The role of MEG cluster characteristics in defining the epileptogenic zone: A retrospective study of 101 seizure-free patients.
TL;DR
The findings support incorporating detailed analysis of MEG cluster characteristics into presurgical evaluation to refine EZ localization, especially for invasive evaluation.
Abstract
Objective
Magnetoencephalography (MEG) is used widely in presurgical evaluation of medically intractable epilepsy. Prior research has documented the added value of MEG in refining surgical strategies; however, not all MEG clusters require resection for seizure freedom, suggesting that they represent nodes within a broader epileptic network, with differing importance for epileptogenic zone (EZ) localization. We examined whether MEG cluster characteristics can identify clusters most relevant to EZ.
Methods
We studied 101 patients with focal epilepsy who underwent intracranial electroencephalography (ICEEG), resective surgery, and became seizure-free at 1 year. MEG recordings were obtained with a 306-channel system and analyzed using single equivalent current dipole (SECD) modeling. Clusters were categorized by anatomic location, tightness, and orientation and defined as "matched" with the EZ if ≥70% of dipoles were included in the resection. A sublobar anatomo-functional scheme was used to map cluster-resection spatial relationships. Logistic regression and generalized linear mixed models with patient as a random effect evaluated age, sex, epilepsy duration, prior surgery, and cluster characteristics. Match rates were compared across pathology groups.
Results
Clusters in frontal and interlobar junctional regions were less likely than temporal clusters to be matched (p = .003 and p = .005). Clusters from patients with multiple clusters were less likely to be matched (p < .001). Tight clusters were more likely matched than loose clusters (p = .013). Cluster-resection mapping identified distinct propagation patterns, including anterior-posterior temporal and ipsilateral-contralateral opercular spread. Among 49 mismatched clusters sampled with ICEEG, 91% showed interictal discharges and 63% were involved in seizure propagation. Match rates did not differ by pathology.
Significance
Our findings support incorporating detailed analysis of MEG cluster characteristics into presurgical evaluation to refine EZ localization, especially for invasive evaluation. Cluster-resection mapping patterns may assist surgical hypothesis generation. Matched clusters in mild malformation of cortical development and negative pathology cases further highlight MEG's value in challenging pathological substrates.