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北京大学学报（医学版） ›› 2019, Vol. 51 ›› Issue (5): 973-976. doi: 10.19723/j.issn.1671-167X.2019.05.031

• 技术方法 • 上一篇    下一篇

机器人辅助三叉神经半月节的穿刺精度研究

朱建华,王晶,刘筱菁,郭传瑸()   

  1. 北京大学口腔医学院·口腔医院,口腔颌面外科 国家口腔疾病临床医学研究中心 口腔数字化医疗技术和材料国家工程实验室 口腔数字医学北京市重点实验室, 北京 100081
  • 收稿日期:2017-08-28 出版日期:2019-10-18 发布日期:2019-10-23
  • 通讯作者: 郭传瑸 E-mail:guodazuo@sina.com
  • 基金资助:
    国家高技术研究发展计划(863计划)(,2012AA041606和北京市科技计划Z141100002014003);北京市科技计划(Z141100002014003)

Accuracy analysis of robotic assistant needle placement for trigeminal gasserian ganglion

Jian-hua ZHU,Jing WANG,Xiao-jing LIU,Chuan-bin GUO()   

  1. Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China
  • Received:2017-08-28 Online:2019-10-18 Published:2019-10-23
  • Contact: Chuan-bin GUO E-mail:guodazuo@sina.com
  • Supported by:
    Supported by the National High Technology Research and Development Program of China (863 Program)(,2012AA041606和北京市科技计划Z141100002014003);the Beijing Science and Technology Project(Z141100002014003)

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摘要：

目的:验证自主研发的穿刺机器人辅助三叉神经半月节穿刺的精确性及可行性。方法:使用仿真头颅模型作为研究对象,橡皮泥模拟软组织,术前对模型进行锥形束CT(cone beam CT, CBCT)扫描,将影像数据导入计算机的术前设计系统,分割卵圆孔作为目标点,选取“皮肤进针点”后生成穿刺路径。将模型固定于模拟手术床的实验台,使用点配准的方式完成系统配准,发送穿刺路径数据至机器人控制器,经过医生确认穿刺路径后,在导航引导下机器人系统自动完成穿刺手术操作。穿刺完成后导航仪获取针尖即刻位置坐标,通过配准矩阵转换,计算针尖点与设计靶点的几何距离对穿刺精度进行术中验证,将穿刺针从执行器末端松解,对模型进行CBCT扫描再次获取术后图像数据,将术前、术后头颅进行图像融合,选取术后图像中针尖坐标数据,经过配准矩阵转换,计算针尖点与设计靶点的几何距离进行术后精度验证。采用IBM SPSS Statistics 20统计软件,以配对t检验方法对术中导航验证精度与术后图像融合验证精度进行统计学分析。结果:20例穿刺手术均一次成功穿过卵圆孔,术中导航验证平均穿刺误差为(0.56±0.07) mm,术后图像融合验证平均穿刺误差为(1.49±0.14) mm,差异有统计学意义(P<0.001)。结论:机器人辅助三叉神经半月节穿刺手术高效、可靠,导航精度是影响机器人辅助穿刺手术的重要因素。

关键词: 机器人, 手术, 计算机辅助, 三叉神经痛

Abstract:

Objective: To evaluate the accuracy and feasibility of a custom robot system guided by optical navigation for needle puncture on trigeminal gasserian ganglion. Methods: A synthetic human skull model was used, with plasticine placed around the skull base to imitate the human soft tissue. Cone beam CT (CBCT) scanning was performed before the operation. With image data transferred to the graphical user interface of the computer workstation, the oval foramen was selected as the target and the “skin entry point” was also determined by the surgeon on the surgical planning software. Thus the needle trajectory was eventually planned. The skull model was fixed firmly to the trial table with a head clamp and relative size of the trial table was the same as a standard operating table. Following point-based registration, the data were sent to the robot control unit. Only after the surgeon’s confirmation, the needle was automatically inserted into the intended target by the robot guided by optical navigation. When the procedure was completed, the instantaneous data of the needle tip orientation acquired by navigation system was sent back to the computer workstation for accuracy verification by calculating the geometric distance between the needle tip and the planning target after matrix transformation. Subsequently, after the needle had been released, CBCT scanning was also acquired to make image fusion of the preoperative skull and the postoperative skull. The data of the needle tip orientation was acquired on the postoperative image and the accuracy was re-verified by calculating the geometric distance between the needle tip and the planning target after matrix transformation. IBM SPSS Statistics 20 was used for statistical analysis and the paired t-test was used to compare the differences in the accuracy measured by the intraoperative navigation and postoperative image fusion. Results:All 20 interventions were successfully located in oval foramen at the first needle insertion. The mean deviation of the needle tip was (0.56±0.07) mm (measured by the navigation system) and (1.49±0.14) mm (measured by the image fusion), respectively (P<0.001). Conclusion: The experimental results show the robot system is efficient and reliable. The navigation accuracy is one of the most significant factors in robotic procedures.

Key words: Robotics, Surgery, computer-assisted, Trigeminal neuralgia

中图分类号: 

  • R745.11

图1

机器人系统 (A为光学导航仪,B为计算机工作站,C为机器人装置)"

图2

闭合回路控制"

图3

术前(银色)、术后(棕绿色)头颅图像融合 (紫色线型为设计路径,棕绿色线性物体为穿刺针)"

图4

针尖偏移误差"

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