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bioRxiv · 10.1101/2021.04.28.441828

Modeling intracranial electrodes

Blenkmann, A. O.·Solbakk, A.-K.·Ivanovic, J.·Larsson, P. G.·Knight, R. T.·Endestad, T.
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Abstract

BackgroundIntracranial electrodes are implanted in patients with drug-resistant epilepsy as part of their pre-surgical evaluation. This allows investigation of normal and pathological brain functions with excellent spatial and temporal resolution. The spatial resolution relies on methods that precisely localize the implanted electrodes in the cerebral cortex, which is critical for drawing valid anatomical inferences about brain function. Multiple methods have been developed to localize implanted electrodes, mainly relying on pre-implantation MRI and post-implantation CT images. However, there is no standard approach to quantify the performance of these methods systematically. The purpose of our work is to model intracranial electrodes to simulate realistic implantation scenarios, thereby providing methods to optimize localization algorithm performance. ResultsWe implemented novel methods to model the coordinates of implanted grids, strips, and depth electrodes, as well as the CT artifacts produced by these. We successfully modeled a large number of realistic implantation "scenarios", including different sizes, inter-electrode distances, and brain areas. In total, more than 3300 grids and strips were fitted over the brain surface, and more than 850 depth electrode arrays penetrating the cortical tissue were modeled. More than 37000 simulations of electrode array CT artifacts were performed in these "scenarios", mimicking the intensity profile and orientation of real artifactual voxels. Realistic artifacts were simulated by introducing different noise levels, as well as overlapping electrodes. ConclusionsWe successfully developed the first platform to model implanted intracranial grids, strips, and depth electrodes and realistically simulate CT artifacts and noise. These methods set the basis for developing more complex models, while simulations allow the performance evaluation of electrode localization techniques systematically. The methods described in this article, and the results obtained from the simulations, are freely available via open repositories. A graphical user interface implementation is also accessible via the open-source iElectrodes toolbox.

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Blenkmann, A. O., Solbakk, A.-K., Ivanovic, J., Larsson, P. G., Knight, R. T., Endestad, T.. 2021-04-29. Modeling intracranial electrodes. https://doi.org/10.1101/2021.04.28.441828

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