Neurosurgical robotic arm drilling navigation system

• Published in: The international journal of medical robotics + computer assisted surgery 2017-09, Vol.13 (3), p.n/a
• Main Authors: Lin, Chung‐Chih, Lin, Hsin‐Cheng, Lee, Wen‐Yo, Lee, Shih‐Tseng, Wu, Chieh‐Tsai
• Format: Article
• Language: English
• Subjects: 3d printing; Algorithms; Animals; Automatic control; Biomechanical Phenomena; Bone and Bones - surgery; bone drilling; Drilling; Equipment Design; haptic device; Humans; Imaging, Three-Dimensional - statistics & numerical data; Medical imaging; Models, Anatomic; Models, Animal; Navigation systems; Neurosurgical Procedures - instrumentation; Neurosurgical Procedures - statistics & numerical data; neurosurgical robot; Phantoms, Imaging; Robot arms; robotic arm; Robotic Surgical Procedures - instrumentation; Robotic Surgical Procedures - statistics & numerical data; Robotics; Skull - surgery; Surgery, Computer-Assisted - instrumentation; Surgery, Computer-Assisted - statistics & numerical data; Sus scrofa; Three dimensional imaging
• ISSN: 1478-5951; 1478-596X
• DOI: 10.1002/rcs.1790

Background The aim of this work was to develop a neurosurgical robotic arm drilling navigation system that provides assistance throughout the complete bone drilling process. Methods The system comprised neurosurgical robotic arm navigation combining robotic and surgical navigation, 3D medical imaging based surgical planning that could identify lesion location and plan the surgical path on 3D images, and automatic bone drilling control that would stop drilling when the bone was to be drilled‐through. Three kinds of experiment were designed. Results The average positioning error deduced from 3D images of the robotic arm was 0.502 ± 0.069 mm. The correlation between automatically and manually planned paths was 0.975. The average distance error between automatically planned paths and risky zones was 0.279 ± 0.401 mm. The drilling auto‐stopping algorithm had 0.00% unstopped cases (26.32% in control group 1) and 70.53% non‐drilled‐through cases (8.42% and 4.21% in control groups 1 and 2). Conclusions The system may be useful for neurosurgical robotic arm drilling navigation.