Next Generation Robotic System for Supervised-Autonomous Bowel Anastomosis

项目总结： 该项目的目标是建立一种新的医疗机器人和手术范例来执行临床结肠 共同控制的吻合术。我们将开发和评估新的微型化功能3D成像，人工 基于智能(AI)的实时软组织跟踪和故障保护自主控制策略，可实现 在人类自主机器人软组织手术中。这项提议的长期目标是减少 肠吻合术和其他软组织手术的并发症发生率和改善功能结果 与外科医生的经验无关。吻合术是一项关键且具有挑战性的手术。 在美国，每年有一百万次。然而，高达19%的胃肠道吻合术并发 渗漏、狭窄和狭窄以及吻合口并发症显著增加患者死亡率，最高可达10%。 泰晤士报。外科领域的最新关键进展，如越来越多的微创手术(MIS)和机器人- 使用远程操作的达芬奇机器人的辅助手术(RAS)并没有解决影响 吻合口结局，总体吻合口并发症发生率保持不变。自主机器人 手术系统有可能显著提高效率、安全性和一致性，而不是目前的远程 运营RAS。由于缺乏(A)，自主机器人软组织手术尚未在人类身上得到证实。 精准的3D内窥镜视觉，(B)强大的无标记软组织跟踪，以及(C)故障安全自主控制。 为了满足临床对自主缝合机器人平台的需求，我们开发了一种有监督的自主缝合平台 用于指导重建肠吻合术的机器人系统。我们建议进行首个人类先导研究 一个自动机器人缝合平台。因为肠吻合术的并发症可能 灾难性的，我们实施一种逐步增加的复杂性，从开放的拼接开始 关闭常见的肠切开术，并建立腹腔镜结肠切除术，以确保患者的安全。我们 假设自主机器人软组织手术在人类身上是可行的，并将执行以下任务 与目前的远程机器人RAS技术相比，腹腔镜结肠切除术具有更高的准确性和效率。这个 以下四个具体目标将使这项技术的发展成为可能，并证明其临床可行性。 我们将开发微型化的功能3D成像和组织健康传感(AIM 1)，基于人工智能的无标记 组织跟踪(目标2)、故障安全自主控制策略(目标3)，并在人类中首次演示 以普通肠切开术形式进行的自主软组织外科手术(目标4)。超越肠道 吻合术，在所有软组织管理信息系统和RAS任务中采用这种方法可能是有益的，需要 精确度和可操作性，包括复杂的儿科、泌尿外科和心脏手术。

Project Summary: The goal of this project is to establish a new medical robot and surgical paradigm to perform clinical colonic anastomosis with shared control. We will develop and evaluate novel miniaturized functional 3D imaging, artificial intelligence (AI) based real time soft tissue tracking, and fail-safe autonomous control strategies that enable first in human autonomous robotic soft tissue surgery. The long-term goal of this proposal is to reduce the complication rates and improve functional outcomes of bowel anastomoses and other soft tissue surgeries independent of surgeon’s experience. Anastomoses are critical and challenging procedures performed over a million times per year in the US. However, up to 19% of gastrointestinal anastomoses are complicated by leakage, strictures, and stenosis, and anastomotic complications significantly increase patient mortality up to ten times. Recent key advances in surgery such as progressively more minimally invasive surgery (MIS) and robot- assisted surgery (RAS) using a tele-operated da Vinci robot have not addressed the critical factors influencing anastomotic outcome, and the overall anastomotic complication rates remain unchanged. Autonomous robotic surgery systems have the potential to significantly improve efficiency, safety, and consistency over current tele- operated RAS. Autonomous robotic soft tissue surgery is yet to be demonstrated in humans due to a lack of (a) accurate 3D endoscopic vision, (b) robust markerless soft tissue tracking, and (c) fail safe autonomous control. To address the clinical need for autonomous robotic suturing platforms, we developed a supervised autonomous robotic system for guiding reconstructive bowel anastomosis. We propose to conduct first-in-human pilot studies of an autonomous robotic suturing platform. Because complications from bowel anastomoses can be catastrophic, we implement a stepwise gradual increase of complexity starting with open overstitching of the closure of a common enterotomy and building up to laparoscopic colectomy to ensure patient safety. We hypothesize that autonomous robotic soft tissue surgery is feasible in humans and will perform the task of laparoscopic colectomy with better accuracy and efficiency over current tele-robotic RAS technology. The following four specific aims will enable the development of this technology and demonstrate clinical feasibility. We will develop miniaturized functional 3D imaging and tissue health sensing (Aim 1), AI based markerless tissue tracking (Aim 2), fail-safe autonomous control strategies (Aim 3), and demonstrate first in human autonomous soft tissue surgery in the form of common enterotomy closures (Aim 4). Beyond intestinal anastomosis, adoption of this approach could be beneficial in all soft tissue MIS and RAS tasks requiring precision and maneuverability, including complex pediatric, urological, and cardiac surgery.