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Image-guided, robot-assisted reduction of joint dislocation in orthopaedic surgery

Image-guided, robot-assisted reduction of joint dislocation in orthopaedic surgery
图像引导、机器人辅助减少骨科手术中的关节脱位
批准号:
10276975
负责人:
Ali Uneri
金额:
$68.75万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-01 至 2025-05-31

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中文摘要
翻译
项目总结/摘要 骨科创伤后关节骨折和脱位的手术治疗需要准确复位, 固定关节间隙以恢复解剖完整性。在踝关节骨折合并下胫联合损伤中, 适当的重新排列与慢性功能障碍、机械不稳定和 骨关节炎尽管术中X射线成像发挥着普遍作用,但3D关节空间推算的不确定性 形态学和手眼协调方面的挑战可能导致研究员的复位不良率高达39-52%, 训练有素的创伤骨科专家 该提案提出了一种新的系统,该系统结合了术中成像,使用低剂量CBCT和3D-2D图像 配准,通过机器人操作骨骼精确恢复关节完整性。该解决方案提供定量 从3D和2D术中图像进行形态分析,并精确引导机器人仪器, 以及与传统跟踪导航相关联的限制。以下目标是制定和评价 踝关节创伤手术中下胫联合损伤的治疗方法: (Aim 1)研制关节复位手术机器人。(1a)设计一种新型的低姿态,无线电遥控机器人系统, 操作腓骨远端(1b)构建设备并开发软件来控制机器人的位置和方向。(1c) 在尸体踝关节标本上进行临床前试验,评价基本操作。 (Aim 2)制定基于图像的计划并确认关节复位。(2a)开发自动3D图像分析, 从低剂量CBCT中获取胫腓骨距间隙,并将脱位关节与正常对侧进行匹配。(二) 开发3D-2D图像配准技术,以配准机器人并确认关节空间的准确恢复 从2个透视视图中。(2c)在尸体踝关节标本上进行实验验证。 (Aim 3)进行系统集成和端到端的性能评估。(3a)整合目标1中的方法 2.根据术中图像引导和确认机器人操作。(3b)在尸体中评价系统 模拟踝关节创伤的标本,目标小于2 mm,关节重新对准误差为5°。 (Aim 4)进行安全性和可行性的临床评价。进行临床研究,以(4a)观察以下护理标准: 踝关节骨折手术和(4 b)评估基于图像的机器人方法的基本安全性和可行性, 10名患者的临床试验。 这些目标的成功实现将提高该地区手术的精度和质量, 通过使用与现有工作流程一致的新方法来实现长期成果。这项研究的成功将 有助于消除因复位不良(主要成本负担)而进行的翻修手术,并改善患者的长期生活质量, > 100,000名患者/年。该平台将由机器人、成像、 和整形外科并转化为临床研究。开发的技术将影响创伤外科, 踝关节修复,并将适用于其他具有挑战性的关节脱位和长骨骨折的手术治疗。
英文摘要
PROJECT SUMMARY / ABSTRACT Surgical treatment of joint fractures and dislocations following orthopaedic trauma requires accurate reduction and fixation of the joint space to restore anatomical integrity. In ankle fractures with syndesmotic injuries, inaccuracies in proper realignment are associated with chronic functional impairment, mechanical instability, and increased risk of osteoarthritis. Despite the prevalent role of intraoperative x-ray imaging, uncertainties in spatial reckoning of 3D joint morphology and challenges in hand-eye coordination can result in malreduction rates of up to 39–52% for fellowship- trained orthopedic trauma specialists. This proposal presents a novel system that combines intraoperative imaging, using low-dose CBCT and 3D-2D image registration, with robotic manipulation of the bones to precisely restore joint integrity. The solution offers quantitative analysis of morphology from 3D and 2D intraoperative images and precisely guides a robotic instrument without the need for and the limitations associated with conventional tracked navigation. The following aims develop and evaluate the approach for treatment of syndesmotic injuries in ankle trauma surgery: (Aim 1) Develop a surgical robot for joint reduction. (1a) Design a novel low-profile, radiolucent robotic system to manipulate the distal fibula. (1b) Build the device and develop software to control the robot position and orientation. (1c) Evaluate basic operation in preclinical testing on cadaveric ankle specimens. (Aim 2) Develop image-based planning and confirmation of joint reduction. (2a) Develop automatic 3D image analysis of the tibio-fibulo-talar space from low-dose CBCT and match the dislocated joint to the normal contralateral side. (2b) Develop 3D-2D image registration techniques to register the robot and confirm accurate restoration of the joint space from as few as 2 fluoroscopic views. (2c) Experimentally validate the algorithms on cadaveric ankle specimens. (Aim 3) Perform system integration and end-to-end evaluation of performance. (3a) Integrate the methods from Aims 1 and 2 to guide and confirm robotic manipulation from intraoperative images. (3b) Evaluate the system in cadaver specimens emulating ankle trauma, targeting less than 2 mm and 5° error in joint realignment. (Aim 4) Conduct clinical evaluation of safety and feasibility. Conduct clinical studies to (4a) observe standard of care of ankle fracture surgery and (4b) assess the basic safety and feasibility of the image-based robotic approach in a first in- human clinical trial with 10 patients. Successful completion of the aims will elevate the precision and quality of surgery in an area that currently suffers poor long-term outcomes through use of new methods that are consistent with existing workflows. Success in this research will help to eliminate revision surgeries due to malreduction (a major cost burden) and improve long-term quality of life for >100,000 patients/year. The platform will be developed in a multi-disciplinary consortium of experts in robotics, imaging, and orthopedic surgery and translated to clinical studies. The technology developed will impact trauma surgery beyond ankle repair and would be applicable to surgical treatment of other challenging joint dislocations and long-bone fractures.
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Image-guided, robot-assisted reduction of joint dislocation in orthopaedic surgery
  • 批准号:
    10461174
  • 项目类别:
  • 资助金额:
    $66.2万
  • 财政年份:
    2021
  • 负责人:
    Ali Uneri
  • 依托单位:
Image-guided, robot-assisted reduction of joint dislocation in orthopaedic surgery
  • 批准号:
    10683107
  • 项目类别:
  • 资助金额:
    $65.02万
  • 财政年份:
    2021
  • 负责人:
    Ali Uneri
  • 依托单位:
海外基金