Advances in Computer Assisted Mosaic Arthroplasty

软骨变性是一种普遍存在的问题，主要发生在膝关节、踝关节和肩部。对于年轻、活跃的患者，早期软骨置换可以大大提高生活质量，并可以延迟或消除最终对假体关节置换术的需求，为加拿大医疗保健系统节省大量资金。马赛克关节成形术是一种外科手术，将软骨和骨塞从关节的非承重区域移植到软骨缺损的部位。我们已经在之前的研究中表明，计算机辅助的马赛克关节置换术（CAMA）比传统的马赛克关节置换术有更好的临床效果。拟议的研究将培训四名研究生和三名本科生，将开发计算机算法和用户界面，以在三个方面改善CAMA的交付：几乎所有的计算机辅助手术都需要患者进行CT或MRI扫描，然后是术前计划阶段，然后是手术。我们将CAMA的扫描和计划阶段分解为手术本身：术中，外科医生将使用跟踪关节镜探头扫描软骨表面，使用计划算法制定手术计划，并使用计算机跟踪和指导执行计划。这可以减少等待时间，减少病人暴露在电离辐射下的时间。2. 对于关节镜CAMA，我们将为外科医生提供增强现实引导显示器，其中手术计划叠加在关节镜实时视频上，显示在患者旁边的显示器上。这将减轻外科医生的认知负担，使手术更有可能成功。3. CAMA工具指导的一种方法是使用在3D打印机上制造的针对患者的指南；它们的底部与患者的软骨表面紧密贴合，顶部有引导手术工具的孔。我们将开发一种自动设计指南的计算机算法，对操作员隐藏的启发式知识进行编码，比目前的手动方法节省大量操作员的时间。

Cartilage degeneration is a widespread problem which occurs predominantly in the knee, ankle, and shoulder. For younger, active patients, early cartilage replacement can result in a much improved quality of life and can delay or eliminate the eventual need for prosthetic joint replacement, with substantial savings to the Canadian healthcare system. Mosaic arthroplasty is a surgical procedure in which plugs of cartilage and bone are transplanted from non-load-bearing areas of the joint to the site of the cartilage defect. We have shown in previous research that computer-assisted mosaic arthroplasty (CAMA) results in better clinical outcomes than conventional mosaic arthroplasty. The proposed research, which will train four graduate and three undergraduate students, will develop computer algorithms and user interfaces to improve the delivery of CAMA in three areas: 1. Almost all computer-assisted operations involve a patient CT or MRI scan, followed by a pre-operative planning stage, followed by the operation. We will collapse the scanning and planning stages of CAMA into the operation itself: The surgeon will intraoperatively scan the cartilage surface with a tracked arthroscope probe, will use a planning algorithm to develop a surgical plan, and will execute the plan using computer tracking and guidance. This can reduce waiting times and can reduce patient exposure to ionizing radiation. 2. For arthroscopic CAMA, we will provide the surgeon with an augmented reality guidance display, where the surgical plan is superimposed on the live arthroscope video, shown on a display beside the patient. This will reduce the cognitive burden on the surgeon and may make the success of the operation more likely. 3. One method of CAMA tool guidance uses patient-specific guides, which are manufactured on a 3D printer; their bottom side fits tightly to the patient's cartilage surface and their top side contains holes to guide the surgical tools. We will develop a computer algorithm that designs the guides automatically, encoding the operator's hidden heuristic knowledge and saving substantial operator time over the current manual method.