Accuracy of omni‐planar and surface casting of epileptiform activity for intracranial seizure localization

Abstract

Summary Objective Intracranial electroencephalography (ICEEG) recordings are performed for seizure localization in medically refractory epilepsy. Signal quantifications such as frequency power can be projected as heatmaps on personalized three‐dimensional (3D) reconstructed cortical surfaces to distill these complex recordings into intuitive cinematic visualizations. However, simultaneously reconciling deep recording locations and reliably tracking evolving ictal patterns remain significant challenges. Methods We fused oblique magnetic resonance imaging (MRI) slices along depth probe trajectories with cortical surface reconstructions and projected dynamic heatmaps using a simple mathematical metric of epileptiform activity (line‐length). This omni‐planar and surface casting of epileptiform activity approach (OPSCEA) thus illustrated seizure onset and spread among both deep and superficial locations simultaneously with minimal need for signal processing supervision. We utilized the approach on 41 patients at our center implanted with grid, strip, and/or depth electrodes for localizing medically refractory seizures. Peri‐ictal data were converted into OPSCEA videos with multiple 3D brain views illustrating all electrode locations. Five people of varying expertise in epilepsy (medical student through epilepsy attending level) attempted to localize the seizure‐onset zones. Results We retrospectively compared this approach with the original ICEEG study reports for validation. Accuracy ranged from 73.2% to 97.6% for complete or overlapping onset lobe(s), respectively, and ~56.1% to 95.1% for the specific focus (or foci). Higher answer certainty for a given case predicted better accuracy, and scorers had similar accuracy across different training levels. Significance In an era of increasing stereo‐EEG use, cinematic visualizations fusing omni‐planar and surface functional projections appear to provide a useful adjunct for interpreting complex intracranial recordings and subsequent surgery planning.

A Taxonomy of Seizure Spread Patterns, Speed of Spread, and Associations With Structural Connectivity

“…To investigate the hierarchical organization of seizure spread patterns across seizures and patients, we need robust measures of seizure spread. Currently, a limited number of studies deploy automated algorithms to quantify seizure spread and usually rely on single features, such as line length 18 or power 2 ; however, we did not know if such algorithms reliably measure seizure spread. Many studies that do quantify spread are performed with a small number of patients or require manual annotations by an epileptologist 19,20 .…”

Modular pipeline for reconstruction and localization of implanted intracranial ECoG and sEEG electrodes

“…There are a large number of ways to visualize electrode locations in the brain [1,[19][20][21][22][23][24][25][26][27][28][29][30]75,76]. Some pipelines involve transforming the brain regions and electrode locations into a common map (MNI) and visualize activity in a single brain [1,28,29].…”

Prediction of Seizure Recurrence. A Note of Caution

“…Variations or extensions of this theme include a final “Improvement over Chance” binary metric that compares the measured AUC to a “chance-level AUC” ( 141 ), accuracy rates based on ROC curves ( 142 ), and an ROC analysis to extrapolate a cut-off value for the most significant predictors of seizure recurrence ( 143 ).…”