DBStar: An Open-Source Tool Kit for Imaging Analysis with Patient-Customized Deep Brain Stimulation Platforms.

Area of Science:

• Neurosurgery
• Neuroimaging
• Computational Neuroscience

Background:

• Accurate localization of deep brain stimulation (DBS) electrodes is crucial for research and clinical applications.
• Existing methods may lack the precision or accessibility required for complex implantation platforms.

Purpose of the Study:

• To develop an open-source method for reconstructing microelectrode recording (MER) and DBS electrode coordinates.
• To facilitate DBS research using patient-specific implantation platforms and advanced neuroimaging techniques.

Main Methods:

• Integrated surgical geometry, CT/MR images, and Python functions within the AFNI environment.
• Calculated electrode coordinates from image-based surfaces and trajectory depths.
• Translated coordinates into trajectories and assessed proximity to anatomical structures for VIM, STN, and GPi targets.

Main Results:

• Successfully calculated final DBS electrode coordinates for VIM, STN, and GPi patient populations.
• 68% of subthalamic nucleus (STN) microelectrode recording sites were within 1 mm of the STN in the TT atlas.

Conclusions:

• DBStar provides a robust toolkit for understanding the anatomical context of electrode locations.
• The tool supports imaging, behavioral, and electrophysiological analyses in DBS research.