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Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes.

Daria Nesterovich Anderson1, Braxton Osting, Johannes Vorwerk

  • 1Department of Bioengineering, University of Utah, Salt Lake City, UT, United States of America. Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, United States of America.

Journal of Neural Engineering
|December 14, 2017
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Summary
This summary is machine-generated.

An automated algorithm significantly speeds up deep brain stimulation (DBS) programming for movement disorders. This new method efficiently optimizes directional leads, improving treatment accuracy and reducing clinical time.

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Area of Science:

  • Neurosurgery and Biomedical Engineering
  • Computational Neuroscience
  • Medical Device Technology

Background:

  • Deep brain stimulation (DBS) is an increasingly utilized therapy for movement and psychiatric disorders.
  • Advancements in DBS technology, particularly directional leads with numerous small contacts, pose challenges for manual programming due to time constraints.
  • Current trial-and-error programming methods are becoming clinically infeasible with sophisticated DBS lead designs.

Purpose of the Study:

  • To develop and validate an algorithm for the automated, near real-time programming of deep brain stimulation (DBS) systems.
  • To create a system capable of handling a diverse range of DBS lead configurations, including complex directional leads.
  • To optimize DBS programming for enhanced therapeutic efficacy and reduced clinical workload.

Main Methods:

  • Finite element models incorporating anisotropic conductivity were constructed using magnetic resonance imaging and diffusion tensor imaging data.
  • An optimization algorithm was designed to maximize target tissue activation, utilizing the Hessian matrix of electric potential for directional neuron activation approximation.
  • The algorithm was tested on three lead designs (Medtronic 3389, STNAcute, Medtronic-Sapiens) targeting the subthalamic nucleus (STN) for Parkinson's disease.

Main Results:

  • The algorithm achieved patient-specific contact configurations in under 10 seconds, even for complex leads.
  • Directional leads activated over 50% of the STN when centrally placed, compared to 40% for the Medtronic 3389.
  • With off-target placement (2mm lateral), directional leads maintained performance while the Medtronic 3389 activated only 2.9% of the STN.

Conclusions:

  • The proposed DBS programming algorithm is effective for both traditional cylindrical and advanced directional electrodes.
  • This automation significantly reduces clinical programming time, making complex lead programming feasible.
  • The algorithm promotes the adoption of directional leads by demonstrating their superior ability to activate larger target volumes, especially in cases of suboptimal lead placement.