By the early 1980s, neurosurgeons were beginning to reach their limits based on traditional methods alone. Even with technological improvements in image guidance, intraoperative imaging, and microscopy, the scale of surgery has become so small that even the best human surgeons become limited by their natural dexterity2,3. The increasing need for greater magnification and smaller tools has made the human hand unfeasible to perform the tasks. Improvements in computer technology, engineering, minimum invasive surgery, along with the new neuroimaging techniques, created the concept of digital robotic neurosurgery2,3. Neurosurgery was one of the first organ systems in which robotic surgery was introduced, due to the high precision that was required to localize and manipulate within the brain, and the relatively fixed landmarks of the cranial anatomy1. The introduction of robot assistance into the surgical arena allowed the surgeon to work with greater accuracy at the microscopic level.

How we got to the Technology today
Programmable Universal Machine for Assembly industrial robot (1985 Ė Advanced Research & Robotics, Oxford, CT)

The PUMA was the first time a robot was ever used for neurosurgery. The surgeon inputted the x-y coordinates on a probe based on a preoperative image of an intracranial lesion. He then used programs which calculated the stereotactic coordinates (frame-based), which then guided the drilling of the biopsy2,3. This was possible with the introduction of a Cartesian robot (Compass International, Rochester, MN) which placed a stereotactic head frame around the patientís head2,3. It then uses fiducial markers to record an image of the patientís brain. The device lacked safety features, but the potential of this technology excited scientists all over the world. Robotics became increasingly used in frame-based stereotactic techniques.

NeuroMate (1987 - Integrated Surgical Systems, Sacramento, CA)

NeuroMate was the first neurorobotic device to be approved by FDA, as well as the first to be commercially available. Preoperative imaging helped the surgeon plan the procedure, and a passive robotic arm was able to perform limited tasks in over 1000 procedures2,3. However, this technology still relied on preoperative images to position the robot, and was prone to errors when the brain shifted.
Minerva (1991 Ė University of Lausanne, Lausanne, Switzerland)

Minerva was the first system to provide image guidance in real-time, allowing the surgeon to change the trajectory as the brain moved, resulting in frameless stereotaxy12. This was important because the structure of the brain and fiducial markers was assumed to be in the same position before. The position of surgical tools in relation to intracranial imaging could now be seen. Intraoperative imaging can compensate for these shifts and deformations. This was accomplished by placing a robotic arm inside a computed tomography (CT) scanner, and improvements in neuronavigation tools2,3. The implementation of CT greatly improved 3-D localization, and thus improving accuracy. The system also improved safety features which were lacking on the pervious models. However, the system was still limited because it could only perform single dimension incursions, and the patient had to be inside the CT system. As a result, the project was discontinued 2 years later in 19932,3.

Robotics in neurosurgery3
Robot-Assisted Microsurgery System (1995 Ė NASA, Washington DC)

RAMS was the first robotic system that resembled present day robotic surgical suites. It was the first system that was compatible with magnetic resonance imaging (MRI), as it was able to filter out electromagnetic fields that distorted images2,3. This was important, as the brain is best visualized with MRI, as it has better soft tissue anatomical detail11. Intraoperative imaging could now be fully integrated into the operating room unlike the Minerva. The system was based on master-slave control with 6 degrees of freedom, allowing 3-D manipulation, and not just limited to stereotactic procedures6. Along with adjustable tremor filters and motion scaling (dexterity enhancements), it was able to improve the precision of the surgeon by 3-folds6, and the benefits of robotic surgery were beginning to be seen. The systems currently on the market are surprisingly very similar in capabilities to RAMS.

The Steady Hand System (1995 Ė John Hopkins University, Baltimore, MD)

Along with RAMS, it defined the new standard of robotic systems in microsurgery. The new wave of systems all enhanced dexterity by filtering out tremor and featured the master-slave interface. The main improvement over RAMS was the fact that this system could also detect force in the handles3. This was important because surgeons had no idea how hard they were pressing against a surface before. Despite its great improvements, it was somewhat surprising that this system was never used in clinical applications.

NeuRobot (Shinshu University School of Medicine, Matsumoto, Japan)

The NeuRobot was the first system that performed telecontrolled surgery through an endoscope3. The 10-mm endoscope contained twin tissue forceps, a camera, a light source, and a laser3. The investigators removed a tumor from a patient, and found the system to be more accurate and less invasive then traditional methods3.

Robotics in neurosurgery3

Robotics in neurosurgery3

The SpineAssist Robot (Major Surgical Technologies, Haifa, Israel)

The soda can sized SpineAssist Robot was the first FDA approved robotic system for spinal surgery3. The device is guided by imaging and is placed directly on the spine for more accurate tool placement and less invasive surgery.

Current Technology

The neurosurgical robot consists of the following components at the most basic level: robotic arm, feedback sensors, controllers which instructs the robot (end-effector), a wireless localization system and a data processing center (the brain)2.The end-effector is able to control the robotic arm and use tools such as a probe, endoscope, or retractor. The tool can usually be manipulated with 6 of freedom. Sensors provide the surgeon with the necessary feedback from the surgical site, which is processed by the computer, returning information such as the location of a tool within a site2.

Using robotics for neurosurgical practice provides the surgeon with many advantages. The most important advantages pertaining to neurosurgery are the ability to perform surgery on a smaller scale (microsurgery), increased accuracy and precision (stereotactic surgery), access to small corridors (minimally invasive surgery), the ability to process large amounts of data (image-guided surgery), the ability for telesurgery, and deducing the surgeonís physiological tremor by 10-folds 2,3. This is particularly important to the brain because all the tissue of the organ is very delicate and of importance.

Surgical robots can be classified into three broad categories on the basis of how the surgeon interacts with them:
1. Supervisory-Controlled Systems

The procedure is planned beforehand and the surgeon specifies the motions which the robot goes through. The robot performs exactly the same motions automatically during the operation, with the surgeon watching to ensure that there are no errors2.
2. Telesurgical Systems

The surgeon directly performs the operation with a haptic interface. Using a force feedback joystick control, the surgeon carries out motions that the surgical manipulator replicates. The surgeon is able to see inside the cranial framework with real-time intraoperative imaging2.
3. Shared-Control System

The robot undergoes steady-hand manipulations of the surgical instrument while the surgeon controls the whole procedure. The surgeon and robot are jointly performing tasks2.

D. Economics and Demographics

Rough estimates show that around 550 neurosurgery cases are conducted in clinical trials every year 11. Robotic neurotechnology is not as widespread as the use of robotics in cardiac and urology procedures, and is rarely used clinically. As a result, the demographics of patients are hard to determine.

Since robotic technology is not widely used for neurosurgery yet, systems are usually purchased for clinical trials. Although the NeuroMate originally came out in 1987, and new intraoperative version was released in 199711. Since the new NeuroMate is very similar to todayís current technology, its costs will give us a good idea of the economics of the neurorobotics sector.

NeuroMate system (stereotactic frame-based version) - $362,43014

+ $88,380 for Stereotactic Frame + $236,368 for Frameless Stereotactic Version Includes: + $61,850 per year for Maintenance
+ $250 per operation for Sterile Operative Cover

The neurorobotics sector is nowhere as lucrative as the da Vinci Surgical System, and very rough estimates show the industry to be around $50-100 million11,13.

Complications and Success rates

One of the best clinical trials was conducted at the Oulu University Hospital using the Oulu Neuronavigator System/The Leksell Index System from September 1994 to September 1996. 19 operations were conducted (10 female, 8 male Ė one person had 2 operations) from patients aged 13 to 70 years old. Patients had a varying degree of lesion complications (low risk to high risk). Although the trails were almost performed a decade ago, there have not been significant advances in neurorobotic technology since then. Therefore, this data gives us a good idea of how present day machines perform 11.


  • Blood loss was on average 144ml per patient, which is very low (half a cup).
  • Postoperative hospital stays are the same as open surgery.
  • Accuracy was greater than open surgery.

    Characteristics of neuronagigator surgery:

  • Surgeons in general found the technology helpful and a better alternative to open surgery.
  • Procedure time due to the use of the neuronavigator system decreased. This is surprising, as most other robotic trials showed an increase in procedure time.
  • Surgeons mostly concluded that it increased safety. This was one of the only studies that were able to make such conclusions.

    Neuronavigator arm of the Leksell Index System:

    Required development and Improvements & Comparison with Existing Procedures

    Technological improvements in imaging and haptic feedback have greatly pushed robotic surgery forward by increasing the surgeonís dexterity and accuracy2,3. However, there are many improvements which need to be made before it becomes widespread; such as more accurate models of brain biophysical properties, tool-tissue interaction, multi-model imaging, and realistic rendering of hemorrhage. The number of procedures done using robotics will be limited until it becomes less distinguishable from reality. Reaching the goal is only a matter of time.

    There are a number of human-robot interface issues that need to be further improved. First of all, there needs to be dexterity enhancements, as the current movements are much slower than those done by the human hand2,3. Although there have been advancements in tactile feedback, the sense of touch is still lacking, and can be improved with bivrotactile feedback and thermal sensors. The current force feedback technology can also be improved by making the sensors smaller to fit at the very tip of the instrument. But they also need to maintain the same accuracy. 3-D spatial navigation, along with the surgeonís visual perception of the surgical field, is still not as good as conventional means. However, this should be improved with better virtual reality simulators. Spatial view is also not perfect, as MRIs still suffer some degree of geometric distortion11.

    The robots also must be better adapted to the deformability of soft brain tissue, as it is still not 100% real-time using current imaging techniques. Because of the highly variable mechanical behavior of the brain, models and estimates should be created during surgical simulation which can be applied during the operation. A better solution is the development of a smart probe from NASA that uses multiple microsensors like optimal spectroscopy, microelectrode recordings, micro-blood flow dynamics, and microendoscopy to gather large amounts of data regarding the tissue in real-time, which can determine nature of tissue.

    The other major problem is the cost-to-benefit ratio. Robotics is currently too expensive for the hospital to invest in for the rather simple tasks and poor-decision-making capabilities of the robot. Furthermore, although the robot is supposed to reduce risk, it has yet to be clinically proven.

    Since the current robotic technology is limited, current technological developments are aimed to make surgery less invasive, improve access to deep structures, and work at a greater magnification, as opposed to a system that replaces the surgeon entirely. The current poor human-to-machine interface, large design, limited ergonomics, and high cost-to-benefit ratio has ultimately limited the integration of robotics into clinical neurosurgical practice.

    The future of neurosurgery will include a system which can perform a wide spectrum of neurosurgical procedures, an increasing usage of telementoring and telesurgery, improvements in artificial intelligence, and virtual reality. The future of neurorobotics will see robots with ambidextrous abilities, more degrees of freedom, kinesthetic feedback, and a more user-friendly interface2. Greater integration of artificial intelligence and nanotechnology will soon create surgical procedures that cannot be done without it, revolutionizing neurosurgical practice2.

    Robotics in Neurosurgery3

    1. NeuroArm (2006 Ė University of Calgary, Calgary, Alberta, Canada)

    Although there are robotic systems that can perform specific well-defined tasks, there is currently no system that can perform a whole range of neurosurgical procedures. The $30 million NeuroArm project packages all the features that a neurosurgeon would need to directly manipulate any intra-cranial function (given present day technical constraints)4. Designed based on biomimicry, the controllerís hand movements (master) are replicated by robotic arms (slave) which hold surgical tools. The NeuroArm comprises 2 arms, each with 7 degrees of freedom, and a third arm with 2 cameras which provides the surgeon with a 3-D stereoscopic view7. NeuroArm is able to carry out microsurgical techniques and soft tissue manipulations such as biopsy, microdissection, thermocoagulation, blunt dissection, grasping of tissue, cauterizing, manipulation of a retractor, tool cleaning, fine suturing, suction, microscissors, needle drivers, and bipolar forceps. All the tools are exchanged at the end-effector, which also provides haptic force feedback to the surgeon. The 3rd component of the NeuroArm which makes it unique is the workstation7. In an attempt to replicate the surgical arena, the workstation provides the surgeon with 3 areas of feedback: sound, sight, and touch4. The surgical microscope (binoculars) give stereoscopic views of the brainís complex folds, while MRIs and robotic sensors create a 3-dimensional map of the brain for the surgeon on the displays. The microsurgical tools and real-time MRIs increase the accuracy of the surgeon 1000-folds (from an accuracy level of 1 millimeter to one-thousandth of a millimeter)5. The NeuroArm also incorporates safety features such as filtering out hand tremors, fail safe switches that prevent accidental movements, and force sensors which provide the sense of touch4,5. With a combination of intraoperative MRIs and fiducial markers, the neuroArm can also program the boundaries of the surgical field during presurgical planning. This is a safety feature against accidental movements. The materials used to build the components have been thoroughly tested for MR compatibility. The robotic arms are made out of titanium and polyetheretherketone (plastic polymer) because they have the least image distortion. The NeuroArmís image guidance system is so advanced that the surgeon can simulate the procedure in virtual reality beforehand. NeuroArm is currently being manufactured after going through a lengthy testing stage, and should be available in clinics within 2 years5.

    The workstation includes a computer processor, hand controllers for robotic arms, joystick controller for cameras and lights, 3 different displays and recorders7.
    • Video Display presents a 3-D stereoscopic view to give surgeon sense of depth.
    • MR Display shows the patients MR scan and tracks the location of the tool in real-time (pre, post, and intraoperative).
    • Control Panel Display shows operation status, force feedback, and control configuration.

    Robotic Long-Distance Telementoring in Neurosurgery8

    Telementoring and Telesurgery (The Socrates System)

    Advancements in computer and telecommunication technology have made it possible for a skilled surgeon to provide real-time guidance to less skilled surgeons across the country. Neurosurgery is ideal for telementoring and telesurgery because of the fact that neurosurgical institutions are usually confined to large urban areas. The Socrates system was the first telecollaboration system to be approved by the FDA, and was first used in Canada when a neurosurgical center in Halifax, Nova Scotia telementored a smaller center in Saint John, New Brunswick. Using the Socrates system, the mentor had direct control of the endoscope camera, real-time neuronavigation data, and two-way video and audio communications with the operative site. He was even able to control the robotic arm, AESOP, if necessary to give him full control of the surgical field in the remote site. It is called telementoring when the local surgical team is performing the operation with an expert mentor watching through the interface for errors. It is called telesurgery when the mentor performs the surgery directly with a surgical team watching to learn techniques (and as a safety precaution should mechanisms fail). Although the mentors have full control of the robotic armís movements during telesurgery, the surgeons in the remote area could override the mentorís control as a safety feature. The general conclusions from the 6 patient trials in Canada was that advice from an expert neurosurgeon provides significant advantages, and that neurosurgeons could save a lot of traveling time. However, experts are debating whether the high costs of skilled neurosurgeons are worth the marginal benefits. Furthermore, liability issues when telecollaboration is performed across the boarders of states and countries have hindered the expansion of this service8.

    Robotic Long-Distance Telementoring in Neurosurgery8

    3. Artificial Intelligence and Artificial Thought Processing

    With improvements in artificial intelligence, the robot will be able to sense what the surgeon is thinking and provide the appropriate responses. Furthermore, expert computer systems can replicate certain human functions, such as diagnosis of the human illness2.

    With advances in kinesthesia and quantitative reasoning, the robot should be able to understand the complex 3-D arena, and be able to plan the intraoperative procedure for the surgeon.

    4. Surgical Simulation and Virtual Reality (Interactive Virtual Dissection)

    Neurosurgeons have to be incredibly precise and knowledgeable when dealing with the highly complex cranial anatomy. By simulating an operation in an interactive 3-D environment, surgeons can practice over and over again to perfect their technique in a safe environment by manipulating 3-D models, and study the structures from many perspectives9,10. A project entitled interactive virtual dissection (IVD) attempts to simulate the drilling of the petrous bone in a virtual environment that provides the surgeon with visual, audio, and tactile feedback9.

    3-D Interactive Virtual Dissection Model
    The creation of the IVD simulation involved 4 main steps:

    1. Data generation from cadaver dissections
    2. Data collection from stereoscope, MRI, image rendering
    3. Image reconstruction and merging to create a 3-D model
    4. A virtual reality system that uses the 3-D model and can recreate the dynamics of the cranial anatomy

    The perfect simulator would be able to create a virtual environment that is indistinguishable from real-life experience by providing sensory input to all of our senses. However, the current virtual surgical simulators have many limitations, as it is unable to provide real-time haptic feedback and unable to recreate the physics of tissue displacement3,9,10. Without tactile feedback, the surgeon would not be accurately and safety performing the operation, and it simply would not feel like they are in the operating room. With technological advancements in the future, simulated surgical training environments should become increasingly lifelike. It should soon become an effective educational tool for neurosurgery, as it is less expensive than cadavers, and it permits performance evaluation of residence students as patients do not want them performing any major role in the operation9,10.

    Virtual Reality Neurosurgery10 Before this becomes an effective form of training and surgeon evaluation, it will need to show that a more structured curriculum and usage of the simulator will improve operating room results. As more detailed data becomes available with increasing number of operations, patient-specific simulation can be done by importing their MRIs2,3,9,10.