Optimizing deep brain stimulation parameter selection with detailed models of the electrode-tissue interface.
Deep brain stimulation (DBS) is an established clinical therapy for the treatment of Parkinson's disease. However, selecting stimulation parameters for maximal clinical benefit can be a difficult and time consuming process that typically requires a highly trained and experienced individual to achieve acceptable results. To address this limitation we developed a Windows-based software package (StimExplorer) intended to aid the clinical implementation of DBS technology. StimExplorer uses detailed computer models to provide a quantitative description of the 3D volume of tissue activated (VTA) by DBS as a function of the stimulation parameters and electrode location within the brain. The DBS electric field models explicitly incorporate the capacitance of the electrode-tissue interface, tissue encapsulation of the electrode, and diffusion-tensor based 3D tissue anisotropy and inhomogeneity. The VTA is predicted with models of axonal activation resulting from the applied field. The stimulation models are tailored to the individual patient by reading in their magnetic resonance imaging (MRI) data and interactively scaling 3D anatomical nuclei to fit the patient anatomy. The user also inputs the DBS electrode orientation, location, and impedance data. The software then provides theoretically optimal stimulation parameter suggestions, intended to represent the start point for clinical programming of the DBS device. The software system is packaged into a clinician-friendly graphical user interface that allows for interactive 3D visualization. The goals of the StimExplorer system are to educate clinicians on the impact of stimulation parameter manipulation, and improve the customization of DBS to individual patients.
McIntyre
Cameron C
CC
Department of Biomedical Engineering, Cleveland Clinic Foundation, Cleveland, OH, USA.
Butson
Christopher R
CR
Maks
Christopher B
CB
Noecker
Angela M
AM
D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D046690:Deep Brain Stimulation / Q000295:instrumentation* / Q000379:methods*; D004567:Electrodes, Implanted; D004867:Equipment Design; D019544:Equipment Failure Analysis; D006801:Humans; D008959:Models, Neurological; D013499:Surface Properties; D013813:Therapy, Computer-Assisted / Q000379:methods*