Patient-specific solution of the electrocorticography forward problem in deforming brain

Benjamin F Zwick; George C Bourantas; Saima Safdar; Grand R Joldes; Damon E Hyde; Simon K Warfield; Adam Wittek; Karol Miller

doi:10.1016/j.neuroimage.2022.119649

Patient-specific solution of the electrocorticography forward problem in deforming brain

Neuroimage. 2022 Nov:263:119649. doi: 10.1016/j.neuroimage.2022.119649. Epub 2022 Sep 24.

Authors

Benjamin F Zwick¹, George C Bourantas², Saima Safdar², Grand R Joldes², Damon E Hyde³, Simon K Warfield³, Adam Wittek², Karol Miller⁴

Affiliations

¹ Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia. Electronic address: benjamin.zwick@uwa.edu.au.
² Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia.
³ Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
⁴ Intelligent Systems for Medicine Laboratory, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia; Harvard Medical School, Boston, MA, USA.

PMID: 36167268
DOI: 10.1016/j.neuroimage.2022.119649

Abstract

Invasive intracranial electroencephalography (iEEG), or electrocorticography (ECoG), measures electric potential directly on the surface of the brain and can be used to inform treatment planning for epilepsy surgery. Combined with numerical modeling it can further improve accuracy of epilepsy surgery planning. Accurate solution of the iEEG forward problem, which is a crucial prerequisite for solving the iEEG inverse problem in epilepsy seizure onset zone localization, requires accurate representation of the patient's brain geometry and tissue electrical conductivity after implantation of electrodes. However, implantation of subdural grid electrodes causes the brain to deform, which invalidates preoperatively acquired image data. Moreover, postoperative magnetic resonance imaging (MRI) is incompatible with implanted electrodes and computed tomography (CT) has insufficient range of soft tissue contrast, which precludes both MRI and CT from being used to obtain the deformed postoperative geometry. In this paper, we present a biomechanics-based image warping procedure using preoperative MRI for tissue classification and postoperative CT for locating implanted electrodes to perform non-rigid registration of the preoperative image data to the postoperative configuration. We solve the iEEG forward problem on the predicted postoperative geometry using the finite element method (FEM) which accounts for patient-specific inhomogeneity and anisotropy of tissue conductivity. Results for the simulation of a current source in the brain show large differences in electric potential predicted by the models based on the original images and the deformed images corresponding to the brain geometry deformed by placement of invasive electrodes. Computation of the lead field matrix (useful for solution of the iEEG inverse problem) also showed significant differences between the different models. The results suggest that rapid and accurate solution of the forward problem in a deformed brain for a given patient is achievable.

Keywords: Biomechanics; Diffusion tensor imaging; Electroencephalography; Epilepsy; Finite element method (FEM); Meshless methods.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Brain / diagnostic imaging
Electrocorticography*
Electrodes, Implanted
Electroencephalography / methods
Epilepsy*
Humans
Magnetic Resonance Imaging / methods