Falk Volkmar, Mourgues Fabien, Adhami Louaï, Jacobs Stefan, Thiele Holger, Nitzsche Stefan, Mohr Friedrich W, Coste-Manière Eve
Herzzentrum, Klinik für Herzchirurgie, Leipzig, Germany.
Ann Thorac Surg. 2005 Jun;79(6):2040-7. doi: 10.1016/j.athoracsur.2004.11.060.
The aim of this study is to optimize the set-up and port placement in robotic surgery and enhance intraoperative orientation by video overlay of the angiographic coronary tree.
In three mongrel dogs and two sheep an electrocardiogram-triggered computed tomographic scan and coronary angiography were performed after placing cutaneous fiducials. The regions of interest (ie, heart, ribs, coronaries, internal thoracic artery) were segmented semiautomatically to create a virtual model of the animal. In this model the target regions of the total endoscopic bypass procedure along the internal thoracic artery and anastomotic area were defined. Algorithms for weighing visibility, dexterity, and collision avoidance were calculated after defining nonadmissible areas using a virtual model of the manipulator. Intraoperatively, registration of the animal and the telemanipulator was performed using encoder data of the telemanipulator by pointing to the fiducials. After pericardiotomy, the reconstructed coronary tree was projected into the videoscopic image using a semiautomatic alignment procedure. In dogs, the total endoscopic bypass procedure was completed on the beating heart. The first human case applying preoperative planning, intraoperative registration, and augmented reality was subsequently performed.
The rigid transformation linked the patient's preoperative frame and the robot coordinate frame with a root mean square error of 9 to 15 mm. The predicted port placement derived from the model initially varied from the one chosen due to an incomplete formulation of the weighing procedure. After only a few iterations, the algorithm became robust and predicted a collision free triangle. Video overlay of the angiographic coronary tree into the videoscopic image was feasible.
Surgical planning and augmented reality are likely to enhance robotic surgery in the future. A more complete understanding of the surgical decision process is required to better formalize the planning algorithms.
本研究的目的是优化机器人手术的设置和端口放置，并通过冠状动脉造影树的视频叠加来增强术中定位。
在三只杂种犬和两只绵羊身上放置皮肤基准点后，进行心电图触发的计算机断层扫描和冠状动脉造影。对感兴趣区域（即心脏、肋骨、冠状动脉、胸廓内动脉）进行半自动分割，以创建动物的虚拟模型。在该模型中，定义了沿胸廓内动脉和吻合区域的全内镜旁路手术的目标区域。使用操纵器的虚拟模型定义不可接受区域后，计算了权衡可见性、灵活性和避免碰撞的算法。术中，通过指向基准点，使用遥操作器的编码器数据对动物和遥操作器进行配准。心包切开术后，使用半自动对准程序将重建的冠状动脉树投影到视频图像中。在犬类中，在跳动的心脏上完成了全内镜旁路手术。随后进行了第一例应用术前规划、术中配准和增强现实的人类病例。
刚性变换将患者的术前框架和机器人坐标系联系起来，均方根误差为9至15毫米。由于权衡程序的制定不完整，最初从模型得出的预测端口放置与所选的不同。经过几次迭代后，该算法变得稳健，并预测出一个无碰撞三角形。将冠状动脉造影树视频叠加到视频图像中是可行的。
手术规划和增强现实可能会在未来提升机器人手术。需要更全面地理解手术决策过程，以更好地规范规划算法。
