Skip to main content
SpringerLink
Log in

30 Years of Neurosurgical Robots: Review and Trends for Manipulators and Associated Navigational Systems

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

This review provides an examination of contemporary neurosurgical robots and the developments that led to them. Improvements in localization, microsurgery and minimally invasive surgery have made robotic neurosurgery viable, as seen by the success of platforms such as the CyberKnife and neuromate. Neurosurgical robots can now perform specific surgical tasks such as skull-base drilling and craniotomies, as well as pedicle screw and cochlear electrode insertions. Growth trends in neurosurgical robotics are likely to continue but may be tempered by concerns over recent surgical robot recalls, commercially-driven surgeon training, and studies that show operational costs for surgical robotic procedures are often higher than traditional surgical methods. We point out that addressing performance issues related to navigation-related registration is an active area of research and will aid in improving overall robot neurosurgery performance and associated costs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7

Similar content being viewed by others

References

  1. Arata, J., H. Kenmotsu, M. Takagi, T. Hori, T. Miyagi, H. Fujimoto, Y. Kajita, Y. Hayashi, K. Chinzei, and M. Hashizume. Surgical bedside master console for neurosurgical robotic system. Int. J. Comput. Assist. Radiol. Surg. 8:75–86, 2013.

    Article  PubMed  Google Scholar 

  2. Barbash, G. I., and S. A. Glied. New technology and health care costs—the case of robot-assisted surgery. N. Engl. J. Med. 363:701–704, 2010.

    Article  CAS  PubMed  Google Scholar 

  3. Beasley, R. A. Medical robots: current systems and research directions. J. Robotics. 2012:401613, 2012.

  4. Begg, N. D. M. Increasing the safety and precision of medical tissue puncture. Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, USA, 2014.

  5. Bekelis, K., T. A. Radwan, A. Desai, and D. W. Roberts. Frameless robotically targeted stereotactic brain biopsy: feasibility, diagnostic yield, and safety. J. Neurosurg. 116:1002–1006, 2012.

    Article  PubMed  Google Scholar 

  6. Bergeles, C., and G. Yang. From passive tool holders to microsurgeons: safer, smaller, smarter surgical robots. IEEE Trans. Biomed. Eng. 61:1565–1576, 2014.

    Article  PubMed  Google Scholar 

  7. Bergman, W. C., R. A. Schulz, and D. S. Davis. Factors influencing the genesis of neurosurgical technology. Neurosurg. Focus. 27:1–6, 2009.

    Google Scholar 

  8. Bertelsen, A., J. Melo, E. Sánchez, and D. Borro. A review of surgical robots for spinal interventions. Int. J. Med. Robot. Comput. 9:407–422, 2013.

    Article  Google Scholar 

  9. Bing, C., M. Ladouceur-Wodzak, C. R. Wanner, J. M. Shelton, J. A. Richardson, and R. Chopra. Trans-cranial opening of the blood–brain barrier in targeted regions using a stereotaxic brain atlas and focused ultrasound energy. J. Ther. Ultrasound 2:13, 2014.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Bischoff, R., J. Kurth, G Schreiber, R. Koeppe, A. Albu-Schaeffer, A. Beyer, O. Eiberger, S. Haddadin, A. Stemmer, G. Grunwald, et al. The KUKA- DLR lightweight robot arm-a new reference platform for robotics research and manufacturing. In: Proceedings of the 41st International Symposium on Robotics and the 6th German Conference on Robotics (Joint conference), pp 1–8, 2010.

  11. Cosgrove, G. R., Buchbinder, B. R., Jiang, H. Functional Magnetic Resonance Imaging for Intracranial Navigation. Online, 2005. URL: http://neurosurgery.mgh.harvard.edu/functional/fmrimage.htm (Last visited June 2, 2015).

  12. Caird, J. D., and K. A. Choudhari. ‘Plunging’ during burr hole craniostomy: a persistent problem amongst neurosurgeons in Britain and Ireland. Br. J. Neurosurg. 17:509–512, 2003.

    Article  CAS  PubMed  Google Scholar 

  13. Dario, P. Surgical robotics: achievements and challenges (plenary talk), 2012. In: Intelligent Robots and Systems Conference 2012 Plenary Talk (Portugal).

  14. Day, B. Fw: Historical perspective on medical/surgical robotics involving people at VGH/UBC. Email Correspondence, 2015.

  15. De Momi, E., D. De Lorenzo, A. Vaccarella, M. D. Comparetti, F. Vicentini, N. Pedrocchi, M. Malosio, L. M. Tosatti, L. Frasson, F. Rodriguez y Baena, and G. Ferrigno. ROBOCAST and ACTIVE: Advanced robotic systems for neurosurgery. In: BioMed@POLIMI Proceedings of the 1st Workshop on the Life Sciences at Politecnico di Milano, 2010, pp. 252–255.

  16. Despinoy, F., A. Sánchez, N. Zemiti, P. Jannin, and P. Poignet. Comparative assessment of a novel optical human–machine interface for laparoscopic telesurgery. In: Information Processing in Computer-Assisted Interventions, Springer, 2014, pp. 21–30.

  17. Donovan, D. J., R. R. Moquin, and J. M. Ecklund. Cranial burr holes and emergency craniotomy: review of indications and technique. Mil. Med. 171:12–19, 2006.

    Article  PubMed  Google Scholar 

  18. Edwards, M. Robots in industry: an overview. Appl. Ergon. 15:45–53, 1984.

    Article  CAS  PubMed  Google Scholar 

  19. Engel, D., J. Raczkowsky, and H. Worn. A safe robot system for craniofacial surgery. IEEE Int. Conf. Robot. Autom. 2:2020–2024, 2001.

    Google Scholar 

  20. Fontana, J., A. Korff, A. Follmann, K. Radermacher, and K. Schmieder. Smart trepanation system: preclinical analysis of safety, efficiency, and user satisfaction. Neurosurg: J. Neurol. Surg. A. Cent. Eur., 2014.

    Google Scholar 

  21. FutureMag—Arte. Des robots chirurgiens—Futuremag—arte. Online (YouTube), 2014. URL: http://youtu.be/LNUC6tLtUFc (Last visited Feb 6, 2015).

  22. Gerber, N., K. A. Gavaghan, B. J. Bell, T. M. Williamson, C. Weisstanner, M.-D. Caversaccio, and S. Weber. High-accuracy patient-to-image registration for the facilitation of image-guided robotic microsurgery on the head. IEEE Trans. Biomed. Eng. 60:960–968, 2013.

    Article  PubMed  Google Scholar 

  23. Germano, I. M. Advanced Techniques in Image-Guided Brain and Spine Surgery. New York: Thieme Medical Publishers, 2011.

    Google Scholar 

  24. Gong, Y., Hu, D., Hannaford, B., and Seibel, E. J. Toward real-time endoscopically-guided robotic navigation based on a 3D virtual surgical field model. In: Proc SPIE Int Soc Opt Eng, p. 9415, 2015.

  25. Grau, C., R. Ginhoux, A. Riera, T. L. Nguyen, H. Chauvat, M. Berg, J. L. Amengual, A. Pascual-Leone, and G. Ruffini. Conscious brain-to-brain communication in humans using non-invasive technologies. PLoS One 9:e105225, 2014.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Guizzo, E. Rescue-robot show-down. IEEE Spectr. 51:52–55, 2014.

    Article  Google Scholar 

  27. Hagn, U. The Aspect of Versatility in the Design of a Lightweight Robot for Surgical Applications. Ph.D. thesis, University of Hannover, Germany, Hannover, Germany, 2011.

  28. Hagn, U., M. Nickl, S. Jörg, G. Passig, T. Bahls, A. Nothhelfer, F. Hacker, L. Le-Tien, A. Albu-Schäffer, R. Konietschke, et al. The DLR MIRO: a versatile lightweight robot for surgical applications. Ind. Robot. 35:324–336, 2008.

    Article  Google Scholar 

  29. Haidegger, T. Improving the Accuracy and Safety of a Robotic System for Neurosurgery. Master’s thesis, Budapest University of Technology and Economics and Johns Hopkins University, Baltimore, USA, 2008.

  30. Haidegger, T., P. Kazanzides, B. Benyó, L. Kovács, and Z. Benyó. Surgical case identification for an image-guided interventional system. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2010, pp. 1831–1836.

  31. Haidegger, T., T. Xia, and P. Kazanzides. Accuracy improvement of a neurosurgical robot system. In: IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, 2008, pp. 836–841.

  32. Hannaford, B., D. Friedman, H. King, M. Lum, J. Rosen, and G. Sankaranarayanan. Evaluation of RAVEN surgical telerobot during the NASA Extreme Environment Mission Operations (NEEMO) 12 mission. Technical Report UWWEETR-2009-0002, University of Washington, Seattle, WA, USA, 2009.

  33. Hannaford, B., J. Rosen, D. Friedman, H. King, P. Roan, L. Cheng, D. Glozman, J. Ma, S. N. Kosari, and L. White. Raven-II: an open platform for surgical robotics research. IEEE Trans. Biomed. Eng. 60:954–959, 2013.

    Article  PubMed  Google Scholar 

  34. Heifetz, M. D. Nuances of Neurosurgical Technique (2nd ed.). Park Ridge: Thieme, p. 108, 1997.

    Google Scholar 

  35. Heinig, M. Design and Evaluation of the Motor Assisted Robotic Stereotaxy System MARS. PhD, University of Luebeck (Universitaet zu Luebeck), Luebeck, Germany, 2012.

  36. Hillman, M. Rehabilitation robotics from past to present—a historical perspective. In: Proceedings of the ICORR 2003 (The 8th International Conference on Rehabilitation Robotics), Daejeon, South Korea: Springer, 2003, pp. 25–44.

  37. Hoeckelmann, M., I. J. Rudas, P. Fiorini, F. Kirchner, and T. Haidegger. Current capabilities and development potential in surgical robotics. Int. J. Adv. Robot. Syst. 12:61, 2015.

    Google Scholar 

  38. Honeybul, S., and K. M. Ho. Long-term complications of decompressive craniectomy for head injury. J. Neurotraum. 28:929–935, 2011.

    Article  Google Scholar 

  39. Ito, M., T. Sonokawa, H. Mishina, and K. Sato. Penetrating injury of the brain by the burr of a high-speed air drill during craniotomy: case report. J. Clin. Neurosci. 8(3):261–263, 2001.

    Article  CAS  PubMed  Google Scholar 

  40. Iwata, H., K. Sato, K. Tatewaki, N. Yokota, M. Inoue, Y. Baba, and Y. Shibamoto. Hypofractionated stereotactic radiotherapy with CyberKnife for nonfunctioning pituitary adenoma: high local control with low toxicity. Neuro. Oncol. 13:916–922, 2011.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Kim, K. C. (ed.). Robotics in General Surgery. New York: Springer, p. 497, 2014.

    Google Scholar 

  42. Kwoh, Y. S., L. S. Reed, J. Y. Chen, H. Shao, T. K. Truong, and E. A. Jonckheere. A new computerized tomographic aided robotic stereotactic system. Robot. Age 7:17–21, 1985.

    Google Scholar 

  43. Lechky, O. World’s first surgical robot in B.C. The Medical Post 21, 1985.

  44. Li, Q. H., L. Zamorano, A. Pandya, R. Perez, J. Gong, and F. Diaz. The Application Accuracy of the neuromate robot—a quantitative comparison with frameless and frame-based surgical localization systems robot. Comput. Aided Surg. 7:90–98, 2002.

    Article  PubMed  Google Scholar 

  45. Lowes, R. FDA investigates robotic surgery system after adverse event spike. Medscape Medical News 30, 2013.

  46. Macario, A. What does 1 min of operating room time cost? J. Clin. Anesth. 22:233–236, 2010.

    Article  PubMed  Google Scholar 

  47. Meho, L.I., and Kiduk, Y. A new era in citation and bibliometric analyses: web of science, scopus, and google scholar. arXiv preprint cs/0612132, 2006.

  48. Meli, L., C. Pacchierotti, and D. Prattichizzo. Sensory subtraction in robot-assisted surgery: fingertip skin deformation feedback to ensure safety and improve transparency in bimanual haptic interaction. IEEE Trans. Biomed. Eng. 61:1318–1327, 2014.

    Article  PubMed  Google Scholar 

  49. Mitsuishi, M., A. Morita, N. Sugita, S. Sora, R. Mochizuki, K. Tanimoto, Y. M. Baek, H. Takahashi, and K. Harada. Master–slave robotic platform and its feasibility study for micro-neurosurgery. Int. J. Med. Robot. Comp. 9:180–189, 2013.

    Article  Google Scholar 

  50. Momi, E. D. Force feedback in neurosurgery. Summer school presentation, Nearlab, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy, 2014.

  51. O’Reilly, B. A. Patents running out: time to take stock of robotic surgery. Int. Urogynecol. J. 25:711–713, 2014.

    Article  PubMed  Google Scholar 

  52. Paleologos, T. S., J. P. Wadley, N. D. Kitchen, and D. G. Thomas. Clinical utility and cost-effectiveness of interactive image-guided craniotomy: Clinical comparison between conventional and image-guided meningioma surgery. Neurosurgery 47:40–48, 2000.

    CAS  PubMed  Google Scholar 

  53. Risholm, P., A. J. Golby, and W. Wells. Multimodal image registration for preoperative planning and image-guided neurosurgical procedures. Neuro. Clinics N. Am. 22:197–206, 2011.

    Article  Google Scholar 

  54. Roulette, G. D., and M. J. Curet. Future directions and alternate systems for robotic surgery. In: Essentials of Robotic Surgery, edited by M. Kroh, and S. Chalikonda. Switzerland: Springer, 2015, pp. 201–214.

    Google Scholar 

  55. Sakaguchi, T. Percutaneous puncture with a robot. Acta Urol. Jpn. 31:1265–1268, 1985.

    CAS  Google Scholar 

  56. Sautot, P., P. Cinquin, S. Lavallee, and J. Troccaz. Computer assisted spine surgery: a first step toward clinical, application in orthopaedics. In: 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol. 3, 1992, pp. 1071–1072.

  57. Schulz, C., S. Waldeck, and U. M. Mauer. Intraoperative image guidance in neurosurgery: development, current indications, and future trends. Radiol. Res. Pract. 2012.

  58. Seering, W. P. Who said robots should work like people? Robot. Comput. Int. Manuf. 1:349–354, 1984.

    Article  Google Scholar 

  59. Sloan, A. E., M. S. Ahluwalia, J. Valerio-Pascua, S. Manjila, M. G. Torchia, S. E. Jones, J. L. Sunshine, M. Phillips, M. A. Griswold, M. Clampitt, C. Brewer, J. Jochum, M. V. McGraw, D. Diorio, G. Ditz, and G. H. Barnett. Results of the NeuroBlate system first-in-humans phase 1 clinical trial for recurrent glioblastoma: clinical article. J. Neurosurg. 118:1202–1219, 2013.

    Article  PubMed  Google Scholar 

  60. Sutherland, G. R., S. Wolfsberger, S. Lama, and K. Zareinia. The evolution of NeuroArm. Neurosurgery 72:A27–A32, 2013.

    Article  Google Scholar 

  61. Takasuna, H., T. Goto, Y. Kakizawa, T. Miyahara, J. Koyama, Y. Tanaka, T. Kawai, and K. Hongo. Use of a micromanipulator system (Neurobot) in endoscopic neurosurgery. J. Clin. Neurosci. 19:1553–1557, 2012.

    Article  CAS  PubMed  Google Scholar 

  62. Tian, Z., W. Lu, T. Wang, B. Ma, Q. Zhao, and G. Zhang. Application of a robotic telemanipulation system in stereotactic surgery. Stereo. Funct. Neuros. 86:54–61, 2007.

    Article  Google Scholar 

  63. Tillander, H. Magnetic guidance of a catheter with articulated steel tip. Acta. Radiol. 35:62–64, 1951.

    Article  CAS  PubMed  Google Scholar 

  64. Vogel, T. W., B. J. Dlouhy, and M. A. Howard. Don’t take the plunge: avoiding adverse events with cranial perforators. J. Neurosurg. 115:570–575, 2011.

    Article  PubMed  Google Scholar 

  65. Voigt, J. D., and M. Torchia. Laser interstitial thermal therapy with and without MRI guidance for treatment of brain neoplasms—a systematic review of the literature. Photon. Laser. Med. 3:77–93, 2014.

    Article  Google Scholar 

  66. Winston, G. P., P. Daga, J. Stretton, M. Modat, M. R. Symms, A. W. McEvoy, S. Ourselin, and J. S. Duncan. Optic radiation tractography and vision in anterior temporal lobe resection. Ann. Neurol. 71:334–341, 2012.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Wirtz, C. R., F. K. Albert, M. Schwaderer, C. Heuer, A. Staubert, V. M. Tronnier, M. Knauth, and S. Kunze. The benefit of neuronavigation for neurosurgery analyzed by its impact on glioblastoma surgery. Neurol. Res. 22:354–360, 2000.

    CAS  PubMed  Google Scholar 

  68. Wu, Z., Q. Zhao, Z. Tian, J. Zhan, X. Xiao, H. Lin, H. Wang, and F. Wang. Efficacy and safety of a new robot-assisted stereotactic system for radiofrequency thermocoagulation in patients with temporal lobe epilepsy. Exp. Ther. Med. 7:1728–1732, 2014.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Dr. Kei Masani and Ms. Michelle Luk for their translation skills and Ryerson University’s Library staff for their help in document retrieval. Many thanks to the University of Washington, the Winnipeg Free Press, Geof Auchinleck, as well as DLR and Tilo Wüsthoff for permission to use their photos and images. We would also like to thank Mr. Auchinleck and Dr. Brian Day for providing details, photos and video of the Arthrobot. We acknowledge financial support by Canada’s Natural Sciences and Engineering Council (NSERC). Finally, we would like to thank our three anonymous reviewers and the ABME editorial staff for their constructive and supportive feedback.

Author information

Authors and Affiliations

  1. Department of Electrical & Computer Engineering, Ryerson University, Toronto, Canada

    Jamil Jivraj, Ronnie Wong & Victor Yang

  2. Sunnybrook Health Sciences Centre, Brain Sciences Program/Imaging Research, Sunnybrook Research Institute, Toronto, Canada

    Jamil Jivraj, Ronnie Wong & Victor Yang

  3. Department of Electrical Engineering & Computer Science, York University, Toronto, Canada

    James Andrew Smith

Authors
  1. James Andrew Smith
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jamil Jivraj
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ronnie Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Victor Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to James Andrew Smith.

Additional information

Associate Editor Xiaoxiang Zheng oversaw the review of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Smith, J.A., Jivraj, J., Wong, R. et al. 30 Years of Neurosurgical Robots: Review and Trends for Manipulators and Associated Navigational Systems. Ann Biomed Eng 44, 836–846 (2016). https://doi.org/10.1007/s10439-015-1475-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-015-1475-4

Keywords

Search

Navigation