Heqiang Tian* | Longxin Ma | Xiaoqing Dang | Jinfeng Zhang | Junlin Ma
OPEN ACCESS
Surgical navigation has emerged as a potential solution to improve accuracy and security of intraoperative surgery. This paper introduces surgical navigation technologies into cervical vertebra bone grinding in spine surgery to guide a bone-grinding robot. Firstly, an active robot-assisted surgical navigation system based on optical positioning for cervical vertebra bone grinding is created, and the space registration coordinate system among “image-patient-robot” is also established. Secondly, space registration among “image-patient-robot” is studied. Here, intraoperative registration between image and patient is achieved by ICP improved algorithm based on coordinate system direction fitting, and space transformation between patient and robot is established by using an optical locator based on planimetric method. At last, the navigating and positioning precision of robot-assisted spine surgery is analyzed by performing positioning and tracking experiments and the influencing factors for surgical navigation errors are also analyzed. The experiment results show that the active surgical navigation system can achieve positioning and tracking of bone-grinding robot feasibly and rationally.
Bone-grinding robot, surgical navigation, registration, tracking
The authors would like to express appreciation to financial supports from China Postdoctoral Science Foundation Funded Project (2016M602164), Qingdao Postdoctoral Researchers Applied Research Project (2016119), Outstanding Young Scientist in Shandong Province (2014SBS1415), Scientific Research Foundation of the SUST University (2014RCJJ023).
1. Tsai TC, Hsu YL, Development of a parallel surgical robot with automatic bone drilling carriage for stereotactic neurosurgery, 2007, Biomed Eng Appl Basis Commun, vol.19, pp.269-77.
2. Kuang SL, Leung KS, Wang TM, Chui LH, Liu WY, Wang Y, A novel passive/active hybrid robot for orthopaedic trauma surgery,2012, Int J Med Robotics Comput Assist Surg, vol.8,pp.458-67.
3. Qiao F, Li D, Jin Z, et al, Application of 3D printed customized external fixator in fracture reduction, 2015, Injury-international Journal of the Care of the Injured, vol.46, no.6, pp.1150-1155.
4. Paula Gomes, Surgical robotics: Reviewing the past, analyzing the present, imagining the future, 2011, Robotics and Computer-Integrated Manufacturing, vol.27, no.2, pp.261-266.
5. Bargar WL, Robots in orthopaedic surgery: past, present, and future, 2007, Clinical Orthopaedics and Related Research, vol.463, no.463, pp.31-36.
6.Taylor RH, Mittelstadt BD , Paul HA, Hanson W, Kazanzides P, Zuhars JF , Williamson B, Musits BL, Glassman E, Bargar WL, An Image- Directed Robotic System for Precise Orthopaedic Surgery,1994, IEEE Trans. Robot and Automation,vol.10,pp. 261-275.
7. Cobb J, Henckel J, Gomes P, et al, Hands-on robotic unicompartmental knee replacement: A prospective, randomised controlled study of the acrobot system, 2006, J Bone Joint Surg Br, vol.88, pp.188-197.
8. Hagag B, Abovitz R, Kang H, et al, RIO: Robotic-arm interactive orthopedic system MAKOplasty: User interactive haptic orthopedic robotics, 2011, Surgical Robotics. New York: Springer, pp.219-246.
9.Pechlivanis I, Kiriyanthan G, Engelhardt M, Scholz M, Lücke S, Harders A, Schmieder K, Percutaneous placement of pedicle screws in the lumbar spine using a bone mounted miniature robotic system: first experiences and accuracy of screw placement, 2009, Spine, vol.34, no.4, pp.392-398.
10. Larsson N, Molin L, Rapid Prototyping of User Interfaces in Robot Surgery — Wizard of Oz in Participatory Design, 2006, Advances in Information Systems Development, Springer US, pp.361-371.
11.Chung GB, Kim S, Lee SG, Yi B, Kim W, Oh SM, Kim YS, So BR, Park JI, Oh SH, An Image-Guided Robotic Surgery System for Spinal Fusion, 2006, International Journal of Control Automation and Systems, vol.4, no.1,pp.30-41.
12. Hu L, Luan S, Wang M Y, et al, A biplanar robot navigation system for the distal locking of intramedullary nails, 2010, Int J Med Robot Comp, vol.6,pp.61-65.
13.Sun Lining, Zhang Jian, Du Zhijiang, A Robot-assisted System of Bone Surgery Based on Image Navigation,2006, College Journal of Harbin Engineering University, vol.27, no.2, pp. 285-289.
14.Besl P J, McKay ND, A method for registration of 3D shapes,1992, IEEE Transactions on pattern analysis and machine intelligence, vol.14, pp.239-256.
15.Heqiang Tian, Peng Yang, Chunjian Su and Zhiqiang Dong, ICP Registration Technology based on the Coordinate System Direction Fit, 2015, International Journal of Security and Its Applications vol.9, no.12 , pp.47-56.
16.Song G L, Han J D, Zhao Y W, Review of orthopedic surgical robot and navigation technology (in Chinese), 2013, Chin Sci Bull (Chin Ver), vol. 58(Supp.II), pp.8-19.
17.Valenti M, Ferrigno G, Martina D, et al, Gaussian mixture models based 2D-3D registration of bone shapes for orthopedic surgery planning, 2016, Medical & Biological Engineering, pp.11-14.
18.Ketcha M D, De S T, Uneri A, et al, Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery, 2016,Proceedings of SPIE--the International Society for Optical Engineering, pp.9786:97860A.
19.Banga V K, Singh Y, Kumar R, Uncertainty compensation and optimization of three and four degree-of-freedom robotics system using Genetic Algorithm, 2008, Modelling, Measurement and Control B,vol.77,no.1-2,pp.70-82.
20. Wang W, Zhang L, Ma J, Kinematic calibration of 6-UPS surgical parallel robot, 2013, ICME International Conference on Complex Medical Engineering, pp.369-374.
21. Ahola J M, SeppälÄ T, Koskinen J, et al, Calibration of the pose parameters between coupled 6-axis F/T sensors in robotics applications, 2017, Robotics & Autonomous Systems, pp.1-8.