole modeling/dipole scanning, current density reconstructions, and beam-forming methods in a large cohort of pediatric patients with intractable epilepsy.

Source localization results for each algorithm and seizure-onset zone, defined by ICEEG, were described by three blinded reviewers according to five location criteria. The accuracy of each algorithm was then compared to ICEEG. The relationships between the accuracy of these algorithms (discordant, lobar concordant, sublobar concordant) and long-term seizure outcome was calculated using positive and negative predictive values.

Thirty-two patients (mean age ± SD, 10.8 ± 5 years) were included in this retrospective review. No algorithms had sublobar concordance with ICEEG in all patients, including when algorithms were grouped by type (dipole modeling/dipole scanning, current density reconstruction, beam forming). Synthetic aperture magnetometry (SAM) with excess kurtosis tended to be the most accurate, but there were no significant differences between algorithms. When comparing the source modeling with ICEEG findings, significantly more patients with a seizure-free outcome were found to have lobar or sublobar concordance of multiple signal classification (MUSIC) (61.1%) and standardized low resolution brain electromagnetic tomography (sLORETA) (52.9%). Positive predictive values were highest for MUSIC (61.9%) and equivalent current dipole (ECD) (57.1%). Negative predictive values were highest for SAM(g2 )-VS (83%), minimum norm estimate (MNE) (75%), MUSIC (73.7%), and ECD (73.5%).

This study describes the use of multiple MEG source estimation techniques and demonstrates that all algorithms have similar rates of concordance with ICEEG. Also, the concordance or discordance of MUSIC with ICEEG was the best predictor of long-term seizure outcome.