User-defined virtual sensors: A new solution to the problem of temporal plus epilepsy sources.

OBJECTIVE

The most common medically resistant epilepsy (MRE) involves the temporal lobe (TLE), and children designated as temporal plus epilepsy (TLE+) have a five-times increased risk of postoperative surgical failure. This retrospective, blinded, cross-sectional study aimed to correlate visual and computational analyses of magnetoencephalography (MEG) virtual sensor waveforms with surgical outcome and epilepsy classification (TLE and TLE+).

METHODS

Patients with MRE who underwent MEG and iEEG monitoring and had at least 1 year of postsurgical follow-up were included in this retrospective analysis. User-defined virtual sensor (UDvs) beamforming was completed with virtual sensors placed manually and symmetrically in the bilateral amygdalohippocampi, inferior/middle/superior temporal gyri, insula, suprasylvian operculum, orbitofrontal cortex, and temporoparieto-occipital junction. Additionally, MEG effective connectivity was computed and quantified using eigenvector centrality (EC) to identify hub regions. More conventional MEG methods (equivalent current dipole [ECD], standardized low-resolution brain electromagnetic tomography, synthetic aperture magnetometry beamformer), UDvs beamformer, and EC hubs were compared to iEEG.

RESULTS

Eighty patients (38 female, 42 male) with MRE (mean age = 11.3 ± 6.2 years, range = 1.0-31.5) were identified and included. Twenty-five patients (31.3%) were classified as TLE, whereas 55 (68.8%) were TLE+. When modeling the association between MEG method, iEEG, and postoperative surgical outcome (odds of a worse [International League Against Epilepsy (ILAE) class > 2] outcome), a significant result was seen only for UDvs beamformer (odds ratio [OR] = 1.22, 95% confidence interval [CI] = 1.01-1.48). Likewise, when the relationship between MEG method, iEEG, and classification (TLE and TLE+) was modeled, only UDvs beamformer had a significant association (OR = 1.47, 95% CI = 1.13-1.92). When modeling the association between EC hub location and resection/ablation to postoperative surgical outcome (odds of a good [ILAE 1-2] outcome), a significant association was seen (OR = 1.22, 95% CI = 1.05-1.43).

SIGNIFICANCE

This study demonstrates a concordance between UDvs beamforming and iEEG that is related to both postsurgical seizure outcome and presurgical classification of epilepsy (TLE and TLE+). UDvs beamforming could be a complementary approach to the well-established ECD, improving invasive electrode and surgical resection planning for patients undergoing epilepsy surgery evaluations and treatments.