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

基本信息

  • 批准号:
    10276975
  • 负责人:
  • 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
  • 起止时间:
    2021-09-01 至 2025-05-31
  • 项目状态:
    未结题

项目摘要

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.
项目摘要/摘要 骨科创伤后关节骨折脱位的手术治疗需要准确的复位和脱位 关节间隙固定术以恢复解剖结构的完整性。在合并关节损伤的踝关节骨折中, 适当的调整与慢性功能损害、机械不稳定和增加的风险有关。 骨性关节炎。尽管术中x射线成像的作用普遍存在,但3D关节空间推算的不确定性 在手眼协调方面的形态和挑战可能会导致团契的错误复位率高达39%-52%- 训练有素的整形外科创伤专家。 这项建议提出了一种新的系统,它结合了术中成像,使用低剂量的CBCT和3D-2D图像 注册,与机器人操纵的骨骼,以准确恢复关节的完整性。该解决方案提供了定量的 术中3D和2D图像的形态分析,无需精确引导机器人器械 以及与传统跟踪导航相关的限制。以下目标是开发和评估 踝关节创伤手术中关节联合损伤的处理方法 (目标1)研制一种关节复位手术机器人。(1A)设计一种新型低调、透光的机器人系统,以 操纵腓骨远端。(1B)建立装置并开发软件来控制机器人的位置和方向。(1C) 评价在身体踝关节标本临床前测试中的基本操作。 (目标2)制定基于图像的关节复位计划和确认。(2a)开发自动三维图像分析 从低剂量CBCT上观察胫腓距间隙,并将脱位的关节与正常对侧进行匹配。(2B) 开发3D-2D图像配准技术来配准机器人并确认关节间隙的准确恢复 从最少的两个透视图。(2C)在身体脚踝标本上进行实验验证。 (目标3)进行系统集成和端到端的绩效评估。(3A)整合AIMS 1的方法 2根据术中图像指导和确认机器人操作。(3B)在身体上评估该系统 模拟脚踝创伤的标本,目标在关节重排时误差小于2 mm和5°。 (目的4)进行安全性和可行性的临床评价。进行临床研究以(4a)遵守护理标准 脚踝骨折手术和(4b)评估了基于图像的机器人方法的基本安全性和可行性。 10例患者的人体临床试验。 这些目标的成功完成将提高目前贫困地区手术的精确度和质量。 通过使用与现有工作流程一致的新方法,实现长期成果。这项研究的成功将会 帮助消除因复位不当(一个主要的成本负担)而进行的翻修手术,并提高长期生活质量 >每年有10万名患者。该平台将由机器人、成像、 和整形外科手术,并转化为临床研究。开发的技术将对创伤外科手术产生更大的影响 该技术可用于脚踝修复,并将适用于其他具有挑战性的关节脱位和长骨骨折的外科治疗。

项目成果

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Ali Uneri其他文献

Ali Uneri的其他文献

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{{ truncateString('Ali Uneri', 18)}}的其他基金

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:
    10461174
  • 财政年份:
    2021
  • 资助金额:
    $ 68.75万
  • 项目类别:
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:
    10683107
  • 财政年份:
    2021
  • 资助金额:
    $ 68.75万
  • 项目类别:

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