Optimizing the delivery of deep brain stimulation using electrophysiological atlases and an inverse modeling approach

Kay Sun; Srivatsan Pallavaram; William Rodriguez; Pierre-Francois D'Haese; Benoit M. Dawant; Michael I. Miga

doi:10.1117/12.912024

17 February 2012 Optimizing the delivery of deep brain stimulation using electrophysiological atlases and an inverse modeling approach

Kay Sun, Srivatsan Pallavaram, William Rodriguez, Pierre-Francois D'Haese, Benoit M. Dawant, Michael I. Miga

Author Affiliations +

Proceedings Volume 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling; 83162Z (2012) https://doi.org/10.1117/12.912024
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

The use of deep brain stimulation (DBS) for the treatment of neurological movement degenerative disorders requires the precise placement of the stimulating electrode and the determination of optimal stimulation parameters that maximize symptom relief (e.g. tremor, rigidity, movement difficulties, etc.) while minimizing undesired physiological side-effects. This study demonstrates the feasibility of determining the ideal electrode placement and stimulation current amplitude by performing a patient-specific multivariate optimization using electrophysiological atlases and a bioelectric finite element model of the brain. Using one clinical case as a preliminary test, the optimization routine is able to find the most efficacious electrode location while avoiding the high side-effect regions. Future work involves optimization validation clinically and improvement to the accuracy of the model.

Citation Download Citation

Kay Sun, Srivatsan Pallavaram, William Rodriguez, Pierre-Francois D'Haese, Benoit M. Dawant, and Michael I. Miga "Optimizing the delivery of deep brain stimulation using electrophysiological atlases and an inverse modeling approach", Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83162Z (17 February 2012); https://doi.org/10.1117/12.912024

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