Department of Computer Science, University of North Carolina Wilmington, Wilmington, NC 28403, USA.
Department of Mechanical Engineering, Johns Hopkins University; Baltimore, MD 21211, USA.
Sci Robot. 2022 Jan 26;7(62):eabj2908. doi: 10.1126/scirobotics.abj2908.
Autonomous robotic surgery has the potential to provide efficacy, safety, and consistency independent of individual surgeon's skill and experience. Autonomous anastomosis is a challenging soft-tissue surgery task because it requires intricate imaging, tissue tracking, and surgical planning techniques, as well as a precise execution via highly adaptable control strategies often in unstructured and deformable environments. In the laparoscopic setting, such surgeries are even more challenging because of the need for high maneuverability and repeatability under motion and vision constraints. Here we describe an enhanced autonomous strategy for laparoscopic soft tissue surgery and demonstrate robotic laparoscopic small bowel anastomosis in phantom and in vivo intestinal tissues. This enhanced autonomous strategy allows the operator to select among autonomously generated surgical plans and the robot executes a wide range of tasks independently. We then use our enhanced autonomous strategy to perform in vivo autonomous robotic laparoscopic surgery for intestinal anastomosis on porcine models over a 1-week survival period. We compared the anastomosis quality criteria-including needle placement corrections, suture spacing, suture bite size, completion time, lumen patency, and leak pressure-of the developed autonomous system, manual laparoscopic surgery, and robot-assisted surgery (RAS). Data from a phantom model indicate that our system outperforms expert surgeons' manual technique and RAS technique in terms of consistency and accuracy. This was also replicated in the in vivo model. These results demonstrate that surgical robots exhibiting high levels of autonomy have the potential to improve consistency, patient outcomes, and access to a standard surgical technique.
自主机器人手术有可能提供疗效、安全性和一致性,而不受个别外科医生技能和经验的影响。自主吻合是一项具有挑战性的软组织手术任务,因为它需要复杂的成像、组织跟踪和手术规划技术,以及通过高度适应性的控制策略进行精确执行,这些策略通常在非结构化和可变形的环境中使用。在腹腔镜环境中,由于需要在运动和视觉约束下具有高的可操作性和可重复性,因此此类手术更加具有挑战性。在这里,我们描述了一种用于腹腔镜软组织手术的增强型自主策略,并在体模和体内肠组织中演示了机器人腹腔镜小肠吻合术。这种增强型自主策略允许操作员在自主生成的手术计划之间进行选择,并且机器人可以独立执行各种任务。然后,我们使用增强型自主策略在一周的存活期内对猪模型进行体内自主机器人腹腔镜手术进行肠吻合。我们比较了开发的自主系统、手动腹腔镜手术和机器人辅助手术(RAS)的吻合质量标准,包括针放置校正、缝合间距、缝合咬口大小、完成时间、管腔通畅性和泄漏压力。体模模型中的数据表明,在一致性和准确性方面,我们的系统优于专家外科医生的手动技术和 RAS 技术。在体内模型中也得到了复制。这些结果表明,具有高水平自主性的手术机器人有可能提高一致性、患者结果和获得标准手术技术的机会。