Sekhar, Laligam N. MD; Tariq, Farzana MD; Kim, Louis J. MD; Pridgeon, James MHA; Hannaford, Blake PhD
“First Law. A robot may not injure a human being, or through inaction, allow a human being to come to harm.
Second Law. A robot must obey the orders given to it by human beings, except where such orders conflict with the first law.
Third Law. A robot must protect its own existence as long as such protection does not conflict with the First or Second laws.
Zeroth Law. A robot may not harm humanity, or by inaction, allow humanity to come to harm.”
The Four Laws of Robotics,
Isaac Asimov, 1942, 1985.
“A lot of times, people don't know what they want until you show it to them.”
Steve Jobs, 1998.
During the last 100 years, Neurosurgery has advanced tremendously due to adoption of new technologies. In many cases, the need for adopting new technology was self-evident. In other cases, (such as the Apple iPhone) the need is evident to a visionary (Steve Jobs) but not to others. When such a revolutionary product is available, adoption follows, slowly at first. In all instances of medical technology development, there are various teams involved. The first is usually a Surgeon - Engineer team that develops a new product. This may involve many innovations, but also investments, missteps, failures, and successes. The next group consists of neurosurgical pioneers, who adopt and popularize the new technology by showcasing its utility to other surgeons. Such surgeons may be motivated not only by their desire to adopt new technologies to benefit their patients, but also by a desire to gain fame and attract new patients. The last group is the “fact checkers” who, through comparative effectiveness research, show that the new technology benefits patients (or does not), and is more effective or less costly than existing tools and related processes. The last group involved is the third party payer, either Insurance Companies or Government agencies, (and indirectly the tax payers) who agree to pay for the technology.
This special issue of Neurosurgery is devoted to Virtual Reality and Robotics in Neurosurgery, under the guest editorship of Dr Garnette Sutherland.
It is now well accepted that both residents and neurosurgeons need training in new surgical procedures to reach a certain level of competency, before performing them in patients. The old adage of “see one, do one, teach one” is definitely not valid in neurosurgery today. The classical method of surgical training used by Halstead (and by others before him) is now widely used. In addition, it is supplemented by observation of operations by expert surgeons, directly or through videos, and practice of the procedure on cadavers. Since cadaver-based training is limited, other techniques are being developed that involve virtual reproduction of the actual patient's anatomy, and simulation using various tools. In a sense, this is an extension of the virtual anatomical imagination which many expert surgeons develop intuitively early in their practice.
Virtual reality systems have been developed for ventriculostomy,1 pedicle screw placement for simulation of surgery with the NEUROBOT (the ROBO-SIM),2,3 simulation of image-guided or microsurgical procedures using the “NeuroArm,”4 for virtual planning of radiosurgical treatment, for virtual reproduction of anatomy,5 and even for remote surgical assistance of surgery in cadavers.6
Future application of similar techniques will involve the application of new technologies from the Game Industry, such as X-Box Kinect (Microsoft, Seattle, Washington), which are already quite advanced, and from the Military (which may be classified). Two major problems for the adoption of such innovations is the small size of the neurosurgical training market, and validating that such techniques improve patient care.
There is a pressing need for Virtual Reality-based training of complex surgical procedures, such as the Clipping of an Intracranial Aneurysm, or the microsurgical removal of a Vestibular Schwannoma. However, due to the complexity of designing the programs for such training, practical adoption is not expected in the near future.
ROBOTICS IN NEUROSURGERY
A robot is a device with a programmable computer brain, which has mechanical attributes to perform tasks that interact with the environment. Robots are widely used in industry today, performing mechanical tasks that are repetitive (such as in the Automobile industry) or in high-risk environments such as Nuclear Reactors or the Space Station. The United States Government has identified Robotics (including Medical Robotics) as one of the most important growth industries of the future, requiring special education, innovation, and business creation.
In general, medical Robots may be classified as Active or Passive. “Active” Robots are those that have been programmed to sense and evaluate the data from their environment, and complete their tasks appropriately. An example is the ROBODOC (Integrated Surgical System Inc, Fremont, California) used for hip replacement surgery. An example encountered in daily life is the vacuum cleaner Robot (iRobot, Burlington, Massachusetts). A passive robot (also called a Master-Slave Robot) is one where the surgeon provides the input to control and move the device. They can also be semi-active, meaning that the Robot may also provide some guidance to the surgeon in performing a procedure. An example of that is NeuroMate (Renishaw Inc, Wotton-under-Edge Gloucestershire, United Kingdom), which provides such guidance in performing stereotactic procedures.
COMPONENTS OF A MEDICAL ROBOT
Any Medical Robotic System consists of sensors for acquiring information, a computer that allows the information to be processed easily, an operator console where the surgeon can view the information and direct the robot to perform certain tasks (at either the master-slave or supervisory level), actuators that transmit the surgeon's movements, and end effectors, which are the surgical tools. The sensors may be visual, based on information gained through operating microscopes, endoscopes, or other types of cameras that are placed in relation to the operative field. Besides the visual spectrum, they may also involve ultrasound, or infrared waves. More recently, “Haptic sensors” (from Hapto in Greek meaning “to touch”) have been incorporated in the effectors, to give the surgeon a sense of feel, and force feedback from the instruments.
A major advantage with master-slave Robotic systems is the ability to scale down motion (by a ratio such as 4:1) from the surgeon's hand; this allows for greater precision. Tremors from the surgeon's hand can be filtered out by software, thus allowing all surgeons to operate with steady hands. The end effector can have 6 or more joints or degrees of motion. This allows greater flexibility of actions than the human forearm/wrist/fingers in controlling surgical instruments.
EXPERIENCE WITH THE DA VINCI SURGICAL SYSTEM
The da Vinci Robotic system (Intuitive Surgical, Inc, Sunnyvale, California) was initially developed for use in cardiac surgery, but did not gain many users, since cardiac surgeons could perform the procedures with the same level of precision, but much faster. However, it was more widely adopted in laparoscopic surgery, for nerve saving prostatectomy, other urological procedures, and gynecological procedures.
The da Vinci Robot has recently been adapted to perform trans-nasal endoscopic skull base procedures,7 as well as the resection of advanced stage nasopharyngeal carcinoma.8 However, this robot is quite bulky and cumbersome, and is not designed for use in Neurosurgery, or microsurgery.
ROBOTS DEVELOPED FOR STEREOTACTIC SURGERY
A number of Robots have been developed for procuring CT or MRI information from the patient, and for guiding the surgeon to perform accurate stereotactic procedures. One example is the Neuro-Mate (Renishaw Inc, New Mills, Wotton-under-Edge, Gloucestershire GL12 8JR, United Kingdom). Such Robots are used to perform accurate stereotactic biopsies, including brain stem locations,9 precise placement of ventricular reservoirs for administration of chemotherapy,10 implantation of deep brain stimulator leads,11 and in epilepsy surgery to accurately locate the temporal horn and epileptic focus in the brain by Elijamel MS and others.12
The Cyberknife (Accuray, Sunnyvale, California) is a robotic stereotactic Gamma Radiation system used for precise and focused irradiation of tumors, arteriovenous malformations, and other lesions anywhere in the body, but particularly those involving the brain, spine, and spinal cord. Here, the patient lies still, while the robot moves around to deliver radiation with precision and proper dosage to the desired place.13
Developing robots for microsurgery is much more challenging than for stereotactic procedures because of the larger number of devices and movements that need to be designed. Such microsurgery can be performed through a craniotomy, or through a key hole. Two groups in Japan have developed such systems. The one developed at Shinshu University by Hongo K and others2 (The NeuRobot) is a master-slave robot wherein the actions on the patient are performed through a 10 mm outer metallic sheath, through which pass a 4 mm three-dimensional endoscope, 2 micromanipulators, each 3 mm in diameter, and 5 channels for irrigation and suction.14-18
The master–slave robot platform developed by Akio Morito's group at the University of Tokyo is for procedures similar to those performed by neurosurgeons with the aid of the operating microscope. Using the system, an experienced surgeon could perform complex experimental tasks such as suturing a blood vessel 0.7 mm in diameter. The robotic system showed sufficient accuracy and dexterity, but a longer task completion time than the experienced surgeon performing the procedure without the aid of the Robotic device.18
The NeuroArm developed by Garnette Sutherland and Associates is the most sophisticated neurosurgical master-slave system to date. It allows both stereotactic and microsurgical procedures to be performed in an environment with real-time MRI.19 Many live patients have been operated on with this Robot, which is still being developed. The system's console provides a 3-Dimensional binocular display and haptic feedback. The device has recently been granted approval for human use by the US Food and Drug Administration.
ROBOTIC SPINAL SURGERY
Due to the need for accuracy of placement of various screws, and the drilling of bone performed by the surgeon who is usually standing bent over the patient weighed down by lead shields, Robotic Surgery would seem to be an ideal tool for spine surgery. The placement of pedicle screws has been performed in both lumbar and cervical spine surgery with equivalent accuracy results between C-arm assisted manual and robotically assisted techniques.20
SURGICAL ROBOTICS RESEARCH AT THE UNIVERSITY OF WASHINGTON
The Raven is a research platform for surgical robotics developed at the University of Washington and U.C. Santa Cruz by a team of Engineers (Blake Hannaford, Jacob Rosen and others) in collaboration with General Surgeon Dr Mika Sinanan, and Pediatric Urologist Dr Thomas Lendvay for general surgical and urological laparoscopic procedures. As compared to the da Vinci Robot, it is much smaller, and can be mounted on the operating table. The spherical design of the effectors limits the range of motion at the surgical port location, which is a mechanical fail-safe design (Figure 1). Raven is now in use at 7 universities conducting research on a wide variety of topics. These universities did not have prior access to such an experimental platform.
A group of surgeons (Laligam Sekhar, Louis Kim, Kristen Moe, and Thomas Lendvay) and other Neurological Surgery faculty (James Pridgeon) has been working with the Engineering group at University of Washington (Blake Hannaford and others) and University of California, Santa Cruz (Jacob Rosen and others), to develop a robotically controlled, bendable robotic sheath (Roboscope) (Figure 2). Through this device, a small flexible endoscope(s) can be inserted for visualization of the operative field. It also contains micromanipulators for grasping, cutting, etc., and working channels for irrigation, suction, laser etc. This device is still under development.
INTELLIGENT (ACTIVE) ROBOTIC ASSISTANT
All surgeons are familiar with a good (human) assistant who provides suction, retraction, etc., in the right place at the right time during operative procedures. Over time, the assistant becomes very experienced in knowing the needs of the particular operation and the surgeon. When observed, such Surgeon–Assistant teams appear to be as graceful as a ballet or symphony. But such a team takes time and active effort to develop. An intelligent Robot can be designed to perform these assistive tasks, and the accuracy of the robot can be improved by a “learning process.” Although such a robot is difficult to develop, it is likely to find ready acceptance by neurosurgeons.
ROBOTICS IN HOSPITALS AND FOR HOME HEALTH CARE
Hospitals and neurosurgical services in particular are highly labor intensive areas. Humanoid robots are thought to find many applications in the hospital, helping to care for patients, for cleaning of hospital areas and instruments, delivering food, and to act as intelligent assistants to alert health care personnel about ongoing problems. A robot has been used in intensive care environments in North America for observing patients, and transmitting information to physicians.25,26 In Japan, increasing attention has been given to using humanoid robots to solve problems concerning personnel shortages and to reduce on-shift duty workloads in clinical and nursing situations. An extended eMOSAIC architecture has been used successfully to generate squatting and object-carrying behaviors in real humanoid robots.26 Robot-Assisted Rehabilitation Therapy is also being used in Japan by building specific technological tools (eg, functional electric stimulation, virtual reality, transcranial magnetic stimulation) to facilitate movement as well as provide assistance to disabled patients. The 5 year Home - Use Robot Practical Application Project, started in 2009 in Japan, seeks a robot that can be used as a wheel chair and a bed; a cleaning robot; a security robot; a wearable robot suit that assists daily activities; and a 2-wheeled rideable robot.
This year, the US Army Research, Development, and Engineering Command (RDECOM) issued a proposal as part of the Small Business Innovation Research (SBIR) funding program to build prototype adaptive actuators for medical robotic systems. These are to improve the robotic capacity needed for future medical robotic applications, such as heavy patient lifting, combat casualty evacuation, dexterous manipulation, and combat casualty care.27
LIMITATIONS AND ACCEPTANCE OF ROBOTS IN NEUROSURGERY
Being technical devices, Robots are bound to have technical problems, especially early in their development. This is commonly encountered with all present hospital equipment and in the operating room. Such a technical failure can be dangerous to the patient due to the actions of the robot, or its inaction in critical moments. Redundant safety mechanisms and the ability to mechanically inactivate such a robot in the OR are vital elements in their design. The use and maintenance of such Robots also require personnel with greater education and skill levels than presently available. This should be factored into the cost equation when considering Robotic Surgery.
Robots will also occupy more space in the OR than their human counterparts, counting not only the effector device near the patient but also the console for controlling it. Neurosurgical robotics currently can demonstrate extraordinary precision, but fail to mimic “human speed.” This increased operative time must be addressed in future iterations in order to gain widespread momentum.
Adequate training of surgeons, nurses, and health care professionals is necessary, in order to ensure this technology is properly used.
If autonomous or semi-autonomous medical Robots are to be adopted in neurosurgery, they must perform tasks that are difficult to perform or are repetitive for the average neurosurgeon, and they must perform these tasks at least as well as human neurosurgeons. Adoption of such robots is likely to occur earlier in developed countries where human labor is more expensive. Nevertheless, there are plenty of well-trained neurosurgeons in every country. Therefore, greater precision, elimination of tiresome and repetitive aspects of a particular operation, intelligent interaction (eg guidance with certain aspects of an operation), intelligent assistance, and training of junior surgeons are the most likely roles for such robots in the near future. Another potential role in the performance of emergent neurosurgery is in the battlefield or other remote (mountains, space, etc) environments by tele-robotics. This would entail neurosurgeons working remotely with a local health care professional.
The funding for research into Robotics in Neurosurgery is a problem. Most of the early research has been funded by Government or Defense sources. Since the market for product is small, commercialization of products is more difficult.
Virtual reality-based training and Robot Assisted Neurosurgery are emerging frontiers. They are expected to be a part of the revolution in Neurosurgery in the 21st century, along with molecular neurosurgery, and imaging advances.
Laligam N. Sekhar has stocks in SPISURGICAL, Inc, and in Viket Medical. Louis Kim and James Pridgeon have stocks in SPISURGICAL, Inc.
The work reported here was supported by following research funds:
1. Department of Defense STTR Phase II Grant W81XWH-09-C-0159, Surgical Cockpit - Multisensory/Multimodal Interfaces for Robotic Surgery.
2. Department of Defense STTR Phase I Grant W81XWH-11-C-0010, Surgical Performance, Intelligent Surgical Instrumentation, and Surgical Robotics.
3. Department of Defense STTR Phase I Grant W81XWH-09-C-0156, Robotic Sheath for Minimally Invasive Neurosurgery.
1. Lemole GM Jr, Banerjee PP, Luciano C, Neckrysh S, Charbel FT. Virtual reality in neurosurgical education: part-task ventriculostomy simulation with dynamic visual and haptic feedback. Neurosurgery. 2007;61(1):142–148; discussion 148-149.
2. Hongo K, Goto T, Miyahara T, Kakizawa Y, Koyama J, Tanaka Y. Telecontrolled micromanipulator system (NeuRobot) for minimally invasive neurosurgery. Acta Neurochir Suppl. 2006;98:63–66.
3. Radetzky A, Rudolph M. Simulating tumour removal in neurosurgery. Int J Med Inform. 2001;64(2-3):461–472.
4. Lang MJ, Greer AD, Sutherland GR. Intra-operative robotics: NeuroArm. Acta Neurochir Suppl. 2011;109:231–236.
5. Balogh A, Preul MC, Schornak M, Hickman M, Spetzler RF. Intraoperative stereoscopic QuickTime Virtual Reality. J Neurosurg. 2004;100(4):591–596.
6. Shenai MB, Dillavou M, Shum C, Ross D, Tubbs RS, Shih A, Guthrie BL. Virtual interactive presence and augmented reality (VIPAR) for remote surgical assistance. Neurosurgery. 2011;68(1 suppl operative):200–207; discussion 207.
7. Kupferman ME, Demonte F, Levine N, Hanna E. Feasibility of a robotic surgical approach to reconstruct the skull base. Skull Base. 2011;21(2):79–82.
8. Wei WI, Kwong DL. Recurrent nasopharyngeal carcinoma: surgical salvage vs. additional chemoradiation. Curr Opin Otolaryngol Head Neck Surg. 2011;19(2):82–86.
9. Haegelen C, Touzet G, Reyns N, Maurage CA, Ayachi M, Blond S. Stereotactic robot-guided biopsies of brain stem lesions: experience with 15 cases. Neurochirurgie. 2010;56(5):363–367.
10. Lollis SS, Roberts DW. Robotic placement of a CNS ventricular reservoir for administration of chemotherapy. Br J Neurosurg. 2009;23(5):516–520.
11. Lefranc M, Le Gars D. Robotic implantation of deep brain stimulation leads, assisted by intra-operative, flat-panel CT. Acta Neurochir (Wien). 2012;154(11):2069–2074.
12. Eljamel MS. Robotic application in epilepsy surgery. Int J Med Robot. 2006;2(3):233–237.
13. Golanov AV, Gorlachev GE, Antipina NA, et al.. CyberKnife stereotactic radiotherapy for mass lesions of the spinal cord and spine [in Russian]. Zh Vopr Neirokhir Im N N Burdenko. 2012;76(1):54–62.
14. Goto T, Hongo K, Kakizawa Y, et al.. Clinical application of robotic telemanipulation system in neurosurgery. Case report. J Neurosurg. 2003;99(6):1082–1084.
15. Goto T, Hongo K, Koyama J, Kobayashi S. Feasibility of using the potassium titanyl phosphate laser with micromanipulators in robotic neurosurgery: a preliminary study in the rat. J Neurosurg. 2003;98(1):131–135.
16. Hongo K, Kobayashi S, Kakizawa Y, et al.. NeuRobot: telecontrolled micromanipulator system for minimally invasive microneurosurgery-preliminary results. Neurosurgery. 2002;51(4):985–988.
17. Koyama J, Hongo K, Kakizawa Y, et al.. Endoscopic telerobotics for neurosurgery: preliminary study for optimal distance between an object lens and a target. Neurol Res. 2002;24(4):373–376.
18. Mitsuishi M, Morita A, Sugita N. Master-slave robotic platform and its feasibility study for micro-neurosurgery [published online ahead of print]. Int J Med Robot. 2012.
19. Sutherland GR, Latour I, Greer AD. Integrating an image-guided robot with intraoperative MRI: a review of the design and construction of neuroArm. IEEE Eng Med Biol Mag. 2008;27(3):59–65.
20. Schizas C, Thein E, Kwiatkowski B, Kulik G. Pedicle screw insertion: robotic assistance versus conventional C-arm fluoroscopy. Acta Orthop Belg. 2012;78(2):240–245.
21. Kapetanakis V, Jacob K, Klauschie J, et al.. Robotic presacral neurectomy—technique and results. Int J Med Robot. 2012;8(1):73–76.
22. Yang MS, Kim KN, Yoon do H, et al.. Robot-assisted resection of paraspinal Schwannoma. J Korean Med Sci. 2011;26(1):150–153.
23. Stüer C, Ringel F, Stoffel M, et al.. Robotic technology in spine surgery: current applications and future developments. Acta Neurochir Suppl. 2011;109:241–245.
24. Ponnusamy K, Chewning S, Mohr C. Robotic approaches to the posterior spine. Spine (Phila Pa 1976). 2009;34(19):2104–2109.
25. Bäck I, Kallio J, Perälä S, Mäkelä K. Remote monitoring of nursing home residents using a humanoid robot. J Telemed Telecare. 2012;18(6):357–361.
26. Sugimoto N, Morimoto J, Hyon SH, Kawato M. The eMOSAIC model for humanoid robot control. Neural Netw. 2012;29-30:8–19.
27. Dickstein-Fischer L, Alexander E, Yan X, et al.. An affordable compact humanoid robot for Autism Spectrum Disorder interventions in children. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:5319–5322.
28. Wu YH, Fassert C, Rigaud AS. Designing robots for the elderly: appearance issue and beyond. Arch Gerontol Geriatr. 2012;54(1):121–126.
29. Fuji S. Research on the possibility of humanoid robots to assist in medical activities in nursing homes and convalescent wards. Paper Presented at: Natural Language Processing and Knowledge Engineering (NLP-KE), 7th International Conference; November 27-29, 2011; Tokushima, Japan.
30. Lambercy O. Development of a robot-assisted rehabilitation therapy to train hand function for activities of daily living. Paper Presented at: Rehabilitation Robotics. ICOR. IEEE 10th International Conference; June 13-15, 2007; Singapore.
Figure. No available...Image Tools
This article has been cited 1 time(s).
The Cancer JournalFuture of Robotic SurgeryThe Cancer Journal
Copyright © by the Congress of Neurological Surgeons