IN TOUCH WITH ROBOTICS:N THE F

TOPIC REVIEW

IN TOUCH WITH ROBOTICS: NEUROSURGERY FOR

THE FUTURE

Narendra Nathoo, M.D.,Ph.D.Brain Tumor Institute andDepartment of Neurosurgery,Cleveland Clinic Foundation,Cleveland, Ohio

M. Cenk Çavusoglu, Ph.D.Department of ElectricalEngineering and ComputerScience, Case Western ReserveUniversity, Cleveland, Ohio

Michael A. Vogelbaum,M.D., Ph.D.Brain Tumor Institute andDepartment of Neurosurgery,Cleveland Clinic Foundation,Cleveland, Ohio

Gene H. Barnett, M.D.Brain Tumor Institute andDepartment of Neurosurgery,Cleveland Clinic Foundation,Cleveland, Ohio

Reprint requests:Gene H. Barnett, M.D.,Brain Tumor Institute, S-80, The Cleveland Clinic,9500 Euclid Avenue,Cleveland, OH 44195.Email: [email protected]

Received, February 11, 2004.

Accepted, December 9, 2004.

THE INTRODUCTION OF multiple front-end technologies during the past quartercentury has generated an emerging futurism for the discipline of neurological surgery.Driven primarily by synergistic developments in science and engineering, neurosur-gery has always managed to harness the potential of the latest technical developments.Robotics represents one such technology. Progress in development of this technologyhas resulted in new uses for robotic devices in our discipline, which are accompaniedby new potential dangers and inherent risks. The recent surge in robot-assistedinterventions in other disciplines suggests that this technology may be considered oneof a spectrum of frontier technologies poised to fuel the development of neurosurgeryand consolidate the era of minimalism. On a more practical level, if the introductionof robotics in neurosurgery proves beneficial, neurosurgeons will need to becomefacile with this technology and learn to harness its potential so that the best surgicalresults may be achieved in the least invasive manner. This article reviews the role ofrobotic technology in the context of neurosurgery.

KEY WORDS: Computer-directed surgery, Neurosurgery, Robot, Robotic technology

Neurosurgery 56:421-433, 2005 DOI: 10.1227/01.NEU.0000153929.68024.CF www.neurosurgery-online.com

The discipline of neurosurgery has under-gone seismic change during the past 50years. Technological advances such as the

operating microscope, modern neuroimagingtechniques, endoscopic surgery, and computer-assisted surgery (CAS) were based on the prin-ciples of stereotaxy and supported by an explo-sion in computer technology. These advanceshave stimulated and augmented the concept ofminimally invasive neurosurgery. Soon thescale of surgery will become so small that eventhe most skilled surgeon will reach the limit ofhis or her dexterity. New surgical paradigmswill require improved precision that will beachievable only through a nexus of technologiesthat incorporate computer science, robotics,nanotechnology, biosensor technology, and ma-chine intelligence.

Exposure to robots and robotic technology,whether via science fiction, the space program,or as used to retrieve artifacts from sunkenships, have made society grow accustomed totheir existence, thereby increasing the likelihoodof acceptance of robots for use in other endeav-ors. The economic advantages, increased preci-sion, and improved quality of product persis-tently demonstrated by industrial robotsstimulated the application of robots in the health

sector. Although the first robot-assisted surgicalintervention was performed in 1985 (39), thefield of medical robotics, particularly robotics inneurosurgery, continues to emerge and has notreached critical mass. Inherent safety concernsand the observation that the growth of medicalrobotics seems to parallel that of CAS appar-ently have slowed the development of robotictechnology in neurosurgery.

The incorporation of robotic technology inthe neurosurgical operating room seems to beimminent, as surgical benefits have beenquantified for recent robot-assisted interven-tions (2, 5, 12, 14, 22, 28, 30, 33, 38, 40, 41, 44,50, 52, 58, 61, 66). In this review, we provideinsight into the fundamentals of surgical ro-botic technology with emphasis on the devel-opment and status of robotics in neurosur-gery, integration with current mainstreamsurgical technologies, current limitations, andtechnical challenges.

COMPUTER-ASSISTED VERSUSCOMPUTER-DIRECTED SURGERY

(NEUROROBOTIC SURGERY)

Although robotic technology may be envis-aged for use in a wide range of surgical pro-

NEUROSURGERY VOLUME 56 | NUMBER 3 | MARCH 2005 | 421

cedures, current applications have mainly concerned ster-eotaxy. With their precise, deliberate, and spatially encodedmovements, robots may be considered instruments of ster-eotaxy. Therefore, computer-assisted neurosurgery may beregarded as a transitional technology to more precise roboticneurosurgery in the near future. Both modes of surgery aresimilar with respect to preoperative planning and registration,but they differ in key aspects during the intraoperative phase.In the preoperative planning phase, a robot will allow com-puter simulation sequences of robotic motions with a virtualhaptic interface, allowing the surgeon to practice the operationbefore performing the procedure. The robotic system, unlikeCAS, is motorized and may be independent of the surgeonwith superior ability to constrain and work with surgical tools.The robot is only directly involved with the patient during theinterventional phase of the procedure. The fundamental ad-vantages of robotic-directed surgery over CAS are greateraccuracy, precision, and sustained identical repetitive motions(31). Robots have superior three-dimensional (3-D) spatialaccuracy, especially when linked to digitized image informa-tion. A significant improvement in manual dexterity is possi-ble with a robotic interface. This allows the surgeon to operatethrough smaller corridors of access, to choose longer workingdistances without tiring easily, and to perform microsurgeryon even smaller structures than currently possible. Further-more, the surgeon’s physiological tremor of �40 �m can bereduced to �4 �m by the use of a robotic interface (4). Becauseof their precision and accuracy, robots have the potential toproduce more reproducible outcomes with smaller margins oferror. Table 1 lists the advantages of robotic surgery over CASin more detail.

ROBOTS IN SURGERY

A surgical robot may be defined as: “A reprogrammable,multifunctional manipulator designed to move material,parts, tools, or specialized devices through various pro-grammed motions for the performance of a variety of tasks”(Robot Institute of America, 1979 [67]). At its most basic level,a robot consists of the following components: Mechanicaldevice consisting of a wheeled platform, arm, and/or otherconstruction capable of interacting with its environment; sen-sors that receive information from both internal (robot) andexternal (environment) sources; and systems that assimilateand process the input data in the context of the device’scurrent situation and instruct the robot to perform appropriateresponsive actions. A robot is connected to a computer (con-troller), which is the “brain” that allows the robot to be net-worked to other systems for integration with other processesand robots. Many robots are robotic arms designed in variousshapes and sizes. The arm is situated such that the end-effector(“hand”) and sensors can perform the preprogrammed task.The robotic arm may resemble human arms with componentssuch as shoulders, elbows, wrists, and even fingers. This de-sign, which is based on human anthropometrics, allows therobot to be positioned in a variety of ways in the workspace.Each joint having 1 degree of freedom implies that a simplerobotic arm with 3 degrees of freedom may move in threeways: left and right, forward and backward, and up anddown. Most working robots have 6 degrees of freedom thatare adequate to perform basic tasks through arbitrary posi-tioning and orientation of the end-effector. The end-effector isconnected to the robot’s arm and ultimately performs thepreprogrammed task; it may be a tool such as a probe, endo-scope, or retractor. Sensors provide feedback so that the robotmay safely perform the task. These sensors also relay spatialinformation back to the controller, informing the computerregarding of the exact location of the robot in the environment.The actuator is the engine that powers the sections betweenthe joints to their desired positions. Most actuators are pow-ered by hydraulics, air, and/or electricity.

To understand the potential impact of robotics in neurosur-gery, it is important to understand the relevant key differencesbetween humans and machines (Table 2). The main advan-tages of robots come from their ability to use abundant, de-tailed, quantitative information to perform accurate, repetitivemotions and to operate in environments inhospitable or inac-cessible to humans (especially through telesurgery and super-visory control). However, they have very limited decision-making and qualitative judgment ability. Conversely, humansare superior at integrating diverse sources of information,using qualitative data, and exercising judgment. Humans alsohave superior dexterity and robust hand–eye coordination,although at a limited scale, and most importantly an exquisitesensation of touch. These crucial differences in capabilitiesimply that current surgical robotic systems are restricted tobasic tasks, with the surgeon providing detailed preoperative

TABLE 1. Advantages of robotic surgery system overcomputer-assisted surgerya

Accurate and predictable, predefined and reprogrammablecomplex 3-D path

Both have accuracy and repeatability to position and orientateat a reprogrammable point, with robot accuracy higher

Ability for repetitive motions, for long periods

Moves to a location and then holds tools for long periodsaccurately, rigidly, and without tremor

Actively constrains tools to particular path or location, evenagainst externally imposed forces, thus preventing vital organdamage

Responds and adapts quickly and automatically to sensorsignals or to a change in commands

Ability for precise micromotions with prespecified microforces

a Modified from Davies B: A review of robotics in surgery. Proc Inst MechEng [H] 214:129–140, 2000 (19).

NATHOO ET AL.

422 | VOLUME 56 | NUMBER 3 | MARCH 2005 www.neurosurgery-online.com

commands or exact move-for-move instructions to completethe preprogrammed task.

The current function of surgical robots is, therefore, to assistthe surgeon under his or her supervision and to extend orenhance human skill rather than to replace the surgeon. Theserobotic systems enhance the practice of surgery by allowingthe surgeon to operate at a very small scale (microsurgery) orthrough very limited access (minimally invasive surgery), toperform highly accurate and repeatable manipulation (stereo-tactic surgery), or to perform surgery with the use of largeamounts of quantitative information (image-guided surgery).The versatility of robots means that these systems have mul-tiple applications in the medical field.

Technical Classifications

From a technological viewpoint, use of robotics in surgicalapplications comprises passive or active effector systems. Apassive mechanism is one in which the surgeon provides thephysical energy to drive the surgical tool; the robot, oncepositioned, acts as a means of holding fixtures at a predestinedlocation to facilitate the precise acquisition of the preopera-tively defined target. In this way, the “powered off” surgicalrobot, locked into position, can be used in a safe manner. Theearliest application of a surgical robot was used in this manner(39).

In active robotic systems, a powered robot actively interactswith a patient, therefore allowing more complex motion to beaccomplished. This robotic system has greater autonomy andthe surgeon has the ability to monitor the entire process andintervene as necessary. An intrinsically safe design is a mech-anism that has physically restricted motion so that all possiblemotions are safe; however, software problems or incorrect usemay override an intrinsically safe mechanism (13).

Interaction Classifications

Surgical robots can be classified into three broad categorieson the basis of how the surgeon interacts with them. Insupervisory-controlled systems, the surgeon plans the opera-tion off line and implicitly or explicitly specifies the motionsthe robot must follow to perform the operation (Fig. 1A). Therobot then performs the specified motions autonomously un-der the supervision of the surgeon.

In telesurgical systems, the surgical manipulator is underdirect control of the surgeon with the surgical tools in the formof a robotic manipulator (Fig. 1B). With an on-line input devicethat is typically a force feedback joystick (master), the surgeonperforms the surgical manipulations, and the surgical manip-ulator (“slave”) faithfully follows the motions of the inputdevice in a master–slave control manner to perform the oper-ation (16, 17, 56).

In shared-control systems, the surgeon and robot share con-trol of the surgical instrument (Fig. 1C) (3, 58). In these syn-ergistic systems, the surgeon remains in control of the proce-dure and the robot provides steady-hand manipulation of theinstrument.

Dexterity Enhancers

Given the current limitations of robotic technology, the mainfocus of medical robotics technology development has been in-tegrating the abilities of human and robot to enhance the sur-geon’s manipulative capabilities at the microscopic scale andimproving the access to areas of the brain that are traditionallydifficult to access, rather than developing robotic systems thatwould be aimed to replace the surgeon (Fig. 2). Technologydesigned to increase the precision of the surgeon’s hands to thelevel enabled by microscopy is termed dexterity enhancement. Thiscan be achieved with a telesurgical or shared-controlled surgical

TABLE 2. Differences between humans and robotsa

Humans Robots

StrengthsStrong hand–eye coordination Good geometric accuracyDexterous (at human scale) Stable and untiring with repeatabilityFlexible and adaptable Designed for wide range of scales, motion scaling with potential future applications for

micro- and nanosurgeryAble to use qualitative information Integrates extensive and diverse informationGood judgment Uses diverse sensors (chemical, force, acoustic, etc.) in control

LimitationsLimited dexterity outside natural state Limited dexterity and hand–eye coordinationProne to tremor and fatigue Poor qualitative decision-making abilityLimited ability to use quantitative information Limited to relatively simple tasksLimited sterility and prone to error Large operating room space requirement,

expensive, technology in flux

a Adapted from Howe RD, Matsuoka Y: Robotics for surgery. Annu Rev Biomed Eng 1:211–240, 1999 (34).

IN TOUCH WITH ROBOTICS


robotic system. A computer-controlled mechanism isplaced between the surgeon’shand and the tip of the surgicalinstrument. This allows thesurgeon’s motions to be re-layed to a computer processor,which digitizes his or her handmotions. The surgeon’s handmotions in a digital format arethen precisely manipulatedand filtered by the system’ssoftware to remove surgicaltremor and to scale downgross macroscopic movementsto a microscopic scale (scale ofmotion) inside the patient,thus enhancing dexterity.

ROBOTS IN OTHERSURGICAL DICIPLINES

Intracranial neurosurgicalprocedures were the focus ofthe first robotic systems, partlybecause a high degree of pre-cision was required for local-ization and manipulationwithin the brain and becausethe cranial anatomy providedrelatively fixed landmarks.Use of medical robots then ex-panded to other fields and hasbeen applied in several othersurgical disciplines. Davies(19) was the first to use an ac-tive motion robot for soft tis-sue surgery in early 1991; thiswas the forerunner to the Pro-bot, which is used currently fortransurethral resection of theprostate (47). In late 1991, Ro-bodoc (Integrated SurgicalSystems, Davis, CA) (5) under-went clinical evaluation in hu-mans. The Robodoc systemprepares the proximal femurto accept an uncemented totalhip prosthesis. The cavity itcreates is 10 times more accu-rate than that achieved viamanual reaming (56).

In 1994, the United StatesFood and Drug Administra-tion approved the first robotfor clinical use in the abdo-

FIGURE 1. Technical classificationof robotic systems: A, supervisorycontrolled system, in which the sur-geon plans the operation off line andthe robot performs the specified mo-tions autonomously under the super-vision of the surgeon. B, telesurgicalsystem, in which the robot is underdirect control of the surgeon with anon-line input device, which is typicallya force feedback joystick (master) thatperforms the manipulations with thesurgical manipulator (slave), faith-fully following the motions of the in-put device in a master–slave controlmanner to perform the operation. C,shared control system, in which therobot and surgeon share control of thesurgical instrument.

NATHOO ET AL.


men. Modified from a robotic arm used by NASA in the spaceprogram, the Automated Endoscopic System for Optimal Po-sitioning (AESOP) (Intuitive Surgical, Inc., Sunnyvale, CA)was developed to hold a laparoscopic camera. A voice-activated version of AESOP was developed later. AESOP hasfacilitated solo-surgeon laparoscopic procedures in generalsurgery (24).

In 1994, the first telesurgical robot was developed by SRIInternational, Inc. (Menlo Park, CA) (32). It was a demonstra-tion developed under a contract for the United States DefenseAdvanced Research Projects Agency to demonstrate the fea-sibility of remote telesurgery. The initial system was devel-oped for open abdominal surgery. Subsequently, a laparo-scopic version was designed.

The Zeus (Intuitive Surgical, Inc.) (38, 50) and daVinci (In-tuitive Surgical, Inc.) (14, 44) robotic systems have been suc-cessfully used in cardiac surgery. Recently, the United StatesFood and Drug Administration approved the Zeus roboticsystem for limited clinical application in chest and abdominalsurgery and the daVinci system for mitral valve repairsurgery.

THE STATUS OF ROBOTSIN NEUROSURGERY

A brief review of pioneering developments in intracraniallocalization is appropriate at this point before the develop-ments in robotic neurosurgery are discussed. Advancement tothe concept of intracranial navigation began with initial ster-eotaxy, i.e., point localization, and progressed to the conceptof volume stereotaxy, opening a new era for neurosurgeons towork through narrow but safe functional corridors and gainaccess to deep lesions (37). Three concurrent technologicaladvances established a foundation for the transition fromframe-based to frameless stereotaxy: improved spatial fidelity

of volume imaging data, rapidly expanding computationalpower, and the development of accurate 3-D digitizers (36,62). This gave rise to a number of different concepts related todigitizers and image display (6, 20, 27, 48, 54). The consolida-tion of these technologies resulted in the commercial develop-ment of image guidance systems that have widely influencedmost aspects of current neurosurgical practice.

Robotization of neurosurgical procedures was the next log-ical step. A large technology base existed in robotic research,derived mainly from experience in the industrial sector. Thisfacilitated the transformation of industrial robots to medicalrobots. Kelly (36), who first described the application of CASin neurosurgery, introduced a Cartesian robot for positioningthe head within the Compass stereotactic head frame (Com-pass International, Rochester, MN) (35). The integration ofrobotic technology into the neurosurgical operating room ad-vanced significantly with the adaptation of industrial robots toperform simple stereotactic tasks. The first recorded medicalapplication of a robot occurred in 1985, when Kwoh et al. (39)used a modified Puma 560 industrial robot (Advance Research& Robotics, Oxford, CT) to define the trajectory of a frame-based brain biopsy. After input of the x-y coordinates of animage-identified intracranial lesion, the robotic effector armwith the probe holder moved to the defined location. Whenthe probe holder reached the target coordinates, the robot waslocked in position and the power removed, making it effec-tively a passive system. The surgeon then used the probe as aguide for drilling the bone and biopsy of the lesion. Unfortu-nately, safety protocols dictated that industrial robots wererequired to operate inside a cage, away from people. Conse-quently, this work was discontinued. Drake et al. (21) laterused a modified industrial robot to resect deep benign astro-cytomas in a small series of patients.

Development of robotic instrumentation specifically de-signed for operative tasks was the focus of both the Grenobleteam led by Benabid et al. (7, 9–11) and the Minerva project inLausanne (26). Minerva was designed to meet exacting spec-ifications incorporating safety, geometry, and to perform sin-gle dimensional incursions into the brain while the patientwas within a computed tomography system that continuouslyprovided real-time imaging data to the robot. This project wasdiscontinued in 1993.

The merging of the roboticized microscope holder devel-oped in Grenoble (Dee-Med, Grenoble, France) with framelessco-registration methodology produced the SurgiScope stereo-tactic system (Elektra AB, Stockholm, Sweden) (10, 42, 51). TheMKM microscope system (Carl Zeiss, Inc., Oberkochen, Ger-many) (49, 63) and the telerobotic system described by Giorgiet al. (25) are similar robotic devices.

In 1990, Adler et al. (1) described an innovative approach toradiosurgery. They used a mechanically precise robot deliverysystem to manipulate a lightweight X-band linear acceleratoras it delivered closed-cranium (or body) radiation of a targetvolume identified with preoperative imaging. This system hasbeen successfully integrated into standard clinical neurosur-gical practice for the treatment of central nervous system

FIGURE 2. Dexterity enhancement: The surgeon’s hand motions are digi-tized, precisely manipulated, and filtered to remove physiological tremorand/or to scale down gross macroscopic movements to a microscopic scale(motion scaling) inside the patient, thus enhancing dexterity.



tumors. Unlike frame-based systems, the CyberKnife (Ac-curay, Inc., Sunnyvale, CA) is noninvasive and compensatesfor limited movement of the target.

NeuroMate (Integrated Surgical Systems) is the first UnitedStates Food and Drug Administration-approved, commer-cially available, image-guided, robotic-assisted system usedfor stereotactic procedures in neurosurgery. This six-axis robotevolved from the work of Benabid et al. (7) at Grenoble Uni-versity. The current version has been modified from the orig-inal design to incorporate specific stereotactic requirementsand to improve safety issues (8). The application accuracy ofthis device is comparable to frame-based or infrared trackinglocalized systems (41) and has been successfully used in aframeless mode for movement disorder surgery (61).

As the brain is best visualized with magnetic resonanceimaging (MRI), robotic systems compatible to work in thisenvironment have been developed. Rather than modifying apreexisting industrial robot, Masamune et al. (43) designed anMRI-compatible robot based on safety and compactness at theUniversity of Tokyo.

Recent, preliminary experience with a robot-assisted,navigation-guided neuroendoscope (66) and robot-assistedthoracoscopic resection of a benign mediastinal tumor (52) hasbeen reported. The use of teleoperated micromanipulators in amaster-slave relationship has been demonstrated in laboratorysettings (28, 33, 40). The NeuRobot telerobotic micromanipu-lator has been used successfully to perform an endoscopicthird ventriculostomy and dissection of the sylvian fissure ina cadaveric specimen (33) and more recently has been used ina limited fashion in the clinical setting of tumor resection (28).

TECHNICAL ANDIMPLEMENTATION CHALLENGES

When an intracranial lesion is encountered for the first time,a surgeon attempts to understand its identity better by accru-ing information with regard to its size, location, boundaries,and neighboring structures. Its identity usually is deducedfrom clinical examination, preoperative neuroimaging, andin-depth knowledge of 3-D anatomy. These factors, coupledwith surgical experience, manual dexterity, and hand–eye co-ordination determine the intraoperative actions of the sur-geon. For robotic systems to perform this form of intellectualfunctioning autonomously in a complex 3-D environment,they must use quantitative reasoning and broad-based sen-sory integration derived from multiple sources (e.g., stereo-scopic vision, kinesthesia). This is not possible with existingtechnology, however, as it requires a quantum leap in alliedtranslational disciplines such as computer sciences, nanotech-nology, biosensor technology, machine intelligence, and ro-botics. For this reason, robots are unlikely to replace surgeonsin the foreseeable future.

Despite their obvious benefits, surgical robotic systems arestill a long way from wide acceptance and use in neurosurgi-cal practice. The high cost of the currently available systems,

poor human-to-machine interface, lack of portability, undesir-able ergonomics, and most importantly, their isolation fromclinical reality limits robot integration into mainstream neu-rosurgical practice. In this section, we discuss the technicalresearch challenges and advanced computer paradigms thatwill improve technology of current surgical robotic systems.

Human–Machine Interface Issues and Machine Haptics

There are a number of human–machine interface problemswith current medical robotic systems that require develop-ment of interface technologies to match and complement hu-man abilities to the surgical tasks (59). Existing manual instru-ments for minimally invasive surgery significantly reducedexterity and impair sensation. They also limit force sensingwith near complete removal of tactile sensation. Current ro-botic telesurgical systems are targeted at improving the dex-terity of surgical manipulation by increasing the motiondegrees-of-freedom available in instruments and providinguser interfaces that improve hand–eye coordination.

Despite being precise and tremor-free in the execution oftasks, current surgical robotic systems lack one crucial at-tribute that surgeons prize: the delicate sense of touch. Be itthe splitting of a sulcus or suturing, tactile sensation and forcefeedback is key to the success of these complex surgical tasks.Important tactile display modalities that need incorporationinto future robotic systems include vibrotactile feedback andthermal sensors. Some studies have explored improving forceand tactile sensation in telesurgical and other medical roboticsystems (15, 29). For force feedback, improvements must bemade in sensor technology, e.g., scaling down the size of forcesensors to fit at the tip of surgical instruments yet maintaininghigh precision and low measurement noise. For efficient tactilefeedback, small sensor arrays are available that can easily fiton surgical instruments, but the currently available displaysare quite bulky. The new compliant tactile display technologythat uses hybrid pneumatic/electric actuation promises signif-icant improvements (45). There remains significant room forimproving dexterity enhancement with surgical robotic tools.Experiments that analyzed the task completion times of sur-geons performing point-to-point or basic manipulation tasks(not outcomes) have demonstrated that robotic telesurgicaltools is still far from reproducing human manual dexteritywith conventional surgical instruments (12, 22).

3-D spatial navigation, planning, and visual-spatial coordi-nation form another set of major problems in robotic surgery,as they do in image-guided surgery. This set of human–ma-chine interface problems is the result of complex and unfamil-iar spatial transformations in image-guided surgery involvingthe surgeon’s visual and haptic perception. Solutions to theseproblems require design of intuitive interfaces for use duringsurgical manipulation, especially for robotic surgery, and de-velopment of training strategies and tools to teach surgeons tointerpret, understand, and handle the complex spatial inter-face. Use of virtual reality training simulators with haptic

NATHOO ET AL.


feedback provides a promising paradigm to teach these com-plex spatial cognitive skills (55, 60).

Soft Tissue Surgery and Deformability

In the realm of soft tissue surgery, robots must adapt to thedeformability and mobility of the operated brain, and othersoft tissue. Therefore, undue reliance of a surgical plan basedexclusively on preoperative data acquisition is unsatisfactory.The complex behavior of soft tissues may be accurately deter-mined via indentation, imaging, boundary condition methods,and mathematical modeling. There are two major approachesto address this problem.

The first approach is to use interventional imaging systemsin conjunction with surgical robots. In this paradigm, a pre-operative plan is constructed with high-resolution preopera-tive images and downloaded to the surgical robot in theoperating room. The operation is performed within an inter-ventional imaging system that acquires near- or real-time im-ages, processes them, identifies the tissue deformations, andsubsequently modifies the surgical plan on line, taking intoaccount the changing surgical scenario as a result of soft tissuedeformations. The most promising interventional imagingsystems for intraoperational robotic assistance are MRI, com-puted tomography, and ultrasound imaging. The main diffi-culty with MRI and computed tomography relates to compat-ibility of the surgical robot with the imaging system. Forexample, a robot that will be used for performing roboticsurgery inside an interventional MRI system must be made ofmaterials that are not affected by the large magnetic gradients,and it should not interfere with operation of the MRI systemor reduce image quality (18). This poses significant challengesin the choice of structural materials, actuators, and sensorsand the design of the size and location of the system (23).Robotic image-guided surgery under ultrasound guidance isattracting attention because of the relatively low cost and wideavailability of these systems. However, the low image resolu-tion of ultrasound systems has proved to be a formidablechallenge.

The second approach to handle soft tissue deformationsduring robotic surgery is to model and estimate induced softtissue deformations during simulated surgical manipulationand compensate for its effects during the construction of thesurgical plan. The major challenge in this approach is theprediction of the mechanical behavior of brain tissue, espe-cially as the biomechanical properties are difficult to predictand highly variable under intraoperative conditions.

A technological spin-off from the NASA smart probe projectis the development of multimodality stereotactic brain tissueidentification by use of advanced information technology suchas neural networking (2). The probe uses multiple microsen-sors, such as optical spectroscopy, microelectrode recordings,micro-blood flow dynamics, and microendoscopy to gatherlarge amounts of data regarding the tissue at the probes tip inreal time, thereby determining the nature of the tissue.

Safety

Safety is of paramount concern with robotic surgery andrequires that rigorous, mandatory preclinical testing be under-taken before clinical application. Two major concerns of safetyin medical robotic systems are the potential hazards to thepatient as a result of failure and unintended actions by therobot and the safety of the surgical team that occupies thespace around the patient and the robot. Although there are nouniversally accepted techniques to guarantee system safetyunder all circumstances, there are several general approachesfor achieving hardware safety (34, 46).

Redundancy in kinematics and sensors is a very commontechnique used in surgical robots to improve system safety.This methodology is very effective in detecting and recoveringfrom partial system failures, and has the potential to performconsistency checks to evaluate the integrity of the hardware.However, it should be noted that redundancy also increaseshardware and software complexity, which increases fragilityof the system overall and makes the design more costly (57).

Another common approach to improve safety of surgicalrobotic systems is to limit the size of the workspace of therobot to avoid potential unintended damage to areas outsidethe point of operation, use less powerful actuators, and com-bine active and passive mechanisms in the robot design (30,53). There are two approaches to limiting the robot workspace.Either the surgeon moves the tool and the robot preventsmotion outside the planned workspace, or, as with the Ro-bodoc hip replacement system, the robot moves the cuttingtool autonomously and the surgeon monitors the progress.Current clinical trials from Europe indicate clinician accep-tance of this autonomous mode (5). As medical robotic useincreases, surgeons will grow more accustomed to autono-mously controlled robotic systems. Another important con-cern in surgical robotic system safety is sterilization. This isusually achieved by covering the entire surgical robot, withthe exception of the surgical end-effector, with sterile drapes.The surgical end-effector, which is the part that is used on thepatient, is sterile and reusable.

FUTURE SURGICAL ROBOTS

Despite a half-century of advancements in robotic technol-ogy, the capabilities of current systems remain limited. Themechanical robots of popular culture, although built to look,act, and emote like humans, are much different from contem-porary surgical robotic systems in appearance and behavior.Robotic systems still have great difficulty identifying objectson the basis of visual appearance or feel and they handleobjects clumsily, so they are far from ready to perform com-plex tasks such as surgery on the brain autonomously (otherthan as extensions of stereotactic surgery).

Almost all robots are preprogrammed by people and willonly perform programmed tasks. In the future, it is likely thatcontrollers with artificial intelligence (AI) will allow robots to“think” on their own or even program themselves, thereby



making them more self-reliant and independent. No computerhas gained the level of AI that comes close to simulatingcomplex human behavior and thinking. The highest form ofAI to date was demonstrated recently when the Deep Bluesupercomputer (International Business Machines Corp.) beatthe world chess champion, Gary Kasparov, in 1997.

For surgical robots to gain acceptance by neurosurgeons,they must possess qualities that will enhance the surgeon’smanipulative capabilities and do so in a robust, user-friendlymanner that is neither obstructive nor restrictive. In this sec-tion, we review some advanced technological paradigms thatwill provide the foundation for future surgical robotic systemsto interact with surgeons in a seamless manner.

Machine/AI and Surgical Robots

AI has been one of the most controversial domains of in-quiry in computer science since it was first proposed in the1950s. Defined as “the scientific understanding of the mecha-nisms underlying thought and intelligent behavior and theirembodiment in machines” (American Association for Artifi-cial Intelligence [68]), AI has, unbeknownst to many, becomepart of our daily lives. AI integral to a swath of industries, e.g.,assisting engineers to create better jet engines, boosting pro-ductivity through the use of monitoring equipment and sig-naling when preventive maintenance is needed, and assistingthe Pentagon in coordinating its immense logistic operations.In the biotechnology sector, AI has been used to gain newinsight into the human genome. Improvement of existingmachine/AI applications will contribute to improvements incurrent surgical robot systems.

Artificial Sensory Modalities

For meaningful interaction between the robot and surgeon,perceptual abilities should overlap so that the each has an ideaof the sensations and responses of the other. Under idealcircumstances, natural language processing will allow peopleto interact with computers without additional specializedknowledge, but this has proved difficult thus far. Althoughrudimentary translation systems are available, they are far lesscapable than human translators. Voice recognition systemsthat convert spoken sounds to written words are currentlyavailable, although these systems do not understand whatthey have written.

Two-dimensional inputs to the human eye are rendered in3-D and interpreted by the brain. To achieve this functionartificially by use of computer vision, the computer must gaininformation regarding the spatial properties of the environ-ment, i.e., shape, motion, distances, and angles. These aremeasurable properties that can only be obtained as imageschange with time. Therefore, either multiple views from thescene are needed, or the viewer’s perspective must change.Only then can a 3-D representation be created. With currentcomputer vision, it is only possible to infer and understand3-D information from images in a limited fashion that is farinferior to human vision. Assimilation and sequential compi-

lation of multiple external sensory sources eventually willtransform current rudimentary robotic systems from accu-rately programmed sequences of motions in a structured en-vironment to dynamic behaviors planned in response to theexternal world.

Artificial Thought Processing

Expert Systems and Heuristic Planning

Expert systems are computer applications designed to re-place and/or aid humans by performing tasks that wouldotherwise be performed by a human expert (e.g., financialforecasts, diagnosis of human illnesses). In this computationalmodel, a “knowledge engineer” interviews experts in variousdomains and attempts to embody their knowledge in a com-puter program for performing each task. Heuristic planninguses commonsense rules drawn from experience to solveproblems, in contrast to algorithmic programming, which isbased on mathematical models. These programs are self-learning and their performance improves with experience.Most expert systems use heuristics.

Artificial Neural Networks

One of the most active areas of AI is neural networks. Anartificial neural network is an information-processing para-digm conceived to process information similar to the denselyinterconnected parallel structure of the mammalian brain. Anartificial neural network is simply a collection of mathematicalmodels that mimic some of the observed properties in biolog-ical nervous systems and possess analogous adaptive biolog-ical learning. The information processing system is composedof large numbers of highly interconnected processing ele-ments that are analogous to neurons and are tied togetherwith weighted connections that are analogous to synapses.Similar to biological systems, learning typically occurs byexample through training or exposure to a correct set ofinput/output data wherein the training algorithm autono-mously adjusts the connection weights (synapses). These con-nection weights store the knowledge necessary to solve spe-cific problems. Neural networks have become the standard fordetecting credit card fraud in the financial sector.

The advantage of artificial neural networks is their resis-tance against distortions to the input data and their capabili-ties of learning and problem solving capabilities for conven-tional technologies. There is developing interest in how neuralnetwork research and neurophysiology can merge; a fieldcalled computational neuroscience has been conceived from bothdisciplines.

Fuzzy Logic

Another computational paradigm of thought processing isfuzzy logic, which uses a problem-solving control system meth-odology that provides a simple way to arrive at a definite con-clusion based upon vague, ambiguous, imprecise, noisy, or miss-ing information. Fuzzy logic , which was introduced in 1960s

NATHOO ET AL.


(64), incorporates a unique type of rule-based mathematicalmodeling and uses the “if x and y, then z” approach to solvingproblems (65) with a superset of conventional Boolean logic thathas been designed to handle partial truth. It provides a frame-work to perform computation and mathematically represent thevague and imprecise nature of rules and information expressedwith natural language, and it handles ambiguous and noisyinformation to mimic the way a human makes decisions.

CONCLUSION

Despite its debut more than 15 years ago, medical robotictechnology has yet to gain prominence in neurosurgery.Achievement of this goal is probably a matter of time. We lookforward to the development of MRI-compatible robotic devices

that will have ambidextrouscapabilities with persistence(i.e., ability to pick up wherethe surgeon has left off), mul-tiple degrees of freedom, highbandwidth, and kinestheticfeedback yet are robust anduser-friendly devices. Roboticswill result in improved surgi-cal techniques and facilitatethe development of new pro-cedures that could not be per-formed without the aid of thisnew class of tools. Undoubt-edly, robotic technology is setto transform future neurosur-gical practice (Fig. 3).

Convincing neurosurgeonsand patients regarding robotsafety may prove to be the big-gest challenge to their imple-mentation. It seems that robotswill initially be more accept-able to the surgeon if the phy-sician is in control of the entiresurgical procedure, with therobot acting primarily as adexterity enhancer (robot-assisted procedure). As robotictechniques become more inte-grated into practice, neurosur-geons should become familiarwith this new interdisciplinaryfield termed neurorobotics (i.e.,robotics applied to neurosur-gery). Awareness of this tech-nology is mandatory if we areto have a solid working foun-dation to handle the currentand future needs of neurosur-gical practice.

The integration of disciplines such as information technol-ogy, robotics, machine intelligence, nanotechnology, and so-phisticated computational networking may revolutionize con-temporary neurosurgical practice, thereby generating manypotential new clinical applications. To ensure the broad appli-cation of robots to medicine and neurosurgery, a new era ofcollaboration and cooperation between surgeons and roboticsscientists is necessary to drive this technological tour de force.However, factors such as cost and safety concerns undoubt-edly will affect the incorporation of robotics into conventionalneurosurgical practice. It will become imperative that resi-dents and neurosurgeons become familiar with this form oftechnology so they can incorporate it into their future surgicalarmamentarium and, it is hoped, improve the quality of pa-tient care. Because the general abilities of a robot and surgeon

FIGURE 3. Brain operating room and surgical robots in the near future. The surgeon, wearing a lightweight head-mounted visor with virtual retinal display technology, sits in a surgical cockpit, with capabilities of dexterityenhancement. An operating table, modular in design, incorporates rigid head fixation, intraoperative MRI, and asurgical robot with two end-effectors. Surgical visualization instruments (microscope and endoscope) will be coupledbut optically delinked, with stereoscopic magnified images of the operative field integrated and fused with the multi-ple real-time image data sets defining the anatomic and functional substrates as appropriate.



are dissimilar yet complementary, great synergy may be gen-erated by combining the two with potential benefit to human-kind, medicine, and neurosurgery.

REFERENCES

1. Adler JR Jr, Murphy MJ, Chang SD, Hancock SL: Image-guided roboticradiosurgery. Neurosurgery 44:1299–1307, 1999.

2. Andrews R, Mah R, Aghevli A, Freitas K, Galvagni A, Guerrero M, PapasinR, Reed C, Stassinopoulos D: Multimodality stereotactic brain tissue iden-tification: The NASA smart probe project. Stereotact Funct Neurosurg 73:1–8, 1999.

3. Ang WT, Riviere CN, Khosla PK: An active hand-held instrument forenhanced microsurgical accuracy, in Delp SL, Digioia AM, Jaramaz B (eds):Medical Image Computing and Computer-assisted Intervention–MICCAI 2000:Third International Conference, Pittsburgh, PA, USA, October 2000 Proceedings.New York, Springer, 2000, pp 878–886.

4. Apuzzo MLJ: In the realm of ideas: The advent of advanced surgery of thehuman cerebrum and neurosurgical education. Acta Neurochir Suppl(Wien) 69:145–150, 1997.

5. Bargar WL, Bauer A, Borner M: Primary and revision total hip replacementusing the Robodoc system. Clin Orthop 354:82–91, 1998.

6. Barnett GH, Komos DW, Steiner CP, Weisenberger J: Intraoperative local-ization using an armless, frameless stereotactic wand. Neurosurgery 33:674–678, 1993.

7. Benabid AL, Cinquin P, Lavallée S, Le Bas JF, Demongeot J, Rougemont J:Computer driven robot for stereotactic surgery connected to CT scan andmagnetic resonance imaging: Technological design and preliminary results.Appl Neurophysiol 50:153–154, 1987.

8. Benabid AL, Hoffman D, Ashraff A, Koudsie A, Le Bas JF: Robotic guidancein advanced imaging environments, in Alexander E III, Maciunas RJ (eds):Advanced Neurosurgical Navigation. New York, Thieme Medical Publishers,Inc., 1999, pp 571–583.

9. Benabid AL, Hoffman D, Munari C, Lavallée S, Cinquin P, Demongeot J, LeBas JF, Danel F: Is there a future for robots in neurosurgery? in Symon L(ed): Advances and Technical Standards in Neurosurgery. Wien, Springer, 1991,pp 3–45.

10. Benabid AL, Hoffman D, Munari C, Le Bas JF: Surgical robots, in Cohen AR,Haines SJ (eds): Minimally Invasive Techniques in Neurosurgery. Baltimore,Williams & Wilkins, 1995, pp 85–97.

11. Benabid AL, Lavallee S, Hoffmann D, Cinquin P, Demongeot J, Danel F:Potential use of robots in endoscopic neurosurgery. Acta Neurochir Suppl(Wien) 54:93–97, 1992.

12. Bowersox JC, Cornum RL: Remote operative urology using a surgicaltelemanipulator system: Preliminary observations. Urology 52:17–22, 1998.

13. Buckingham RA, Buckingham RO: Robots in operating theatres. BMJ 311:1479–1482, 1995.

14. Carpentier A, Louimel D, Aupacie B, Reliand J: Computer-assisted cardiacsurgery. Lancet 353:379–380, 1999 (letter).

15. Cavusoglu MC, Sherman A, Tendick F: Design of bilateral teleoperationcontrollers for haptic exploration and telemanipulation of soft environ-ments. IEEE Trans Rob Autom 18:641–647, 2002.

16. Cavusoglu MC, Tendick F, Cohn M, Sastry SS: A laparoscopic telesurgicalworkstation. IEEE Trans Rob Autom 15:728–739, 1999.

17. Cavusoglu MC, Williams W, Tendick F, Sastry SS: Robotics for telesurgery:Second generation Berkeley/UCSF laparoscopic telesurgical workstationand looking towards the future applications—Special issue on medicalrobotics. Ind Rob 30:22–29, 2003.

18. Chinzei K, Hata N, Jolesz FA, Kikinis R: MR Compatible surgical assistrobot: System integration and preliminary feasibility study, in Medical ImageComputing and Computer-assisted Intervention–MICCAI 2000: Third Interna-tional Conference, Pittsburgh, PA, USA, October 2000 Proceedings. New York,Springer, 2000.

19. Davies B: A review of robotics in surgery. Proc Inst Mech Eng [H] 214:129–140, 2000.

20. Doshi PK, Lemieux L, Fish DR, Shorvon SD, Harkness WH, Thomas DG:Frameless stereotaxy and interactive neurosurgery with the ISG viewingwand. Acta Neurochir Suppl (Wien) 64:49–53, 1995.

21. Drake JM, Joy M, Goldenberg A, Kreindler D: Computer and robot-assistedresection of thalamic astrocytomas in children. Neurosurgery 29:27–31,1991.

22. Garcia-Ruiz A, Gagner M, Miller JH, Steiner CP, Hahn JF: Manual versusrobotically assisted laparoscopic surgery in the performance of basic ma-nipulation and suturing tasks. Arch Surg 133:957–961, 1998.

23. GE Medical Systems: MR safety and MR compatibility: Test guidelines forSigna SPTM—1997. Available at: http://www.gemedicalsystems.com/rad/mri/pdf/safety1.pdf. Accessed December 15, 2004.

24. Geis WP, Kim HC, Brennan EJ Jr, McAfee PC, Wang Y: Robotic armenhancement to accommodate improved efficiency and decreased resourceutilization in complex minimally invasive surgery procedures. Stud HealthTechnol Inform 29:471–481, 1996.

25. Giorgi C, Eisenberg H, Costi G, Gallo E, Garibotto G, Casolino DS: Robot-assisted microscope for neurosurgery. J Image Guid Surg 1:158–163, 1995.

26. Glauser D, Fankhauser H, Epitaux M, Hefti JL, Jaccottet A: Neurosurgicalrobot Minerva: First results and current developments. J Image Guid Surg1:266–272, 1995.

27. Golfinos JG, Fitzpatrick BC, Smith LR, Spetzler RF: Clinical use of a frame-less stereotactic arm: Results in 325 cases. J Neurosurg 83:197–205, 1995.

28. Goto T, Hongo K, Kakizawa Y, Muraoka H, Miyairi Y, Tanaka Y, KobayashiS: Clinical application of robotic telemanipulator system in neurosurgery.J Neurosurg 99:1082–1084, 2003.

29. Gray BL, Fearing RS: A surface micromachined microtactile sensor array.Presented at the IEEE International Conference on Robotics and Automa-tion, Minneapolis, April, 1996.

30. Harris SJ, Arambula-Cosio F, Mei Q, Hibberd RD, Davies BL, Wickham JE,Nathan MS, Kundu B: The Prorobot: An active robot for prostate resection.Proc Inst Mech Eng [H] 211:317–325, 1997.

31. Heilbrun MP, Mcdonald JD: The future of image-guided surgery. ClinNeurosurg 46:89–101, 2000.

32. Hill JW, Green JF, Jensen JS, Gorfu Y, Shah AS: Telepresence surgerydemonstration system, in Proceedings of the IEEE International Conference onIndustrial Technology: Canton, China—1994. Piscataway, IEEE Service Center,1994, pp 2302–2307.

33. Hongo K, Kobayashi S, Kakizawa Y, Goto T, Okudera H, Kan K, Fujie MG,Iseki H, Takakura K: NeuRobot: Telecontrolled micromanipulator systemfor minimally invasive microneurosurgery—Preliminary results. Neuro-surgery 51:985–988, 2002.

34. Howe RD, Matsuoka Y: Robotics for surgery. Annu Rev Biomed Eng1:211–240, 1999.

35. Kall BA, Kelly PJ, Goerss S, Frieder G: Methodology and clinical experiencewith computed tomography and a computer-resident stereotactic atlas.Neurosurgery 17:400–407, 1985.

36. Kelly PJ: Stereotactic surgery: What is past is prologue. Neurosurgery46:16–27, 2000.

37. Kelly PJ, Alker GJ, Goerss S: Computer assisted stereotactic laser microsur-gery for the treatment of intracranial neoplasms. Neurosurgery 10:324–331,1982.

38. Kiaii B, Boyd WD, Rayman R, Dobrowsi WB, Ganapathy S, Jablonsky G,Novick RJ: Robot-assisted computer enhanced closed-chest coronary sur-gery: Preliminary experience using harmonic scalpel and Zeus. Heart SurgForum 3:194–197, 2000.

39. Kwoh YS, Hou J, Jonckheere EA, Hayathi S: A robot with improved absolutepositioning accuracy for stereotactic brain surgery. IEEE Trans Biomed Eng35:153–160, 1988.

40. Le Roux PD, Das H, Esquenazi S, Kelly PJ: Robot-assistedmicroneurosurgery: Feasibility study in the rat. Neurosurgery 48:584–589,2001.

41. Li QH, Zamorano L, Pandaya A, Perez R, Gong J, Diaz F: The applicationaccuracy of the Neuromate robot: A quantitative comparison with framelessand frame-based surgical localization systems. Comput Aided Surg 7:90–98,2002.

42. Marinov M, Roberts D: Interactive image-guided cranial neurosurgery usingthe SurgiScope. Bulg Neurosurg 4:9–18, 1996.

NATHOO ET AL.


43. Masamune K, Kobayashi E, Masutani Y, Suzuki M, Dohi T, Iseki H,Takakura K: Development of an MRI-compatible needle insertion manipu-lator for stereotactic neurosurgery. J Image Guid Surg 1:242–248, 1995.

44. Mohr FW, Falk V, Diegeler A, Walther T, Gummert JF, Bucerius J,Autschbach R: Computer-enhanced “robotic” cardiac surgery: Experience in148 patients. J Thorac Cardiovasc Surg 121:842–885, 2001.

45. Moy G, Wagner C, Fearing RS: A compliant tactile display for teletaction.Presented at the IEEE International Conference on Robotics and Automa-tion, San Francisco, April, 2000.

46. Ng WS, Tan CK: On safety enhancements for medical robots. Reliab EngSyst Saf 54:35–45, 1996.

47. Ng WS, Davies BL, Hibberd RD, Timoney AG: A first hand experience intransurethral resection of the prostate. IEEE Med Bio Soc Magazine 120–125, 1993.

48. Olivier A, Germano IM, Cukiert A, Peters T: Frameless stereotaxy forsurgery of the epilepsies: Preliminary experience. J Neurosurg 81:629–633,1994.

49. Pillay PK: Image-guided stereotactic neurosurgery with the multicoordinatemanipulator microscope. Surg Neurol 47:171–177, 1997.

50. Reichenspurner H, Damiano RJ, Mack M, Boehn DH, Gulbins H, Detter C,Meiser B, Ellgass R, Reichart B: Use of the voice-controlled and computer-assisted surgical system ZEUS for endoscopic coronary artery bypass graft-ing. J Thorac Cardiovasc Surg 118:11–16, 1999.

51. Roberts DW, Darcey TM: The evaluation and image guided surgical treat-ment of the patient with medically retractable seizure disorder, inMarciunas RJ (ed): Clinical Frontiers of Interactive Image Guided Neurosurgery.Philadelphia, W.B. Saunders Co., 1996, pp 215–227.

52. Ruurda JP, Hanlo PW, Hennipman A, Broeders IA: Robot-assisted resectionof a benign mediastinal neurogenic tumor: Technical note. Neurosurgery52:462–464, 2003.

53. Slatkin AB, Burdick J, Grundfest W: The development of the robotic endo-scope, in Khatib O, Salisbury JK (eds): Experimental Robotics IV: The 4thInternational Symposium, Stanford, California, June 30–July 2, 1995. Berlin,Springer-Verlag, 1995, pp 161–169.

54. Smith KR, Frank KJ, Bucholz RD: The NeuroStation: A highly accurate,minimally invasive solution to frameless stereotactic neurosurgery. ComputMed Imaging Graph 18:247–256, 1994.

55. Spicer MA, Apuzzo MLJ: Virtual reality surgery: Neurosurgery and thecontemporary landscape. Neurosurgery 52:489–497, 2003.

56. Stoianovici D: Robotic surgery. World J Urol 18:289–295, 2000.57. Taylor RH, Stoianovici D: Medical robotics in computer integrated surgery.

IEEE Trans Rob Autom 19:765–781, 2003.58. Taylor RH, Jensen P, Whitcomb LL, Barnes A, Kumar R, Stoianovici D,

Gupta P, Wang ZX, de Jauan E, Kavoussi LR: A steady-hand robotic systemfor microsurgical augmentation. Int J Rob Res 18:1201–1210, 1999.

59. Tendick F, Cavusoglu MC: Human machine interfaces for minimally inva-sive surgery, in Proceedings of the 19th Annual International Conference of theIEEE Engineering in Medicine and Biology Society (EMBS’97), Chicago, Illinois,October 30–November 2, 1997. New York, IEEE, 1997, pp 2771–2776.

60. Tendick F, Downes M, Goktekin T, Cavusoglu MC, Feygin D, Wu X, Eyal R,Hegarty M, Way LW: A virtual environment test bed for traininglaparoscopic surgical skills. Presence Teleoper Virtual Environ 9:236–255,2000.

61. Varma TRK, Eldridge PE, Forster A, Fox S, Fletcher N, Steiger M, LittlechildP, Byrne P, Sinnott: Use of a frameless stereotactic robot for movementdisorder surgery. Presented at the 2003 Quadrennial Meeting, AmericanSociety for Stereotactic and Functional Neurosurgery, New York, New York,May 18–21, 2003.

62. Watanabe E, Mayanagi Y, Kosugi Y, Manaka S, Takakura K: Open surgeryassisted by the neuronavigator, a stereotactic, articulated sensitive arm.Neurosurgery 28:792–800, 1991.

63. Wirtz CR, Bonsanto MM, Knauth M, Tronnier VM, Albert FK, Staubert A:Intraoperative magnetic resonance imaging to update interactive navigationin neurosurgery: Method and preliminary experience. Comp Aided Surg2:172–179, 1997.

64. Zadeh L: Fuzzy sets. Information Control 8:338–353, 1965.65. Zadeh L: Outline of a new approach to the analysis of complex systems.

IEEE Trans Syst Man Cybern 3: 28–44, 1973.

66. Zimmerman M, Krishnan R, Raabe A, Seifert V: Robot-assisted navigatedneuroendoscopy. Neurosurgery 51:1446–1452, 2002.

67. http://www.frc.ri.cmu.edu/robotics-faq/1.html#1.1. Accessed 2/4/05.68. http://www.aaai.org. Accessed 2/4/05.

AcknowledgmentsWe thank Martha Tobin (Department of Neurosurgery) for editing the manu-

script and Mark Szabo (Department of Medical Illustration) for designing thefigures. This research was supported in part by Grants CISE IIS-0222743, CISEEIA-0329811, and CISE EIA-0423253 from the National Science Foundation(MCÇ).

COMMENTS

The authors describe the basis of surgical robotics, previousexperience with clinical robotics, and directions for devel-

opment of future robotic applications in neurosurgery. Theyprovide a basic review of robotic terminology and concepts,which are important for modern neurosurgeons to under-stand. Use of robotics in neurosurgery is not simply a passingfad; however, the correct applications must be found for theconcepts outlined in this article to gain practical acceptance.Robotics in neurosurgery has developed on a convergent evo-lutionary path with computer-assisted surgery; the result willbe the merging of these two technologies. Image guidance,coupled with the scaling and dexterity-enhancing propertiesof surgical robotics, will provide for a new era of minimallyinvasive neurosurgery. Robots used in this manner will notreplace neurosurgeons in the operating room, but they willallow us to see and work in places that once required largeexposures. Flexible endoscopes, end-effectors with multipledegrees of freedom, and stereotactic imaging techniques willallow us to see and work in deep locations and around cor-ners, limiting patient morbidity. These concepts are beginningto become reality. Nathoo et al. provide a review of the statusof neurosurgical robotics, but we have a long way to go. Afterthe theoretical ideas are addressed, widespread acceptancewill follow only when the practical concerns of reduced cost,ease of use, and improved clinical outcome are realized.

Lee TesslerPatrick J. KellyNew York, New York

Mirroring general surgery, a number of recent publicationssuggest growing interest among neurosurgeons in the

burgeoning field of robotics. Nathoo et al. provide a relativelythorough overview of the robotic surgical field, which addsfurther to the topical literature. Having personally dedicatedmy professional career to a specific application of operativerobotics, image-guided robotic radiosurgery, I am by naturean enthusiast for this emerging field. However, I have alsoexperienced first-hand the economic realities that enable newsurgical technologies to be developed. Although I agree that itmight be feasible and even advantageous to redesign specifichigh-volume procedures (e.g., in the spine or deep brain stim-ulation) around a dedicated robotic tool, most of the recentemphasis in the neurosurgical robotics literature has been on



conceptualizing a general-purpose robot for performing mi-crosurgery. Despite the theoretical advantages of operatingunder robotic control or with robotic assistance, I remainskeptical that these putative benefits are currently greatenough that companies will make the needed investment.Consequently, I think that for the foreseeable future, much ofthe enthusiasm for microsurgical robots in neurosurgery willremain within the realm of academic speculation.

John R. Adler, Jr.Stanford, California

Nathoo et al. continue their series of reviews of robotics forneurosurgeons. All of us, especially neurosurgeons, love

our machines. We want the newest technological toys in ouroperating rooms to enable us to perform our art faster, better,and safer. We readily embrace technology that extends oursenses, improves our motor control, and speeds up the pro-cedure. Why, then, have robots made so little impact in sur-gery in general and in neurosurgery in particular? The answerlies in Table 7 in the article: there is a risk-to-benefit ratio, andcurrently the risks are simply too large to invest in expensive,bulky equipment that performs a limited number of rathersimple tasks and has poor decision-making capability.

This limited capability hampers progress in this field oftechnology. Far more information must be supplied beforerobots can dramatically evaluate their environment. There is avery good reason why industrial robots are caged and humansmust stay out of their working area: there is no feedback tothese robots that would allow them to stop and prevent aninjury should a human enter their work space. Artificial intel-ligence remains quite limited. Software “glitches” and theinability to correct errors, whether human or robotic in origin,means very slow acceptance of technology until these prob-lems are corrected. Supervisory controlled robotics systems orrobotic telesurgery systems will have a place in the neurosur-gery technology armamentarium in the distant future. Beforethat can be accomplished, it must be proved that the precisionelements that provide the strengths related to the use of robotshave the safety and efficacy necessary to perform surgicalprocedures. A neurosurgery chairman once said that a mon-key can be trained to perform the mechanics required forneurosurgery. It was pointed out later, however, that a humanbeing with a great deal of intelligence, insight, and compas-sion is required to properly apply those mechanics when,where, and how they are needed.

People always have had a love/hate relationship with ro-bots. This psychological barrier must be overcome. Sciencefiction has presented robots as both monsters and saviors.Classic science fiction movies such as Forbidden Planet, The Daythe Earth Stood Still, The Terminator, and Star Wars play into ouremotions regarding robots. Few surgeons and even fewerpatients like the idea of autonomously controlled roboticssystems performing potentially life-and-death procedures. Iam not willing to accept that robots could or should “think”on their own or even program themselves. If one thinks of the

personal computer, it is obvious that computers have a longway to go. Although IBM’s Deep Blue supercomputer wasable to beat world chess champion Gary Kasparov, Deep Bluedoes not always win, and it does not do so by any insight orinnovation in the game of chess; it wins simply by manualcalculation of the odds through possible steps into the future.Computer-assisted surgery has dramatically improved thepractice of stereotactic and functional neurosurgery. However,the neurosurgeon must be the master of technology, as subtleerrors can be introduced into stereotactic neurosurgical pro-cedures extremely easily. The correction of some errors mayrequire a little bit of common sense, but others require con-siderable experience and insight, e.g., the realization that acalculated target or trajectory is incorrect. If robots are everallowed to “think for themselves,” it is hoped that the pro-gramming will incorporate Isaac Asimov’s three laws of ro-botics: 1) a robot may not injure a human being, or, throughinaction, allow a human being to become harmed; 2) a robotmust obey the orders given it by human beings, except wheresuch orders would conflict with the first law; and 3) a robotmust protect its own existence as long as such protection doesnot conflict with the first or second laws. A recently releasedfilm, I, Robot, incorporates a number of Asimov’s ideas but isa story that is foreign to his writings. The plot involves pro-gram glitches that allow these laws to be ignored. I foundmyself sympathizing with the detective played by Will Smith.Who distrusts robots? As a police officer, he instructed a robotto save a child and sacrifice himself. The robot, calculating theprobability of success, “chose” to save Smith’s life against hisinstructions. I, too, will use robots but will never truly trustthem. The problem is that robots will act based on theirprogramming and observations, not on my experience andinsight. Fuzzy logic is a poor match for the brain of an expe-rienced neurosurgeon.

I agree with the authors that surgical robotic systems are along distance from wide acceptance and use in neurosurgicalpractice. Many problems must be overcome before some of thesimpler master-slave interactions can be perfected. We aremuch further away from allowing independent action undersupervision or even shared control. The authors provide areality check to the enthusiasm generally expressed forrobotics.

Roy A.E. BakayChicago, Illinois

Nathoo et al. provide an overview of neurosurgical robot-ics and speculate regarding future developments in the

field. We agree with the authors that the possibilities offeredby robots make their incorporation into the neurosurgicaloperating room inevitable. However, this article overstates theability of current robotic systems in many ways. The authorsdescribe how neurosurgical robots have become more “ac-tive,” progressing from simple guides for stereotactic proce-dures to motion-scaled, tremor-filtered, master-slave systems.The statement that the newer active robots are more autono-

NATHOO ET AL.


mous may not be correct (1). Autonomy implies that the robotperforms a task automatically, i.e., without the control of thesurgeon. Although some systems such as the CyberKnife (Ac-curay, Inc., Sunnyvale, CA) perform tasks automatically, dex-terous master-slave surgical robots are under real-time posi-tion control by the surgeon. The robotic link simply upgradesthe surgeon’s hands, permitting finer motion with a magnifiedsense of touch.

The authors classify robotic systems in three categories onthe basis of how the surgeon interacts with them: supervisory,telesurgical, and shared systems. An example of the sharedconfiguration is the SteadyHand system developed at JohnsHopkins. It does not permit motion scaling, because the sur-geon directly manipulates tools attached to the robot arm. Thestatement that these shared systems are designed to increasethe precision of surgery “to the level enabled by microscopy”is bold if relying on tremor filtering alone, as motion scalingalso must be considered.

The situation is different in teleoperator systems, in whichthe surgeon controls the slave robot through a master devicesuch as a haptic hand controller. Because the link betweenmaster and slave is electronic, it is possible to scale coarsemotion by the surgeon to fine motion by the robot. However,motion and forces cannot be scaled indefinitely because thesystem eventually becomes unstable. Related to stability is theconcept of latency. The transparency of the haptic interface islimited by the amount of time it takes to position informationfrom the master to reach the slave and for force information tobe communicated back to the master. Even with improvedlow-latency communication channels between master andslave, only a handful of long-distance data exchanges persecond are possible, because the signals can travel no fasterthan the speed of light. Therefore, telesurgery to remote loca-tions of the world with high-fidelity haptic feedback may notbe possible.

Nathoo et al. discuss the need for the robotic system toadapt to the deformability and shifting of the brain duringsurgery. This is important: despite knowing the absolute po-sition of the robot end-effector, the location of a lesion maymove relative to the preoperative scan, in which case therelative position between end-effector and lesion is lost. Neu-roArm, a robotic system developed at the University of Cal-gary, will deal with brain-shift by providing near-real-timemagnetic resonance images at the robot workstation on a flatpanel display (2, 3). Alternatively, robotic systems may beused much like they are in contemporary surgery throughimmersion in an electronic visual and haptic environment.

Robotic platforms enable new types of intelligent tools nolonger constrained by the human hand. These may come tofruition long before robots are capable of intelligent, autono-mous thought. The reality of surgical robots as the standard ofcare for neurological disorders is speculative and will requireconsiderable interaction between multiple disciplines includ-ing medicine, engineering, computer science, and physics.There are, however, increasing numbers of people and emerg-ing societies committed to this endeavor. The evolving roboticsystems, especially those with haptics, provide the opportu-nity for virtual surgery. This will be particularly important asmechatrons enter our operating rooms.

Garnette SutherlandPete RizunCalgary, Alberta, Canada

1. Chitwood WR, Krummel TM: Introduction: Robotic surgery today and to-morrow. Am J Surg 188[Suppl]:1S, 2004.

2. Kaibara T, Saunders JK, Sutherland GR: Advances in mobile intraoperativemagnetic resonance imaging. Neurosurgery 47:131–138, 2000.

3. Louw DF, Fielding T, McBeth PB, Gregoris D, Newhook P, Sutherland GR:Surgical robotics: A review and neurosurgical prototype development. Neu-rosurgery 54:525–537, 2004.

Congress of Neurological Surgeons/American Association ofNeurological Surgeons Joint Section Chairmen

Cerebrovascular Surgery: Philip E. Stieg, New York, New York

Disorders of the Spine and Peripheral Nerves: Gerald E. Rodts, Jr., Atlanta, Georgia

History of Neurological Surgery: Dennis E. McDonnell, LaCrosse, Wisconsin

Neurotrauma and Critical Care: Alex B. Valadka, Houston, Texas

Pain: Oren Sagher, Ann Arbor, Michigan

Pediatric Neurological Surgery: Andrew D. Parent, Jackson, Mississippi

Stereotactic and Functional Neurosurgery: G. Rees Cosgrove, Boston, Massachusetts

Tumors: Raymond Sawaya, Houston, Texas



Documents

IN TOUCH WITH ROBOTICS:N THE F