Gu Wenhao, Knopf Jonathan, Cast John, Higgins Laurence D, Knopf David, Unberath Mathias
Johns Hopkins University, Baltimore, MD, USA.
Arthrex Inc., 1 Arthrex Way, Naples, FL, USA.
Int J Comput Assist Radiol Surg. 2023 Jul;18(7):1235-1243. doi: 10.1007/s11548-023-02950-x. Epub 2023 May 25.
PURPOSE: Mixed reality-guided surgery through head-mounted displays (HMDs) is gaining interest among surgeons. However, precise tracking of HMDs relative to the surgical environment is crucial for successful outcomes. Without fiducial markers, spatial tracking of the HMD suffers from millimeter- to centimeter-scale drift, resulting in misaligned visualization of registered overlays. Methods and workflows capable of automatically correcting for drift after patient registration are essential to assuring accurate execution of surgical plans. METHODS: We present a mixed reality surgical navigation workflow that continuously corrects for drift after patient registration using only image-based methods. We demonstrate its feasibility and capabilities using the Microsoft HoloLens on glenoid pin placement in total shoulder arthroplasty. A phantom study was conducted involving five users with each user placing pins on six glenoids of different deformity, followed by a cadaver study by an attending surgeon. RESULTS: In both studies, all users were satisfied with the registration overlay before drilling the pin. Postoperative CT scans showed 1.5 mm error in entry point deviation and 2.4[Formula: see text] error in pin orientation on average in the phantom study and 2.5 mm and 1.5[Formula: see text] in the cadaver study. A trained user takes around 90 s to complete the workflow. Our method also outperformed HoloLens native tracking in drift correction. CONCLUSION: Our findings suggest that image-based drift correction can provide mixed reality environments precisely aligned with patient anatomy, enabling pin placement with consistently high accuracy. These techniques constitute a next step toward purely image-based mixed reality surgical guidance, without requiring patient markers or external tracking hardware.
目的:通过头戴式显示器(HMD)进行的混合现实引导手术正受到外科医生的关注。然而,HMD相对于手术环境的精确跟踪对于成功的手术结果至关重要。如果没有基准标记,HMD的空间跟踪会出现毫米到厘米级别的漂移,导致注册叠加层的可视化未对齐。能够在患者注册后自动校正漂移的方法和工作流程对于确保手术计划的准确执行至关重要。 方法:我们提出了一种混合现实手术导航工作流程,该流程仅使用基于图像的方法在患者注册后持续校正漂移。我们在全肩关节置换术中使用Microsoft HoloLens进行肩胛盂销钉置入,展示了其可行性和能力。进行了一项模型研究,涉及五名用户,每个用户在六个不同畸形的肩胛盂上放置销钉,随后由一名主治外科医生进行尸体研究。 结果:在两项研究中,所有用户在钻销钉前对注册叠加层都很满意。术后CT扫描显示,在模型研究中,平均进入点偏差误差为1.5毫米,销钉方向误差为2.4[公式:见正文];在尸体研究中,误差分别为2.5毫米和1.5[公式:见正文]。一名经过培训的用户完成该工作流程大约需要90秒。我们的方法在漂移校正方面也优于HoloLens原生跟踪。 结论:我们的研究结果表明,基于图像的漂移校正可以提供与患者解剖结构精确对齐的混合现实环境,从而能够始终如一地高精度放置销钉。这些技术朝着纯粹基于图像的混合现实手术引导迈出了下一步,无需患者标记或外部跟踪硬件。
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