Evaluation of robotic system for mandibular reconstruction based on intelligent preoperative planning
10.3760/cma.j.cn114453-20201207-00613
- VernacularTitle:基于智能术前规划的下颌骨重建手术机器人系统实验验证
- Author:
Jiannan LIU
1
;
Junlei HU
;
Jing HAN
;
Jiangchang XU
;
Zijie ZHOU
;
Daowei LI
;
Xiaojun CHEN
;
Chenping ZHANG
Author Information
1. 上海交通大学医学院附属第九人民医院口腔医学院口腔-颌面头颈肿瘤科，上海市口腔医学重点实验室 200011
- Keywords:
Mandibular reconstruction;
Image processing, computer-assisted;
Robotic Surgical Procedures
- From:
Chinese Journal of Plastic Surgery
2021;37(2):130-136
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate the performance and the accuracy of surgical robot for mandibular reconstruction based on intelligent surgical planning.Methods:115 CT scanning images of normal mandible (57 males, 48 females, 40.3±9.1 years old, from February 2010 to May 2019) and 115 CT scanning images of mandible with tumor (62 males, 53 females, 55.6±7.2 years old, from March 2008 to August 2019) from Shanghai Ninth People’s Hospital were selected. The surgical robot system including work station, UR robot, optical navigation system, 6 dimensional force senor and surgical instrument. A 3D V-Net for mandible preoperational segmentation from CT scans was proposed and used to segment the mandible of a 54-year-old male patient who received mandible reconstruction with fibular flaps. The machine learning algorithm was used to aid surgical planning for maxillo-mandibular defect by detecting landmarks. The accuracy was defined as the distance between corresponding landmarks on the intact mandible. The robot could locate the target according to surgical planning and perform fibula osteotomy through force-motion control. The CT scanning of limb and head from the patient (male, 54 years old) was used for phantom experiments. 30 osteotomies on 5 3D-priented resin phantom were carried out. The pre- and post-operative images were compared to calculate the accuracy. The descriptive results were in the format of Mean±SD.Results:The average accuracy of V-Net for mandible segmentation was 96.581% and the time cost was less than 30 seconds. The average error of feature points on mandible was (2.24±1.74) mm. The residual length error was (1.02±0.45) mm and angle error was (0.96±0.42) degree in robotic-assisted osteotomy according to 3 cases of phantom experiments. The surgical robot could perform osteotomy safely and steadily within 15 min.Conclusions:Intelligent surgical planning can precisely segment the mandible and determine its landmarks. Robot for mandibular reconstruction can perform fibular osteotomy precisely with the pre-operative planning.
