From virtual reality simulation to collaborative surgery: Enabling data-driven teleoperated percutaneous nephrolithotomy****

经皮肾镜取石术（PCNL）很快被确立为治疗大型尿路结石的主要方法。尽管经过了40多年的发展，PCNL仍然是一个具有挑战性的学习过程。特别是经验不足的人，与其他内窥镜手术相比，PCNL可能导致更高的并发症发生率。培养足够的专业知识以获得手术能力并非易事，因为它包括进入肾脏的培训，还包括结石碎裂、工具导航和结石清除方面的培训。由于过程的陡峭学习曲线和固有的复杂性，PCNL住院医生在训练过程中不可避免地会进行一定数量的次优干预。****Marion Surgical已经确定需要改进PCNL训练，并将其作为一种安全有效的治疗方法。该公司开发了一种虚拟现实模拟器，使住院医生有机会在不损害患者安全的系统环境中进行培训。该系统可以再现手术室的样子，并向操作员提供肾脏的实时透视图像，操作员使用力反馈装置操纵手术工具。后者模拟了触摸人体组织的感觉，就像在现实世界的干预一样。****这次合作的目的是创建一个数据驱动的远程机器人系统，与外科医生一起共同操作手术工具，以改善住院医生的临床结果。该项目将在机器人辅助手术的新兴领域培养两名硕士生，该项目的成果将在PCNL期间带来更好的临床结果。这将使马里恩外科公司能够首次将机器学习应用于不断发展的虚拟手术领域，并有力地进入新兴的手术机器人市场。* * * * * * * *

Percutaneous nephrolithotomy (PCNL) was quickly established as the leading procedure used for management of urinary calculi for large urinary stones. Despite over 40 years of development, PCNL remains a challenging procedure to learn. Particularly in less experienced hands, PCNL can lead to higher complication rates compared to other endoscopic procedures. Developing adequate expertise to achieve surgical competence is not trivial as it involves training in gaining access to the kidney, but also in stone fragmentation, tool navigation, and stone scavenging. Due to the procedure steep learning curve and inherent complexity, PCNL residents will inevitably perform a certain number of sub-optimal interventions during the training process. ****Marion Surgical has identified the need to improve PCNL training and maintain it as a safe and effective treatment for patients. The company has developed a virtual reality simulator that affords residents the opportunity to train in a systematic environment that does not compromise patient safety. The system reproduces what an operating room would look like, and offers real-time fluoroscopic images of the kidney to the operator, who manipulates a surgical tool using a force-feedback device. The latter emulates the sensation of touch with the human tissue and as in a real-world intervention. ****The purpose of this collaboration is to create a data-driven telerobotic system that co-manipulates the surgical tools in tandem with the surgeon in order to improve clinical outcomes of residents. The project will train two Master students in emerging areas of robot-aided surgey and the outcomes of this project will lead to better clinical outcomes during PCNL. It will allow Marion Surgical to develop some of the first-ever applications of machine learning to the growing area of virtual surgery and make a strong entry into the emerging surgical robotics market. ********