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Related Concept Videos

Brain Imaging01:14

Brain Imaging

303
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
303

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Related Experiment Video

Updated: Sep 5, 2025

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
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Automated optimization of deep brain stimulation parameters for modulating neuroimaging-based targets.

Mahsa Malekmohammadi1, Richard Mustakos1, Sameer Sheth2

  • 1Boston Scientific Neuromodulation, 25155 Rye Canyon Loop, Valencia, CA 91355, United States of America.

Journal of Neural Engineering
|July 5, 2022
PubMed
Summary

Deep brain stimulation (DBS) programming is challenging. A new algorithm, DBS Illumina 3D, uses patient imaging to optimize stimulation, minimizing side effects and improving target coverage for conditions like depression.

Keywords:
DBSneuroanatomyprogrammingtreatment resistant depression

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Area of Science:

  • Neurosurgery
  • Neuromodulation
  • Medical Imaging

Background:

  • Deep brain stimulation (DBS) efficacy relies on precise lead placement and optimized programming.
  • Clinical programming is time-consuming and complex due to numerous parameter options.
  • Patient-specific neuroimaging data can potentially improve DBS programming.

Purpose of the Study:

  • To introduce and evaluate the DBS Illumina 3D algorithm for optimizing DBS stimulation parameters.
  • To assess the algorithm's ability to maximize target coverage while minimizing off-target stimulation.

Main Methods:

  • Developed the DBS Illumina 3D algorithm using preoperative and postoperative imaging.
  • Applied the algorithm to three patients with treatment-resistant depression undergoing DBS in the subcallosal cingulate cortex.
  • Compared algorithm-derived settings with clinician-selected settings.

Main Results:

  • DBS Illumina 3D achieved similar or greater target coverage compared to clinician settings.
  • Algorithm-optimized settings significantly reduced the volume of stimulation outside the intended target (P=0.002).

Conclusions:

  • The DBS Illumina 3D algorithm assists clinicians in navigating complex stimulation parameter spaces.
  • This tool integrates with programmer software, offering an optimized starting point for DBS programming.
  • The algorithm enhances image-based anatomical analysis for improved DBS therapy.