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Current state-of-the-art and future perspectives of robotic technology in neurosurgery

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Abstract

Neurosurgery is one of the most demanding surgical specialties in terms of precision requirements and surgical field limitations. Recent advancements in robotic technology have generated the possibility of incorporating advanced technological tools to the neurosurgical operating room. Although previous studies have addressed the specific details of new robotic systems, there is very little literature on the strengths and drawbacks of past attempts, currently available platforms and prototypes in development. In this review, the authors present a critical historical analysis of the development of robotic technology in neurosurgery as well as a comprehensive summary of the currently available systems that can be expected to be incorporated to the neurosurgical armamentarium in the near future. Finally, the authors present a critical analysis of the main technical challenges in robotic technology development at the present time (such as the design of improved systems for haptic feedback and the necessity of incorporating intraoperative imaging data) as well as the benefits which robotic technology is expected to bring to specific neurosurgical subspecialties in the near future.

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References

  1. Adler JR Jr (2013) The future of robotics in radiosurgery. Neurosurgery 72(Suppl 1):8–11

    Article  PubMed  Google Scholar 

  2. Alric M, Chapelle F, Lemaire JJ, Gogu G (2009) Potential applications of medical and non-medical robots for neurosurgical applications. Minim Invasive Ther Allied Technol 18:193–216

    Article  PubMed  Google Scholar 

  3. Ambrose J (1973) Computerized transverse axial scanning (tomography). 2. Clinical application. Br J Radiol 46:1023–1047

    Article  CAS  PubMed  Google Scholar 

  4. Ayres RU (1990) Technological transformations and long waves.1. Technol Forecast Soc Chang 37:1–37

    Article  Google Scholar 

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

    Article  PubMed  Google Scholar 

  6. Benabid AL, Cinquin P, Lavalle S, Le Bas JF, Demongest J, de Rougemont J (1987) Computer-driven robot for stereotactic surgery connected to CT scan and magnetic resonance imaging; technological design and preliminary results. Appl Neurophysiol 50:153–154

    CAS  PubMed  Google Scholar 

  7. Brodie J, Eljamel S (2011) Evaluation of a neurosurgical robotic system to make accurate burr holes. Int J Med Robot Comput Assist Surg 7:101–106

    Article  Google Scholar 

  8. Buchanan BG (2005) A (very) brief history of artificial intelligence. AI Mag 26:53–60

    Google Scholar 

  9. Capek K (1923) R.U.R. (Rossum’s Universal Robots). Page & Co Garden City, Doubleday

    Google Scholar 

  10. Dandy WE (1918) Ventriculography following the injection of air into the cerebral ventricles. Ann Surg 68:5–11

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  11. Dandy WE (1919) Rontgenography of the brain after the injection of air into the spinal canal. Ann Surg 70:397–403

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  12. Deacon G, Harwood A, Holdback J, Maiwand D, Pearce M, Reid I, Street M, Taylor J (2010) The Pathfinder image-guided surgical robot. Proc Inst Mech Eng Part H-J Eng Med 224:691–713

    Article  CAS  Google Scholar 

  13. Devito DP, Kaplan L, Dietl R, Pfeiffer M, Horne D, Silberstein B, Hardenbrook M, Kiriyanthan G, Barzilay Y, Bruskin A, Sackerer D, Alexandrovsky V, Stuer C, Burger R, Maeurer J, Donald GD, Schoenmayr R, Friedlander A, Knoller N, Schmieder K, Pechlivanis I, Kim IS, Meyer B, Shoham M (2010) Clinical acceptance and accuracy assessment of spinal implants guided with SpineAssist surgical robot: retrospective study. Spine (Phila Pa 1976) 35:2109–2115

    Article  Google Scholar 

  14. Di Ieva A (2010) Microtechnologies in neurosurgery. Proc Inst Mech Eng H 224:797–800

    Article  PubMed  Google Scholar 

  15. Dogangil G, Davies BL, Rodriguez y Baena F (2010) A review of medical robotics for minimally invasive soft tissue surgery. Proc Inst Mech Eng H 224:653–679

    Article  CAS  PubMed  Google Scholar 

  16. Eljamel MS (2009) Robotic neurological surgery applications: accuracy and consistency or pure fantasy? Stereotact Funct Neurosurg 87:88–93

    Article  CAS  PubMed  Google Scholar 

  17. Gera D (2003) Ancient Greek ideas on speech, language, and civilization. Oxford University Press, Oxford

    Book  Google Scholar 

  18. Glauser D, Fankhauser H, Epitaux M, Hefti JL, Jaccottet A (1995) Neurosurgical robot Minerva: first results and current developments. J Image Guid Surg 1:266–272

    Article  CAS  PubMed  Google Scholar 

  19. Goto T, Hongo K, Kakizawa Y, Muraoka H, Miyairi Y, Tanaka Y, Kobayashi S (2003) Clinical application of robotic telemanipulation system in neurosurgery. Case report. J Neurosurg 99:1082–1084

    Article  PubMed  Google Scholar 

  20. Goto T, Hongo K, Yako T, Hara Y, Okamoto J, Toyoda K, Fujie MG, Iseki H (2013) The concept and feasibility of EXPERT: intelligent armrest using robotics technology. Neurosurgery 72(Suppl 1):39–42

    Article  PubMed  Google Scholar 

  21. Goto T, Miyahara T, Toyoda K, Okamoto J, Kakizawa Y, Koyama J, Fujie MG, Hongo K (2009) Telesurgery of microscopic micromanipulator system “neurobot” in neurosurgery: interhospital preliminary study. J Brain Dis 1:45–53

    PubMed Central  PubMed  Google Scholar 

  22. Haegelen C, Touzet G, Reyns N, Maurage CA, Ayachi M, Blond S (2010) Stereotactic robot-guided biopsies of brain stem lesions: experience with 15 cases. Neurochirurgie 56:363–367

    Article  CAS  PubMed  Google Scholar 

  23. Havenbergh TS, Somers T (2012) Pathology: our lessons learned over 50 cases. J Neurol Surg B 73

  24. Heuer GG, Zaghloul KA, Jaggi JL, Baltuch GH (2008) Use of an integrated platform system in the placement of deep brain stimulators. Neurosurgery 62:245–247, discussion 247–248

    Article  PubMed  Google Scholar 

  25. Hongo K, Goto T, Miyahara T, Kakizawa Y, Koyama J, Tanaka Y (2006) Telecontrolled micromanipulator system (NeuRobot) for minimally invasive neurosurgery. Acta Neurochir Suppl 98:63–66

    Article  CAS  PubMed  Google Scholar 

  26. Hongo K, Kobayashi S, Kakizawa Y, Koyama J, Goto T, Okudera H, Kan K, Fujie MG, Iseki H, Takakura K (2002) NeuRobot: telecontrolled micromanipulator system for minimally invasive microneurosurgery-preliminary results. Neurosurgery 51:985–988, discussion 988

    PubMed  Google Scholar 

  27. Hounsfield GN (1995) Computerized transverse axial scanning (tomography): part I. Description of system. 1973. Br J Radiol 68:H166–H172

    CAS  PubMed  Google Scholar 

  28. Howe RD, Matsuoka Y (1999) Robotics for surgery. Annu Rev Biomed Eng 1:211–240

    Article  CAS  PubMed  Google Scholar 

  29. Joskowicz L, Shamir, RR, Israel, Z, Shoshan, Y and Shoham, M. (2011) Renaissance robotic system for keyhole cranial neurosurgery: in-vitro accuracy study. Proceedings of the Simposio Mexicano en Ciruga Asistida por Computadora y Procesamiento de Imgenes Mdicas (MexCAS’11)

  30. Kantelhardt SR, Finke M, Schweikard A, Giese A (2013) Evaluation of a completely robotized neurosurgical operating microscope. Neurosurgery 72(Suppl 1):19–26

    Article  PubMed  Google Scholar 

  31. Kantelhardt SR, Martinez R, Baerwinkel S, Burger R, Giese A, Rohde V (2011) Perioperative course and accuracy of screw positioning in conventional, open robotic-guided and percutaneous robotic-guided, pedicle screw placement. Eur Spine J 20:860–868

    Article  PubMed Central  PubMed  Google Scholar 

  32. Kubben PL, Pouratian N (2012) An open-source and cross-platform framework for brain computer interface-guided robotic arm control. Surg Neurol Int 3:149

    Article  PubMed Central  PubMed  Google Scholar 

  33. Kwoh YS, Hou J, Jonckheere EA, Hayati S (1988) A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery. IEEE Trans Biomed Eng 35:153–160

    Article  CAS  PubMed  Google Scholar 

  34. L’Orsa R, Macnab CJ, Tavakoli M (2013) Introduction to haptics for neurosurgeons. Neurosurgery 72(Suppl 1):139–153

    Article  PubMed  Google Scholar 

  35. Lang MJ, Greer AD, Sutherland GR (2011) Intra-operative robotics: NeuroArm. Acta Neurochir Suppl 109:231–236

    Article  PubMed  Google Scholar 

  36. Le Roux PD, Das H, Esquenazi S, Kelly PJ (2001) Robot-assisted microsurgery: a feasibility study in the rat. Neurosurgery 48:584–589

    Article  PubMed  Google Scholar 

  37. Louw DF, Fielding T, McBeth PB, Gregoris D, Newhook P, Sutherland GR (2004) Surgical robotics: a review and neurosurgical prototype development. Neurosurgery 54:525–536, discussion 536–527

    Article  PubMed  Google Scholar 

  38. Mattei T (2013) The O-Arm revolution in spine surgery. J Neurosurg Spine. 2013 Sep 20. [Epub ahead of print]

  39. Mei Q, Harris SJ, ArambulaCosio F, Nathan MS, Hibberd RD, Wickham JEA, Davies BL (1996) PROBOT—a computer integrated prostatectomy system. Vis Biomed Comput 1131:581–590

    Article  Google Scholar 

  40. Moniz E (1934) L’ Angiographie Cerebrale Paris, France;. Masson & Cie

  41. Morgan PS, Carter T, Davis S, Sepehri A, Punt J, Byrne P, Moody A, Finlay P (2003) The application accuracy of the Pathfinder neurosurgical robot. Cars 2003. Comp Assist Radiol Surg Proc 1256:561–567

    Google Scholar 

  42. Moskowitz RM, Young JL, Box GN, Pare LS, Clayman RV (2009) Retroperitoneal transdiaphragmatic robotic-assisted laparoscopic resection of a left thoracolumbar neurofibroma. JSLS 13:64–68

    PubMed Central  PubMed  Google Scholar 

  43. Nathoo N, Cavusoglu MC, Vogelbaum MA, Barnett GH (2005) In touch with robotics: neurosurgery for the future. Neurosurgery 56:421–433, discussion 421–433

    Article  PubMed  Google Scholar 

  44. Nimsky C, Rachinger J, Iro H, Fahlbusch R (2004) Adaptation of a hexapod-based robotic system for extended endoscope-assisted transsphenoidal skull base surgery. Minim Invasive Neurosurg 47:41–46

    Article  PubMed  Google Scholar 

  45. Ohta T, Kuroiwa T (2000) Freely movable armrest for microneurosurgery: technical note. Neurosurgery 46:1259–1261

    Article  CAS  PubMed  Google Scholar 

  46. Pearce J (2011) George C. Devol, Inventor of Robot Arm, Dies at 99. The New York Times

  47. Procaccini E, Dorfmuller G, Fohlen M, Bulteau C, Delalande O (2006) Surgical management of hypothalamic hamartomas with epilepsy: the stereoendoscopic approach. Neurosurgery 59:ONS336–ONS344, discussion ONS344-336

    Article  PubMed  Google Scholar 

  48. Roser F, Tatagiba M, Maier G (2013) Spinal robotics: current applications and future perspectives. Neurosurgery 72(Suppl 1):12–18

    Article  PubMed  Google Scholar 

  49. Schizas C, Thein E, Kwiatkowski B, Kulik G (2012) Pedicle screw insertion: robotic assistance versus conventional C-arm fluoroscopy. Acta Orthop Belg 78:240–245

    PubMed  Google Scholar 

  50. Shaikhouni A, Elder JB (2012) Computers and neurosurgery. World Neurosurg 78:392–398

    Article  PubMed  Google Scholar 

  51. Shoham M, Lieberman IH, Benzel EC, Togawa D, Zehavi E, Zilberstein B, Roffman M, Bruskin A, Fridlander A, Joskowicz L, Brink-Danan S, Knoller N (2007) Robotic assisted spinal surgery—from concept to clinical practice. Comput Aided Surg 12:105–115

    CAS  PubMed  Google Scholar 

  52. Stuer C, Ringel F, Stoffel M, Reinke A, Behr M, Meyer B (2011) Robotic technology in spine surgery: current applications and future developments. Acta Neurochir Suppl 109:241–245

    Article  PubMed  Google Scholar 

  53. Sukovich W, Brink-Danan S, Hardenbrook M (2006) Miniature robotic guidance for pedicle screw placement in posterior spinal fusion: early clinical experience with the SpineAssist. Int J Med Robot 2:114–122

    Article  CAS  PubMed  Google Scholar 

  54. Sutherland GR, Lama S, Gan LS, Wolfsberger S, Zareinia K (2013) Merging machines with microsurgery: clinical experience with neuroArm. J Neurosurg 118:521–529

    Article  PubMed  Google Scholar 

  55. Sutherland GR, Latour I, Greer AD, Fielding T, Feil G, Newhook P (2008) An image-guided magnetic resonance-compatible surgical robot. Neurosurgery 62:286–292, discussion 292–283

    Article  PubMed  Google Scholar 

  56. Sutherland GR, Wolfsberger S, Lama S, Zarei-nia K (2013) The evolution of neuroArm. Neurosurgery 72(Suppl 1):27–32

    Article  PubMed  Google Scholar 

  57. Taylor RH, Lavalle S, Burdea G, Mosges R (eds) (1995) Computer-integrated surgery: technology and clinical applications. MIT Press, Cambridge/MA

    Google Scholar 

  58. Varma TR, Eldridge P (2006) Use of the NeuroMate stereotactic robot in a frameless mode for functional neurosurgery. Int J Med Robot 2:107–113

    Article  CAS  PubMed  Google Scholar 

  59. Varma TR, Eldridge PR, Forster A, Fox S, Fletcher N, Steiger M, Littlechild P, Byrne P, Sinnott A, Tyler K, Flintham S (2003) Use of the NeuroMate stereotactic robot in a frameless mode for movement disorder surgery. Stereotact Funct Neurosurg 80:132–135

    Article  CAS  PubMed  Google Scholar 

  60. Wei J, Wang T, Liu D (2011) A vision guided hybrid robotic prototype system for stereotactic surgery. Int J Med Robot 7:475–481

    Article  PubMed  Google Scholar 

  61. Young RF (1987) Application of robotics to stereotactic neurosurgery. Neurol Res 9:123–128

    CAS  PubMed  Google Scholar 

  62. Zamorano L, Li Q, Jain S, Kaur G (2004) Robotics in neurosurgery: state of the art and future technological challenges. Int J Med Robot 1:7–22

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Tobias A. Mattei.

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Comments

Kazuhiro Hongo, Matsumoto, Japan

The authors have nicely reviewed historical developments and current state of robotic technology in neurosurgery as well as a comprehensive summary of the currently available systems. As surgery-assisting robotics, there are mainly two types applicable in neurosurgery: stereotactic needle and master–slave manipulator. The stereotactic needle is a good application of robotic technology, while master–slave manipulator has not yet been fully developed in neurosurgical field. The da Vinci surgical system, master–slave type surgical robotics, is currently used in various fields where there is an adequate working space for manipulators such as abdominal, retroperitoneal, and thoracic areas and so on. On the other hand, for neurosurgery where working space is quite limited, further developments in master–slave manipulator might be needed. Another point as the authors described is the haptic feedback which is not available yet. With this function, a surgeon can conduct more accurate surgical procedure. In the future development, however, haptic sensation to the surgeon can be available.

As the technology develops so fast, surgery-assisting robotics becomes available in the near future. Important point, however, is that even with the development of surgery-assisting robotics, surgery should be carried out or controlled by a surgeon, not by robotics, especially in a master–slave manipulator type.

Claudio Tatsui, Houston, USA

Mattei et al. presents a very interesting review of the past, present, and future applications of robotical technology to brain and spinal neurosurgical procedures. Currently, the applicability of robotic technology in neurosurgery is limited and in its infancy, however, as pointed by the authors, development of robotic modular systems can find great applicability when combined to intraoperative imaging in order to perform complex motor tasks through narrow and limited surgical corridors, overcoming the limitations in dexterity of the human hands. In addition, improvements in haptic feedback will allow development of better simulators and will facilitate training in complex and delicate neurosurgical procedures. Obviously, as new technology is introduced, clinical studies have to be performed to evaluate the exact impact in terms of cost and improvement in outcome.

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Mattei, T.A., Rodriguez, A.H., Sambhara, D. et al. Current state-of-the-art and future perspectives of robotic technology in neurosurgery. Neurosurg Rev 37, 357–366 (2014). https://doi.org/10.1007/s10143-014-0540-z

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