Olga Dergachyova1,2,3, Yulong Zhao4,5, Claire Haegelen4,5,6, Pierre Jannin4,5, Caroline Essert7. 1. ICube Laboratory, CNRS, UMR 7357, Université de Strasbourg, Strasbourg, France. olga.dergachyova@univ-rennes1.fr. 2. INSERM, U1099, Rennes, 35000, France. olga.dergachyova@univ-rennes1.fr. 3. Université de Rennes 1, LTSI, Rennes, 35000, France. olga.dergachyova@univ-rennes1.fr. 4. INSERM, U1099, Rennes, 35000, France. 5. Université de Rennes 1, LTSI, Rennes, 35000, France. 6. CHU Rennes, Service de Neurochirurgie, Rennes, 35000, France. 7. ICube Laboratory, CNRS, UMR 7357, Université de Strasbourg, Strasbourg, France.
Abstract
PURPOSE: Deep brain stimulation (DBS) is a procedure requiring accurate targeting and electrode placement. The two key elements for successful planning are preserving patient safety by ensuring a safe trajectory and creating treatment efficacy through optimal selection of the stimulation point. In this work, we present the first approach of computer-assisted preoperative DBS planning to automatically optimize both the safety of the electrode's trajectory and location of the stimulation point so as to provide the best clinical outcome. METHODS: Building upon the findings of previous works focused on electrode trajectory, we added a set of constraints guiding the choice of stimulation point. These took into account retrospective data represented by anatomo-clinical atlases and intersections between the stimulation region and sensitive anatomical structures causing side effects. We implemented our method into automatic preoperative planning software to assess if the algorithm was able to simultaneously optimize electrode trajectory and the stimulation point. RESULTS: Leave-one-out cross-validation on a dataset of 18 cases demonstrated an improvement in the expected outcome when using the new constraints. The distance to critical structures was not reduced. The intersection between the stimulation region and structures sensitive to stimulation was minimized. CONCLUSIONS: Introducing these new constraints guided the planning to select locations showing a trend toward symptom improvement, while minimizing the risks of side effects, and there was no cost in terms of trajectory safety.
PURPOSE: Deep brain stimulation (DBS) is a procedure requiring accurate targeting and electrode placement. The two key elements for successful planning are preserving patient safety by ensuring a safe trajectory and creating treatment efficacy through optimal selection of the stimulation point. In this work, we present the first approach of computer-assisted preoperative DBS planning to automatically optimize both the safety of the electrode's trajectory and location of the stimulation point so as to provide the best clinical outcome. METHODS: Building upon the findings of previous works focused on electrode trajectory, we added a set of constraints guiding the choice of stimulation point. These took into account retrospective data represented by anatomo-clinical atlases and intersections between the stimulation region and sensitive anatomical structures causing side effects. We implemented our method into automatic preoperative planning software to assess if the algorithm was able to simultaneously optimize electrode trajectory and the stimulation point. RESULTS: Leave-one-out cross-validation on a dataset of 18 cases demonstrated an improvement in the expected outcome when using the new constraints. The distance to critical structures was not reduced. The intersection between the stimulation region and structures sensitive to stimulation was minimized. CONCLUSIONS: Introducing these new constraints guided the planning to select locations showing a trend toward symptom improvement, while minimizing the risks of side effects, and there was no cost in terms of trajectory safety.
Entities:
Keywords:
Anatomo-clinical atlas; Deep brain stimulation; Parkinson’s disease; Preoperative planning; Volume of tissue activated
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