The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes

Roan A LaPlante; Wei Tang; Noam Peled; Deborah I Vallejo; Mia Borzello; Darin D Dougherty; Emad N Eskandar; Alik S Widge; Sydney S Cash; Steven M Stufflebeam

doi:10.1007/s11548-016-1504-2

The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural electrodes

Int J Comput Assist Radiol Surg. 2017 Oct;12(10):1829-1837. doi: 10.1007/s11548-016-1504-2. Epub 2016 Dec 3.

Authors

Roan A LaPlante^{1

2}, Wei Tang³, Noam Peled^{4

5}, Deborah I Vallejo⁶, Mia Borzello⁶, Darin D Dougherty⁷, Emad N Eskandar⁸, Alik S Widge^{7

9}, Sydney S Cash⁶, Steven M Stufflebeam^{4

5

10}

Affiliations

¹ Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. aestrivex@gmail.com.
² Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, 149 13th Street, Charlestown, MA, USA. aestrivex@gmail.com.
³ Department of Neurobiology and Anatomy, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
⁴ Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁵ Department of Radiology, Harvard Medical School, Boston, MA, USA.
⁶ Cortical Physiology Laboratory, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁷ Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁸ Department of Neurological Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁹ Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
¹⁰ Harvard-MIT Health Sciences and Technology, Cambridge, MA, USA.

Abstract

Purpose: Existing methods for sorting, labeling, registering, and across-subject localization of electrodes in intracranial encephalography (iEEG) may involve laborious work requiring manual inspection of radiological images.

Methods: We describe a new open-source software package, the interactive electrode localization utility which presents a full pipeline for the registration, localization, and labeling of iEEG electrodes from CT and MR images. In addition, we describe a method to automatically sort and label electrodes from subdural grids of known geometry.

Results: We validated our software against manual inspection methods in twelve subjects undergoing iEEG for medically intractable epilepsy. Our algorithm for sorting and labeling performed correct identification on 96% of the electrodes.

Conclusions: The sorting and labeling methods we describe offer nearly perfect performance and the software package we have distributed may simplify the process of registering, sorting, labeling, and localizing subdural iEEG grid electrodes by manual inspection.

Keywords: CT; Electrocorticography; Image registration; MRI; Software.

MeSH terms

Algorithms
Brain / diagnostic imaging*
Electrodes, Implanted*
Electroencephalography / instrumentation*
Epilepsy / diagnosis*
Humans
Imaging, Three-Dimensional / methods*
Magnetic Resonance Imaging / methods*
ROC Curve
Software
Tomography, X-Ray Computed / methods*

Abstract

MeSH terms

Grants and funding