How to Recognize and Manage Missing Key Electrodes in Defining the Epileptogenic Zone.

Authors

Hussam Shaker, Samuel Medina Villalon, Jorge Gonzalez-Martinez, Agnes Trebuchon

Published in

Epilepsy currents. Pages 15357597261460901. Sep 29, 2026. Epub Sep 29, 2026.

Abstract

Identifying and localizing the epileptogenic zone (EZ) is the cornerstone of successful epilepsy surgery, as it directly determines surgical efficacy and patient outcomes. Stereoelectroencephalography (SEEG) has emerged as a transformative tool for pinpointing the EZ, offering precise 3-dimensional recordings of seizure activity in individual patients. SEEG does not begin with electrode implantation, but with the formulation of a precise hypothesis regarding the epileptogenic networks involved. This hypothesis is based on data gathered during Phase I investigations, particularly the electroclinical correlations of seizure obtained from video-EEG monitoring. SEEG can be appropriately performed only when a prior estimation of EZ and propagation networks is available. The guiding principle of SEEG is therefore not exhaustive anatomical coverage, but rather the validation of a predefined hypothesis. Consequently, certain brain regions are deliberately not explored, there is always missing electrodes. However, in some cases, we encounter true "missing" electrodes, unanticipated gaps in electrode coverage, that can profoundly impact the diagnostic process. These missing electrodes may create critical gaps in the spatial sampling of epileptic networks, leading to incomplete localization of the EZ. This limitation can hinder the identification of seizure onset zone, propagation pathways, and network interactions, ultimately restricting surgical options and compromising patient outcomes. Current clinical practice highlights a significant knowledge gap in how to anticipate such issues during SEEG planning and how to optimally interpret data when electrode coverage is suboptimal. Key questions remain: How can electrode placement errors be identified early? And how can emerging technologies help compensate for these gaps? In this article, we aim to illustrate and discuss these critical issues.

PMID:
42819520
Bibliographic data and abstract were imported from PubMed on 02 Oct 2026.

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