Abstracts

Rationale: Phase II monitoring with intracranial electroencephalography (iEEG) is an essential part of surgical epilepsy programs. Implantation arrangements are becoming increasingly complex making source localization and interpretation more difficult. Visualizing electrode locations has therefore become significantly more important.

Several software packages are designed to visualize iEEG electrodes. But these programs are costly or require expensive proprietary software to run, and licensing restrictions limit their use to a handful of computers making interaction with the software inaccessible to a large team. Individual team members invest significant time copying images from visualization software into documents to share with the full team for iEEG interpretation and multidisciplinary epilepsy conferences.

R Analysis and Visualization of Intracranial EEG, or “RAVE”, is a powerful, free, open-source, NIH-funded research tool designed to analyze and visualize iEEG data. RAVE includes a powerful built-in 3-dimensional viewer. This software feature displays stereo electroencephalography (sEEG) electrodes over axial, sagittal and coronal slices of a MRI (figure 1A), in addition to projecting surface electrodes over cortical surface models (figure 1B). Users can scroll and rotate images to pinpoint locations of implanted electrodes.

RAVE was developed for rigorous, reproducible statistical analysis of iEEG recordings for basic science applications. Here we present our workflow for using RAVE to visualize iEEG electrodes as part of our clinical pipeline for surgical epilepsy patients.

Methods: RAVE is written in R using the Shiny package to run interactive web browser applications. Source code and documentation are available at https://openwetware.org/wiki/RAVE. RAVE is deployed from a lab server, and users interact via any web browser from an internet connected device (figure 2).

Pre-operative MRI and post-implantation CT brain are first coregistered. RAVE provides a workflow in which users point and click over electrodes based on the CT projection. Alternatively, a MRI and list of (x,y,z) coordinates for the location of the electrodes can be uploaded to RAVE for visualization.

Results: The implementation of RAVE significantly streamlines electrode localization. After localization is performed, a local web address is provided to the team so that all members can access the visualization software via a web browser to interact with the data. RAVE also provides a function to print out all electrodes, facilitating the process of building presentations for multidisciplinary conferences and surgical planning.

Conclusions: We have incorporated RAVE's free 3-dimensional viewer to facilitate the localization and interactive viewing of intracranial electrodes. Free access to interact with RAVE’s visualization software through an internet connected device facilitates the accurate localization of seizure onset zones, even with complicated arrangements of intracranial electrodes. Visualization with RAVE also merges our clinical and basic science analysis pipelines, saving valuable resources by eliminating the duplication of work.

Funding: Please list any funding that was received in support of this abstract.: NIH R24MH117529 (MSB); NIH R25NS070694 (PJK).