Next Generation of Surgical Imaging and Robotics for Supervised Autonomous Soft Tissue Surgery

用于监督自主软组织手术的下一代手术成像和机器人技术

• 批准号: 9234534
• 负责人: Jin U Kang
• 金额: $ 8.64万
• 依托单位: CHILDREN'S RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9234534
• 关键词: Address; Adoption; Affect; Algorithms; Anastomosis - action; Anatomy; Blood Vessels; Cardiac; Cardiac Surgery procedures; Cardiovascular system; Childhood; Clinical; Cognition; Colorectal; Complex; Complication; Custom; Effectiveness; Endoscopy; Environment; Extravasation; Family suidae; Gastrointestinal Surgical Procedures; Goals; Gynecologic; Gynecologic Surgical Procedures; Gynecology; Hour; Image; Image-Guided Surgery; Imagery; Individual; Injury; Intestines; Location; Manuals; Methods; Modeling; Operative Surgical Procedures; Outcome; Patients; Peripheral; Physiological; Procedures; Quality of life; Reconstructive Surgical Procedures; Research; Robot; Robotics; Rupture; Site; Slave; Stenosis; Structure; Supervision; Surgeon; Surgical sutures; System; Techniques; Technology; Testing; Thick; Time; Tissues; Training; Transplantation; Urologic Surgical Procedures; Visceral; Vision; Visual Fields; Visuospatial; base; biomaterial compatibility; dexterity; ergonomics; experience; functional outcomes; gastrointestinal; imaging system; improved; improved functioning; in vivo; innovation; minimally invasive; mortality; next generation; novel; preclinical study; public health relevance; robot assistance; robot control; soft tissue; stem; technology development; tool; urologic

 DESCRIPTION (provided by applicant): Anastomosis is a necessary and critical part of all reconstructive surgery involving any luminal structure from cardiovascular to gastrointestinal (GI) surgery. Well over a million anastomoses are performed in the USA each year for visceral indications alone (gastrointestinal, urologic and gynecologic surgery). However, up to 30% of GI anastomoses are complicated by leakage, strictures, and stenosis, in part attributable to technical and technologic issues. An anastomotic complication significantly increases patient mortality from three times up to ten times, and diminishes the function and quality of life for affected patients. Although the minimally invasive surgical approach has transformed surgery with significantly reduced collateral tissue damage associated with access to operative sites, recent advances in surgical tools and vision technology have not addressed the critical factors influencing anastomotic outcome. This is evidenced by the lack of improvements in complication rates. To the contrary, the current minimally invasive surgery (MIS) or robot assisted surgery (RAS) pose additional new challenges for anastomosis stemming from visual and spatial limitations. The long-term goal of this research is to reduce complications and improve functional outcomes of anastomosis by robotically executing best anastomosis techniques. The following specific aims will enable the development of this technology and demonstrate feasibility, as a path to clinical adoption: Aim 1: Identify optimal suture placements using multispectral imaging. We will compare suture placements and anastomotic outcome between those guided by our novel algorithm for suture location optimization incorporating subsurface anatomic and physiologic information and those performed by expert surgeons in pre-clinical studies. Aim 2: Accurately track mobile and deformable soft tissue targets in an unstructured surgical environment. We will demonstrate how our innovative fused 3D tracking based on plenoptic imaging and NIR marker technology allows real-time, accurate identification and tracking of tissue targets during the task of anastomosis in contrast to current tracking methods in phantom and in-vivo studies. Aim 3: Compare supervised autonomous robotic control to manual anastomosis. We will compare the algorithm of automated suture planning controlled by supervised autonomous robotics to current standard master-slave robotic and manual laparoscopic technology in performing in-vivo anastomosis in preclinical studies. This research has the potential to significantly improve the function and outcome of anastomosis, independent of surgeon experience. Beyond anastomosis, adoption of this approach could be beneficial in all soft tissue MIS and RAS tasks requiring precision and maneuverability due to small working space, including pediatric and complex cardiac surgery.

 描述（由申请人提供）：吻合术是所有涉及从心血管到胃肠道 (GI) 手术的任何管腔结构的重建手术的必要且关键的部分，美国每年仅针对内脏适应症（胃肠道、胃肠道、胃肠道）进行超过一百万次吻合术。泌尿科和妇科手术）然而，高达 30% 的胃肠道吻合术因渗漏、狭窄和并发症而变得复杂。狭窄，部分归因于技术和技术问题，使患者死亡率显着增加三倍至十倍，并降低受影响患者的功能和生活质量，尽管微创手术方法已经改变了手术，大大减少了手术的时间。与手术部位相关的附带组织损伤、手术工具和视觉技术的最新进展并没有解决影响吻合结果的关键因素，相反，目前的并发症发生率缺乏改善。由于视觉和空间限制，微创手术（MIS）或机器人辅助手术（RAS）给吻合术带来了额外的新挑战。这项研究的长期目标是通过机器人执行最佳吻合技术来减少并发症并改善吻合术的功能结果。以下具体目标将促进该技术的发展并证明其作为临床采用途径的可行性： 目标 1：使用多光谱成像确定最佳缝合位置 我们将比较缝合位置和吻合术。目标 2：在非结构化手术环境中准确跟踪移动和可变形软组织目标。与目前的体模和 NIR 跟踪方法相比，我们基于全光成像和 NIR 标记技术的创新融合 3D 跟踪如何能够在吻合任务期间实时、准确地识别和跟踪组织目标目标 3：将监督自主机器人控制与手动吻合进行比较 我们将在临床前进行体内吻合时将监督自主机器人控制的自动缝合规划算法与当前标准主从机器人和手动腹腔镜技术进行比较。这项研究有可能显着改善吻合术的功能和结果，除了吻合术之外，采用这种方法可能对所有软组织 MIS 和手术都有益。由于工作空间狭小，RAS 任务需要精确性和可操作性，包括儿科和复杂的心脏手术。