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Modeling intracranial electrodes. A simulation platform for the evaluation of localization algorithms.

Alejandro O Blenkmann1,2, Anne-Kristin Solbakk1,2,3,4, Jugoslav Ivanovic3

  • 1Department of Psychology, University of Oslo, Oslo, Norway.

Frontiers in Neuroinformatics
|October 24, 2022
PubMed
Summary

Researchers developed a novel simulation platform to model intracranial electrodes and CT artifacts for epilepsy surgery evaluation. This tool enables standardized validation and optimization of electrode localization methods, improving brain function analysis.

Keywords:
ECoGSEEGdepth electrodesiEEGintracranial electrodessubcortical gridssubdural grids

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Computational Biology

Background:

  • Intracranial electrodes are crucial for pre-surgical evaluation in drug-resistant epilepsy, requiring precise anatomical localization for accurate brain function analysis.
  • Current methods for localizing intracranial electrodes, primarily using MRI and CT scans, lack standardized validation due to the absence of ground truth data.
  • This deficiency hinders the systematic quantification and optimization of electrode localization algorithms.

Purpose of the Study:

  • To develop a computational platform for modeling intracranial electrode arrays and simulating realistic implantation scenarios.
  • To create a standardized method for evaluating and optimizing the performance of electrode localization techniques.
  • To provide a freely accessible resource for the research community to advance epilepsy pre-surgical evaluation.

Main Methods:

  • Novel methods were implemented to model the coordinates of implanted grids, strips, and depth electrodes, along with their associated CT artifacts.
  • Realistic implantation scenarios were simulated, including variations in electrode size, spacing, and brain area coverage.
  • Approximately 50,000 thresholded CT artifact arrays were simulated across 12 noise levels and validated against real patient data.

Main Results:

  • A comprehensive simulation platform was successfully developed, capable of modeling intracranial electrodes and realistic CT artifacts with controlled noise.
  • Simulations included over 3,300 surface grids/strips and 850 depth electrode arrays, validated for spatial deformation, artifact shape, intensity, and noise.
  • The platform was demonstrated to effectively characterize the performance of two cluster-based electrode localization methods.

Conclusions:

  • The developed platform represents the first of its kind for modeling intracranial electrodes and simulating CT artifacts, providing a basis for advanced modeling.
  • Simulations enable systematic and standardized performance evaluation of electrode localization techniques, crucial for improving pre-surgical epilepsy assessment.
  • The simulation methods, results, and an open-source GUI (iElectrodes toolbox) are publicly available to facilitate further research and development.