Personalized tDCS for Focal Epilepsy—A Narrative Review: A Data-Driven Workflow Based on Imaging and EEG Data

Brain Sciences

Steven Beumer¹  Maarten M. Paulides¹  Debby C. W. Klooster¹  Paul Boon¹  Evelien Carrette¹  Rob M. C. Mestrom¹  Raymond van Ee² 

[1] Department of Electrical Engineering, University of Technology Eindhoven, P.O. Box 513, 5600 MB Eindhoven, The Netherlands;Philips Research Eindhoven, High Tech Campus 34, 5656 AE Eindhoven, The Netherlands;

关键词: neurostimulation;    personalized;    forward modeling;    inverse modeling;    transcranial electric stimulation;    clinical outcome;   

DOI  :  10.3390/brainsci12050610

来源: DOAJ

【 摘 要 】

Conventional transcranial electric stimulation(tES) using standard anatomical positions for the electrodes and standard stimulation currents is frequently not sufficiently selective in targeting and reaching specific brain locations, leading to suboptimal application of electric fields. Recent advancements in in vivo electric field characterization may enable clinical researchers to derive better relationships between the electric field strength and the clinical results. Subject-specific electric field simulations could lead to improved electrode placement and more efficient treatments. Through this narrative review, we present a processing workflow to personalize tES for focal epilepsy, for which there is a clear cortical target to stimulate. The workflow utilizes clinical imaging and electroencephalography data and enables us to relate the simulated fields to clinical outcomes. We review and analyze the relevant literature for the processing steps in the workflow, which are the following: tissue segmentation, source localization, and stimulation optimization. In addition, we identify shortcomings and ongoing trends with regard to, for example, segmentation quality and tissue conductivity measurements. The presented processing steps result in personalized tES based on metrics like focality and field strength, which allow for correlation with clinical outcomes.

【 授权许可】

Unknown