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Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation
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Model-Based Deep Brain Stimulation Programming for Parkinson's Disease: The GUIDE Pilot Study.

Michael H Pourfar1, Alon Y Mogilner, Sierra Farris

  • 1Department of Neurosurgery, Center for Neuromodulation, NYU Langone Medical Center, New York, N.Y., USA.

Stereotactic and Functional Neurosurgery
|May 23, 2015
PubMed
Summary
This summary is machine-generated.

A new computer model for deep brain stimulation (DBS) programming in Parkinson's disease patients yielded similar symptom improvement to traditional methods. This model also reduced programming time and power consumption.

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Area of Science:

  • Neurology
  • Neurosurgery
  • Biomedical Engineering

Background:

  • Deep brain stimulation (DBS) programming requires extensive clinician time.
  • The Graphical User Interface for DBS Evaluation (GUIDE) study investigated a visual programming system.
  • Optimizing DBS settings is crucial for Parkinson's disease (PD) patients.

Purpose of the Study:

  • To evaluate a neuroanatomically based computer model for predetermining DBS stimulation settings.
  • To compare the efficacy of model-derived settings versus traditional clinical programming.
  • To assess time efficiency and power consumption of the model-based approach.

Main Methods:

  • A multicenter prospective, observational study.
  • Blinded Unified Parkinson's Disease Rating Scale (UPDRS)-III examinations.
  • Comparison of model-derived settings (Model) with traditional monopolar review-based programming (Clinical).

Main Results:

  • No statistically significant difference in UPDRS-III improvement between Model (10.4 ± 7.8) and Clinical (11.7 ± 8.7) settings.
  • Model settings required significantly less power (48.7 ± 22 μW vs. 76.1 ± 46.5 μW).
  • Model programming time was substantially reduced (31 ± 16 s vs. 41.4 ± 29.1 min).

Conclusions:

  • Model-based DBS settings offer comparable clinical benefit to traditional methods.
  • The model-based approach is more time-efficient and conserves power.
  • This visual programming system shows promise for optimizing DBS therapy in Parkinson's disease.