Anatomical registration of intracranial electrodes. Robust model-based localization and deformable smooth brain-shift compensation methods

Intracranial electrodes are typically localized from post-implantation CT artifacts. Automatic algorithms localizing low signal-to-noise ratio artifacts and high-density electrode arrays are missing. Additionally, implantation of grids/strips introduces brain deformations, resulting in registration...

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Bibliographic Details
Published in:Journal of neuroscience methods 2024-04, Vol.404, p.110056, Article 110056
Main Authors: Blenkmann, Alejandro Omar, Leske, Sabine Liliana, Llorens, Anaïs, Lin, Jack J., Chang, Edward F., Brunner, Peter, Schalk, Gerwin, Ivanovic, Jugoslav, Larsson, Pål Gunnar, Knight, Robert Thomas, Endestad, Tor, Solbakk, Anne-Kristin
Format: Article
Language:English
Subjects:
Brain - diagnostic imaging
Cerebral Cortex - diagnostic imaging
Depth electrodes
EEG (iEEG)
Electrocorticography (ECoG)
Electrodes
Electrodes, Implanted
Electroencephalography - methods
Humans
Intracranial
Magnetic Resonance Imaging - methods
Simulations
Stereo electroencephalography (SEEG)
Subcortical grids
Subdural grids
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Summary:Intracranial electrodes are typically localized from post-implantation CT artifacts. Automatic algorithms localizing low signal-to-noise ratio artifacts and high-density electrode arrays are missing. Additionally, implantation of grids/strips introduces brain deformations, resulting in registration errors when fusing post-implantation CT and pre-implantation MR images. Brain-shift compensation methods project electrode coordinates to cortex, but either fail to produce smooth solutions or do not account for brain deformations. We first introduce GridFit, a model-based fitting approach that simultaneously localizes all electrodes’ CT artifacts in grids, strips, or depth arrays. Second, we present CEPA, a brain-shift compensation algorithm combining orthogonal-based projections, spring-mesh models, and spatial regularization constraints. We tested GridFit on ∼6000 simulated scenarios. The localization of CT artifacts showed robust performance under difficult scenarios, such as noise, overlaps, and high-density implants (
ISSN:0165-0270
1872-678X
1872-678X
DOI:10.1016/j.jneumeth.2024.110056