Lapeer R, Chen M S, Gonzalez G, Linney A, Alusi G
School of Computing Sciences, University of East Anglia, Norwich, UK.
Int J Med Robot. 2008 Mar;4(1):32-45. doi: 10.1002/rcs.175.
Endoscopic sinus surgery (ESS) is generally applied to treat sinusitis when medication is not effective in eliminating the symptoms. Images captured by the endoscope are viewed on a monitor placed near the surgeon. Due to the separation of the handling of the endoscope from the viewing of the image, ESS requires surgeons to have well-trained hand-eye coordination. Unlike the use of the stereo surgical microscope in ENT, the endoscope does not provide the stereo cue for depth perception, hence a surgeon can only perceive depth through motion and shading, which may affect the accuracy of tool placement. Whilst the skill and experience of the surgeon are important factors to the success of ESS, the assistance of image-enhanced surgical navigation (IESN) can further reassure the surgeon's judgement and enhance surgical performance.
We developed and validated an IESN system (ARView) for a rigid zero-degree endoscope, typically used for ESS. We present the interface, and calibration and registration (pre-operative and intra-operative) methods of the system. We then quantitatively assess the performance of each of the steps needed to generate the overlay of a real endoscope image with its 'virtual' counterpart, obtained from computed tomography (CT) image data of a real skull. These steps include calibration, registration, motion tracking and final overlay.
Calibration results using a planar calibration object displayed optimized object space errors of 0.025 +/- 0.013 mm, whilst a non-planar calibration object displayed errors of 0.12 +/- 0.08 mm. Target registration errors (TREs) near the region of interest (ROI), using our pre-operative registration method with the calibration object located near the mouth of the patient (skull), were 2.3 +/- 0.4 mm. The proposed photo-consistency method for intra-operative registration has not yet yielded satisfactory results for ESS-based IESN. (RMS) values for tracking accuracy were found to be around 1.2 mm in a typical workspace of 400 x 400 mm. Object space overlay errors in a small measurement volume of 10 x 10 x 10 mm were found to be around 0.4 +/- 0.02 mm.
We conclude that, in agreement with individual experiments, the current overall overlay accuracy is of the order of 2-3 mm in the x-y plane, which is in line with current conventional SN systems. The method which is most in need of improvement is registration, hence we wish to investigate the application of the proposed photo-consistency method further.
当药物治疗无法有效消除鼻窦炎症状时,通常会采用内窥镜鼻窦手术(ESS)。通过内窥镜拍摄的图像会在靠近外科医生的监视器上显示。由于内窥镜的操作与图像的查看相分离,ESS要求外科医生具备训练有素的手眼协调能力。与耳鼻喉科中使用的立体手术显微镜不同,内窥镜无法提供用于深度感知的立体线索,因此外科医生只能通过运动和阴影来感知深度,这可能会影响工具放置的准确性。虽然外科医生的技能和经验是ESS成功的重要因素,但图像增强手术导航(IESN)的辅助可以进一步确保外科医生的判断并提高手术性能。
我们开发并验证了一种用于刚性零度内窥镜的IESN系统(ARView),该内窥镜通常用于ESS。我们展示了该系统的界面、校准和配准(术前和术中)方法。然后,我们定量评估了将真实内窥镜图像与其从真实颅骨的计算机断层扫描(CT)图像数据中获得的“虚拟”对应图像进行叠加所需的每个步骤的性能。这些步骤包括校准、配准、运动跟踪和最终叠加。
使用平面校准物体的校准结果显示优化后的物体空间误差为0.025±0.013毫米,而使用非平面校准物体时误差为0.12±0.08毫米。在感兴趣区域(ROI)附近,使用我们的术前配准方法,将校准物体放置在患者口腔(颅骨)附近时,目标配准误差(TRE)为2.3±0.4毫米。所提出的用于术中配准的光一致性方法在基于ESS的IESN中尚未产生令人满意的结果。在400×400毫米的典型工作空间中,跟踪精度的均方根(RMS)值约为1.2毫米。在10×10×10毫米的小测量体积中,物体空间叠加误差约为0.4±0.02毫米。
我们得出结论,与个别实验一致,当前在x - y平面上的整体叠加精度约为2 - 3毫米,这与当前传统的手术导航系统一致。最需要改进的方法是配准,因此我们希望进一步研究所提出的光一致性方法的应用。