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

Background/Objectives: To create an open-source method for reconstructing microelectrode recording (MER) and deep brain stimulation (DBS) electrode coordinates along multiple parallel trajectories with patient-specific DBS implantation platforms to facilitate DBS research. Methods: We combined the surgical geometry (extracted from WayPoint Planner), pre-/intra-/postoperative computed tomography (CT) and/or magnetic resonance (MR) images, and integrated them into the Analysis of Functional NeuroImages (AFNI) neuroimaging analysis environment using functions written in Python. Electrode coordinates were calculated from image-based electrode surfaces and recording trajectory depth values. Coordinates were translated into appropriate trajectories, and were tested for proximity to patient-specific or atlas-based anatomical structures. Final DBS electrode coordinates for 3 patient populations (ventral intermediate nucleus [VIM], subthalamic nucleus [STN], and globus pallidus pars interna [GPi]) were calculated. For STN cases, MER site coordinates were then analyzed to see whether they were inside or outside the STN. Results: Final DBS electrode coordinates were described for VIM, STN, and GPi patient populations. 115/169 (68%) STN MER sites were within 1 mm of the STN in AFNI's Talairach and Tournoux (TT) atlas. Conclusions: DBStar is a robust tool kit for understanding the anatomical location and context of electrode locations, and can easily be used for imaging, behavioral, or electrophysiological analyses.
Stereotact Funct Neurosurg

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