Abstracts

Rationale:
The workup of drug resistant epilepsy patients who undergo implantation of intracranial electrodes to detect seizure onset zones (SOZ) is inherently multimodal. Data that needs to be visualized during clinical decision making include structural and functional imaging results (such as MRI and PET), electrical stimulation mapping (ESM) results, anatomical location of electrodes and results from electrophysiological analyses. The goal of this project is to develop an open-source, offline, browser-based application for easy displaying, navigating and annotating the implanted electrodes and clinically relevant multi-modal data on an individual subject’s data but also across a pool of subjects.
Method:
The application consists of html, css and javascript files as well as any dependent libraries so no other downloads are needed. It is built to integrate directly with iElvis (Groppe et al., 2017), a imaging preprocessing and electrode localization toolbox built around other freely available software such as Freesurfer (Fischl, 2012) and BioImageSuite (Papademetris et al., 2005) but our viewer also works with data that was preprocessed with other tools. Imaging data and electrodes are rendered using Web Graphics Library and data for individual electrodes are displayed in an accompanying interactive table.
Results:
This tool is browser based (but not web-based) and runs completely offline on the local computer or a server. No installation of software or upload of sensitive data files to a cloud service is needed. It visualizes volumetric, surface and subcortical reconstructions, electrode coordinates and associated labels and other functional data such as fMRI or PET. The intuitive interface allows easy navigation between the 2D-planar views and 3D rendered images with overlaid visualization of electrodes in both views. The rendered image allows adding annotations and multiple labels (i.e. seizure onset, ESM results etc.) to each electrode. Electrodes can be binned into customized groups based on these labels and have their display features (such as shape and color) changed. Surface and subcortical reconstruction displays can be toggled in the 3D view as well. An additional advantage is the ability to aggregate and query information across patients and display data on standard brains.
Conclusion:
This open-source software supplements other previously created applications (Stein, 2017; Papademetris et al., 2005; Narizzano et al., 2017) by providing an intuitive, user-friendly interface to interact with multimodal data from epilepsy patients that were evaluated with intracranial electrodes. It is browser-based and no installation of software or technical knowledge is needed for its use. Ideally, this application will facilitate the complex decision making required by clinicians when discussing data obtained from invasive monitoring of medically refractory epilepsy patients. Furthermore, the ability to integrate data across a pool of patients may be useful for both clinical and research groups as a way to catalog and query their data.
Funding:
:N/A