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Related Experiment Video

Updated: Jan 23, 2026

Deep Brain Stimulation with Simultaneous fMRI in Rodents

Deep Brain Stimulation with Simultaneous fMRI in Rodents

Published on: February 15, 2014

A statistical framework for quantification and visualisation of positional uncertainty in deep brain stimulation

Tushar M Athawale¹, Kara A Johnson¹, Christopher R Butson²

¹Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, USA.

Computer Methods in Biomechanics and Biomedical Engineering. Imaging & Visualization

|June 13, 2019

Summary

Positional uncertainty in deep brain stimulation (DBS) electrodes due to finite imaging resolution is significant. Interactive visualization helps explore these uncertainties for improved patient treatment.

Keywords:

Uncertainty visualisation electrodes probabilistic computation

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Last Updated: Jan 23, 2026

Deep Brain Stimulation with Simultaneous fMRI in Rodents

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Published on: February 15, 2014

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Microelectrode Guided Implantation of Electrodes into the Subthalamic Nucleus of Rats for Long-term Deep Brain Stimulation

Microelectrode Guided Implantation of Electrodes into the Subthalamic Nucleus of Rats for Long-term Deep Brain Stimulation

Published on: October 2, 2015

Area of Science:

Neurosurgery
Medical Imaging
Computational Neuroscience

Background:

Deep brain stimulation (DBS) is a key therapy for movement disorders like Parkinson's disease.
Patient-specific computational models aid surgical and therapeutic decisions in DBS.
Finite resolution of brain imaging (MR, CT) introduces uncertainty in DBS electrode positioning.

Purpose of the Study:

To quantify positional uncertainty of DBS electrodes arising from finite imaging resolution.
To develop a method for visualizing subvoxel positional uncertainties in DBS leads.

Main Methods:

Derived a closed-form mathematical model for DBS electrode geometry.
Devised a statistical framework using Bayesian inference for uncertainty quantification.
Implemented interactive visualization techniques (volume rendering, isosurfacing) for positional uncertainty.

Main Results:

Spatial variations in DBS electrode positions are significant with finite resolution imaging.
The developed statistical framework accurately quantifies subvoxel positional uncertainties.
Interactive visualization effectively demonstrates probabilistic positional variations.

Conclusions:

Finite imaging resolution significantly impacts DBS electrode localization accuracy.
The proposed computational and visualization methods are crucial for understanding and managing DBS lead positional uncertainty.
This work can enhance precision in DBS targeting and optimize patient outcomes.