Collaborating Investigator: Christopher R. Butson, Ph.D., Medical College of Wisconsin

The CIBC is working with neuroscientist Dr. Chris Butson at the Medical College of Wisconsin to develop new computational tools and methods for planning neurostimulation system implantation surgery as a treatment for Parkinson's Disease. Parkinson’s disease (PD) is a significant health problem for the aging population of the U.S. There are a 1.5 million PD patients in the United States. Despite the success of levodopa-based treatment for PD, many patients develop disabling motor side effects over time. One alternative for these patients is deep brain stimulation (DBS). DBS is a therapy in which a neurostimulation system is implanted in the brain during stereotactic surgery. The effectiveness of DBS is well established, but DBS is not without side effects. The primary side effects are neuropsychological. The problem of DBS treatment is additionally complicated by two factors. First, DBS is a complicated procedure with many free parameters and is heavily dependent on the skill of the clinician. Second, no atlas exists for clinicians to share therapeutic or side effect outcomes for DBS patients.

Dr. Butson and the other collaborators have developed a systematic procedure for pre – and post-operative evaluation of DBS patients, a database of neuropsychological outcomes, and computational methods that predict the effects of DBS on an individual patient basis. A 3D brain atlas anatomical model is used to define the electrode location in the brain from the MRI. A brain atlas is created through merging the differences of many individual normal brains, thereby creating a single representation of a brain that is average in its features and morphology for brains in the general population. The anatomical model is coupled to an electrical model that captures the shapes and forms of the stimulation. The DBS electrodes are surrounded by an anisotropic, inhomogeneous tissue medium. The tissue medium is accounted for with a 3D finite element model (FEM) that incorporates tissue conductivities derived from diffusion tensor imaging and a Fourier FEM solver that accounts for the capacitance of the electrode-tissue interface under voltage-controlled stimulation. The neural response to the DBS is predicted by coupling the electric field data from the FEM to multi-compartment models of axons surrounding the electrode.

The CIBC is focused on solving two general computing problems to assist Dr. Butson and his team: 1) the ability to generate large, complex, multi-resolution finite element models and 2) visualization of the model results. This project will help provide a knowledge base of correlations between stimulation-induced activation of particular brain regions and neuropsychological outcomes. The project will also result in an activation atlas that expresses the knowledge base in an interactive, 3D viewer, using the Center’s SCIRun software. The overall goal is to better manage patient outcomes through use of the knowledge base the project will create, in addition to the potential to predict neuropsychological outcomes in DBS patients.