Fully Automatic Robot-Assisted Surgery for Mandibular Angle Split Osteotomy
Sun, Chai, Chai, Zheng (2020) Fully Automatic Robot-Assisted Surgery for Mandibular Angle Split Osteotomy J Craniofac Surg (IF: 0.9) 31(2) 336-339Abstract
With the development of computer-assisted surgery, preoperational design is detailed in software. However, it is still a challenge for surgeons to realize the surgical plan in the craniofacial surgery. Robot-assisted surgery has advantages of high accuracy and stability. It is suitable for the high-stress procedures like drilling, milling, and cutting. This study aims to verify the feasibility for automatic drilling without soft tissues in model test based on an industrial robot platform.This study chose the data from digital laboratory in Shanghai 9th People's Hospital. The mandibular was reconstructed in software and surgical plan was also designed. Then, the coordinate data was input to the robot's software and matrix conversion was calculated by 4 marked points. The trajectory generation was calculated by inverse kinematics for target coordinates and robot coordinates. The model was fixed and calibrated for automatic drilling. At last, the accuracy was calculated by optic scanning instrument.The installment and preparation cost 10 minutes, the drilling procedure cost 12 minutes. The outside position error was (1.71 ± 0.16) mm, the inside position error was (1.37 ± 0.28) mm, the orientation error was (3.04 ± 1.02)°. Additionally, a total of 5 beagles were tested, with an accuracy error of (2.78 ± 1.52) mm. No postoperative complications occurred.This is the first study reported for robot-assisted automatic surgery in craniofacial surgery. The result shows it is possible to realize the automatic drilling procedure under the condition of no interference like soft tissues. With the development of artificial intelligence and machine vision, robot-assisted surgery may help surgeons to fulfill more automatic procedures for craniofacial surgery.
Links
http://www.ncbi.nlm.nih.gov/pubmed/31232983http://dx.doi.org/10.1097/SCS.0000000000005587
