Hao Ran, Itsarachaiyot Yuttana, Çavuşoğlu M Cenk
Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH.
Int Symp Med Robot. 2024 Jun;2024. doi: 10.1109/ismr63436.2024.10585608. Epub 2024 Jul 12.
Left atrial appendage occlusion is a procedure to reduce the risk of thromboembolism in atrial fibrillation patients by blocking the left atrial appendage ostium using an occlusion device implanted by an intra-vascular delivery catheter. The preprocedural planning of the left atrial appendage occlusion procedure aims to identify an optimal implantation trajectory for a successful occlusion implant delivery from a structural understanding of the left atrial appendage. In this paper, a Bayesian Optimization based preprocedural planning approach is proposed for the robotic left atrial appendage occlusion procedure. The preprocedural planner efficiently samples transseptal puncture positions over the fossa ovalis and sequentially optimizes the transseptal puncture location. The iterative linear-quadratic-regulator is employed by the Bayesian Optimization planner for locally optimizing the occlusion trajectory for a given transseptal puncture location. The performance of the proposed Bayesian Optimization based preprocedural planner is evaluated in a simulation environment using a real cardiac anatomy model.
左心耳封堵术是一种通过使用血管内输送导管植入封堵装置来封闭左心耳开口，从而降低房颤患者血栓栓塞风险的手术。左心耳封堵手术的术前规划旨在从左心耳的结构理解出发，确定一条最佳植入轨迹，以便成功植入封堵装置。本文提出了一种基于贝叶斯优化的术前规划方法，用于机器人辅助左心耳封堵手术。术前规划器在卵圆窝上高效地采样经房间隔穿刺位置，并依次优化经房间隔穿刺位置。贝叶斯优化规划器采用迭代线性二次调节器，针对给定的经房间隔穿刺位置局部优化封堵轨迹。在使用真实心脏解剖模型的模拟环境中评估了所提出的基于贝叶斯优化的术前规划器的性能。
