Abstract
Directional deep brain stimulation (DBS) leads are now widely used, but the orientation of directional leads needs to be taken into account when relating DBS to neuroanatomy. Methods that can reliably and unambiguously determine the orientation of directional DBS leads are needed. In this study, we provide an enhanced algorithm that determines the orientation of directional DBS leads from postoperative CT scans. To resolve the ambiguity of symmetric CT artifacts, which in the past, limited the orientation detection to two possible solutions, we retrospectively evaluated four different methods in 150 Cartesia™ directional leads, for which the true solution was known from additional X-ray images. The method based on shifts of the center of mass (COM) of the directional marker compared to its expected geometric center correctly resolved the ambiguity in 100% of cases. In conclusion, the DiODe v2 algorithm provides an open-source, fully automated solution for determining the orientation of directional DBS leads.
Highlights
Directional leads have become the new standard in deep brain stimulation (DBS) for Parkinson’s disease and Essential tremor
Directional DBS leads vastly increase the number of possible stimulation parameters, of which an optimal subset needs to be chosen in an individual patient
We previously demonstrated that lead orientation can be reliably detected using the open-source Directional Orientation Detection (DiODe) algorithm, which analyzes the streak artifacts generated by different elements of the directional lead on postoperative CT scans [14,15]
Summary
Directional leads have become the new standard in deep brain stimulation (DBS) for Parkinson’s disease and Essential tremor. Directional DBS leads vastly increase the number of possible stimulation parameters, of which an optimal subset needs to be chosen in an individual patient. This selection process can be guided by a priori neuroanatomical knowledge [3], probabilistic sweet spots [4,5] or individual neuroimaging [6], but detailed information about the lead’s location and orientation with respect to the surrounding anatomy is needed. We demonstrate the validity of the algorithm in a large retrospective dataset
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
