Mirota Daniel J, Uneri Ali, Schafer Sebastian, Nithiananthan Sajendra, Reh Douglas D, Gallia Gary L, Taylor Russell H, Hager Gregory D, Siewerdsen Jeffrey H
Department of Computer Science, Johns Hopkins University, Baltimore MD.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD.
Proc SPIE Int Soc Opt Eng. 2011 Feb;7964. doi: 10.1117/12.877803. Epub 2011 Mar 1.
Registration of endoscopic video to preoperative CT facilitates high-precision surgery of the head, neck, and skull-base. Conventional video-CT registration is limited by the accuracy of the tracker and does not use the underlying video or CT image data. A new image-based video registration method has been developed to overcome the limitations of conventional tracker-based registration. This method adds to a navigation system based on intraoperative C-arm cone-beam CT (CBCT) that reflects anatomical change, in turn providing high-accuracy registration of video to the surgical scene. The resulting registration enables visualization of the CBCT and planning data within the endoscopic video. The system incorporates a mobile C-arm for high-performance CBCT, integrated with an optical tracking system, video endoscopy, deformable registration of preoperative CT with intraoperative CBCT, and 3D visualization. As in the tracker-based approach, in the image-based video-CBCT registration the endoscope is localized using an optical tracking system that provides a quick initialization followed by a direct 3D image-based registration of the video to the CBCT. In this way, the system achieves video-CBCT registration that is both fast and accurate. Application in skull-base surgery demonstrates overlay of critical structures (e.g., carotid arteries and optic nerves) and surgical target volumes with sub-mm accuracy. Phantom and cadaver experiments show consistent improvement in target registration error (TRE) in video overlay over conventional tracker-based registration - e.g., 0.92 mm versus 1.82 mm for image-based and tracker-based registration, respectively. The proposed method represents a two-fold advance-first, through registration of video to up-to-date intraoperative CBCT (overcoming limitations associated with navigation with respect to preoperative CT), and second, through direct 3D image-based video-CBCT registration, which together provide more confident visualization of target and normal tissues within up-to-date images and improved targeting precision.
将内镜视频与术前CT进行配准有助于对头、颈和颅底进行高精度手术。传统的视频-CT配准受追踪器精度的限制，且未利用基础视频或CT图像数据。一种新的基于图像的视频配准方法已被开发出来，以克服传统基于追踪器配准的局限性。该方法被添加到一个基于术中C臂锥束CT（CBCT）的导航系统中，该系统能反映解剖结构变化，进而实现视频与手术场景的高精度配准。由此产生的配准能够在内镜视频中可视化CBCT和规划数据。该系统集成了一个用于高性能CBCT的移动C臂，与光学追踪系统、视频内窥镜、术前CT与术中CBCT的可变形配准以及三维可视化技术相结合。与基于追踪器的方法一样，在基于图像的视频-CBCT配准中，使用光学追踪系统对内镜进行定位，该系统提供快速初始化，随后将视频直接基于三维图像配准到CBCT上。通过这种方式，该系统实现了快速且准确的视频-CBCT配准。在颅底手术中的应用表明，关键结构（如颈动脉和视神经）和手术目标体积的叠加精度可达亚毫米级。体模和尸体实验表明，与传统基于追踪器的配准相比，视频叠加中的目标配准误差（TRE）持续改善——例如，基于图像和基于追踪器的配准的TRE分别为0.92毫米和1.82毫米。所提出的方法代表了两方面的进步——首先，通过将视频配准到最新的术中CBCT（克服与术前CT导航相关的局限性），其次，通过直接基于三维图像的视频-CBCT配准，这两者共同在最新图像中提供了对目标和正常组织更可靠的可视化，并提高了靶向精度。
