ICube Laboratory, CNRS, UMR 7357, Université de Strasbourg, Strasbourg, France.
INSERM, U1099, Rennes, 35000, France.
Int J Comput Assist Radiol Surg. 2018 Jul;13(7):1117-1128. doi: 10.1007/s11548-018-1724-8. Epub 2018 Mar 20.
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.
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.
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.
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.
深部脑刺激(DBS)是一种需要精确定位和电极放置的程序。成功规划的两个关键要素是通过确保安全的轨迹来确保患者的安全,并通过优化刺激点的选择来创造治疗效果。在这项工作中,我们提出了计算机辅助术前 DBS 规划的第一种方法,该方法能够自动优化电极轨迹的安全性和刺激点的位置,从而提供最佳的临床效果。
在以前专注于电极轨迹的研究结果的基础上,我们增加了一组约束条件,指导刺激点的选择。这些约束条件考虑了解剖临床图谱和刺激区域与引起副作用的敏感解剖结构之间的交点所代表的回顾性数据。我们将我们的方法实现到自动术前规划软件中,以评估算法是否能够同时优化电极轨迹和刺激点。
在 18 个病例的数据集上进行的留一法交叉验证表明,使用新的约束条件可以改善预期的结果。关键结构的距离没有减少。刺激区域与对刺激敏感的结构之间的交点最小化。
引入这些新的约束条件可以指导规划选择显示出症状改善趋势的位置,同时最大限度地降低副作用的风险,并且不会对轨迹安全造成任何影响。