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Probabilistic maps for deep brain stimulation - Impact of methodological differences.

Teresa Nordin1, Dorian Vogel2, Erik Österlund3

  • 1Department of Biomedical Engineering, Linköping University, Linköping, Sweden.

Brain Stimulation
|August 20, 2022
PubMed
Summary
This summary is machine-generated.

Understanding deep brain stimulation (DBS) requires analyzing probabilistic stimulation maps (PSMs). Input data and clustering methods significantly impact PSMs, crucial for optimizing DBS treatment in movement disorders.

Keywords:
Deep brain stimulation (DBS)Electric field simulationEssential tremorFinite element method (FEM)Improvement mapsMRI templateSide effects

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Area of Science:

  • Neurosurgery
  • Neurology
  • Biomedical Engineering

Background:

  • Deep brain stimulation (DBS) is vital for movement disorder treatment.
  • Probabilistic stimulation maps (PSMs) analyze DBS effects but vary methodologically.

Purpose of the Study:

  • To compute a group-specific MRI template and PSMs.
  • To investigate the impact of PSM model parameters on DBS outcomes.

Main Methods:

  • Analyzed dizziness and improvement in 68 essential tremor patients undergoing DBS.
  • Computed patient-specific electric field simulations for 488 DBS settings.
  • Transformed electric fields to a group-specific MRI template for analysis using N-maps, M-maps, wM-maps, and p-maps.

Main Results:

  • DBS input data (screening/clinical settings) had the largest impact on PSMs.
  • Clustering methods also notably affected PSM volumes and positioning.
  • Weighting functions had minimal impact, except for wM-map cluster positioning.

Conclusions:

  • Input data distribution and clustering methods are critical for creating accurate PSMs.
  • PSM analysis is essential for understanding the anatomy-DBS outcome relationship.
  • Optimizing PSM parameters can improve DBS treatment strategies.