利用增强现实逐步优化机器人辅助根治性前列腺切除术

J. Noël, M. Moschovas, E. Patel, T. Rogers, J. Marquinez, B. Rocco, A. Mottrie, V. Patel
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引用次数: 1

摘要

导语:随着COVID - 19大流行的持续,外科培训将辅以数字化(1)。Proximie是一个增强现实(AR)平台,可以显示多达4个本地摄像头视图,支持实时或半实时远程监控。它可以优化外科医生在控制台的人体工程学(2),以及机器人仪器的定位。我们描述了在机器人辅助根治性前列腺切除术(RARP)中使用Proximie作为一步一步的指南。使用HDMI电缆连接Intuitive Surgical塔,显示控制台的输出显示和额外的腹腔镜塔。每个网络摄像头都安装在控制台的侧扶手上,对准外科医生的手。通过左侧上象限额外5mm的端口使用独立的“插入”腹腔镜。观察者可以在笔记本电脑和/或智能手机上可视化AR平台的记录。PTZ (pan-tilt-zoom)摄像机可以捕捉手术室、床边助手、端口和病人的位置。我们的视频展示了相对于翻译机器人步骤的姿势、前臂、手腕、手和手指方向的四个摄像机视图中的三个。钳式腕内机械手在吻合过程中可以实现最佳的机械手腕旋转。第二次腹腔镜相机视图显示机器人手臂的体腔角度和床边助手的器械位置,用于神经保留和吻合等关键步骤(3)。控制台时间为100分钟,使用该平台未发生术中并发症或图像传输延迟。注意事项:AR平台可以在实时或录制会话中为RARP创建更深入的学习。双向口头和视觉交流,能够在屏幕上注释,允许远程指导。该平台的实用功能可以在任何地方访问,以预测外科医生的直接环境。这允许进入高容量机构的民主化及其技术的发展(4),以帮助全球患者。潜在的发展是人工智能(AI)网络分析这些记录数据的存储库,以识别术中手部运动和机器人仪器跟踪。增强现实是增强机器人训练、技能传播、精准医疗(5)和外科手术的相关组成部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Step-by-step optimisation of robotic-assisted radical prostatectomy using augmented reality
ABSTRACT Introduction: Surgical training will be complemented by digitalisation, as the COVID 19 pandemic continues (1). Proximie is an augmented reality (AR) platform that can display up to 4 native camera views, with live or semi live telementoring. It can optimise ergonomics of the surgeon at the console (2), and robotic instrument orientation. We describe the utilisation of Proximie as a step-by-step guide in a robotic assisted radical prostatectomy (RARP). Surgical Technique: Author V. P. performed a transperitoneal multiport da Vinci Xi RARP with the Proximie platform: a laptop computer, multiple HD webcams, microphones and speakers. Using an HDMI cable to the Intuitive Surgical tower, output display from the console and an additional laparoscopic tower is shown. Each webcam was mounted to the side armrests of the console, directed at the surgeon's hands. An independent ‘drop in’ laparoscope via an additional 5mm left upper quadrant port was utilised. Observers can visualise the AR platform's recordings on a laptop and/or smartphone. A PTZ (pan-tilt-zoom) camera can capture the operating room, bedside assistant, ports and patient position. Our video demonstrates three of four camera views for posture, forearm, wrist, hand, and finger orientation, relative to the translated robotic steps. A pincer grasp of the endowrist manipulator during anastomosis allows optimal robotic wrist rotation. The second laparoscopic camera view demonstrated intracorporeal angles of robotic arm and bedside assistant's instrument position for critical steps such as nerve sparing and anastomosis (3). The console time was 100 minutes, no intraoperative complications, or delay in image transmission occurred with utilising the platform. Considerations: An AR platform can create deeper learning for RARP in real time or recorded sessions. Two-way verbal and visual communication with ability to annotate on screen, allows long distance mentoring. The platform's utility can be accessed in anywhere, to project surgeons beyond their immediate environment. This allows for democratisation of access to high volume institutions and their evolution of techniques (4), to assist patients globally. Potential developments are artificial intelligence (AI) networks analysing repository of such recorded data, to identify intraoperative hand motion and robotic instrument tracking. AR is a pertinent building block to enhance robotic training, skill dissemination, precision medicine (5) and surgery overall.
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