Purpose

Robot-assisted laparoscopic radical prostatectomy (RALRP) using the da Vinci surgical robot is a common treatment for organ-confined prostate cancer. Augmented reality (AR) can help during RALRP by showing the surgeon the location of anatomical structures and tumors from preoperative imaging. Previously, we proposed hand-eye and camera intrinsic matrix estimation procedures that can be carried out with conventional instruments within the patient during surgery, take < 3 min to perform, and fit seamlessly in the existing surgical workflow. In this paper, we describe and evaluate a complete AR guidance system for RALRP and quantify its accuracy.

Methods

Our AR system requires three transformations: the transrectal ultrasound (TRUS) to da Vinci transformation, the camera intrinsic matrix, and the hand-eye transformation. For evaluation, a 3D-printed cross-wire was visualized in TRUS and stereo endoscope in a water bath. Manually triangulated cross-wire points from stereo images were used as ground truth to evaluate overall TRE between these points and points transformed from TRUS to camera.

Results

After transforming the ground-truth points from the TRUS to the camera coordinate frame, the mean target registration error (TRE) (SD) was \(4.56\pm 1.57\) mm. The mean TREs (SD) in the x-, y-, and z-directions are \(1.93\pm 1.26\) mm, \(2.04\pm 1.37\) mm, and \(2.94\pm 1.84\) mm, respectively.

Conclusions

We describe and evaluate a complete AR guidance system for RALRP which can augment preoperative data to endoscope camera image, after a deformable magnetic resonance image to TRUS registration step. The streamlined procedures with current surgical workflow and low TRE demonstrate the compatibility and readiness of the system for clinical translation. A detailed sensitivity study remains part of future work.

中文翻译：

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机器人辅助腹腔镜前列腺癌根治术的无标记，术中，增强现实指导系统的评估。

目的

使用达芬奇外科手术机器人的机器人辅助的腹腔镜根治性前列腺切除术（RALRP）是器官受限的前列腺癌的常见治疗方法。增强现实（AR）可以通过向外科医生显示术前影像显示的解剖结构和肿瘤的位置来帮助RALRP。以前，我们提出了手眼和相机固有矩阵估计程序，这些程序可以在手术过程中使用患者体内的常规仪器进行，花费不到3分钟的时间完成，并无缝地适应现有的手术流程。在本文中，我们描述和评估了针对RALRP的完整的AR指导系统，并对其准确性进行了量化。

方法

我们的AR系统需要进行三种转换：经直肠超声（TRUS）转换为达芬奇转换，相机固有矩阵和手眼转换。为了进行评估，在水浴中的TRUS和立体声内窥镜中可视化了3D打印的交叉线。将来自立体图像的手动三角剖分交叉线点用作地面真相，以评估这些点与从TRUS转换为相机的点之间的总体TRE。

结果

将地面真点从TRUS转换为相机坐标系后，平均目标配准误差（TRE）（SD）为\（4.56 \ pm 1.57 \）  mm。在x-，y-和z方向上的平均TRE（SD）为\（1.93 \ pm 1.26 \） mm，\（2.04 \ pm 1.37 \） mm和\（2.94 \ pm 1.84 \） mm，分别。

结论

我们描述并评估了一个完整的RALRP AR引导系统，该系统可在将磁共振图像变形为TRUS配准步骤后将术前数据增加到内窥镜摄像机图像。当前手术流程和低TRE的简化程序证明了该系统的兼容性和为临床翻译的准备就绪。详细的敏感性研究仍是未来工作的一部分。