Keywords robotic neurosurgery - computer-aided surgery - image-guided surgery - minimally invasive
neurosurgery - evolution
Introduction
The word robot was first used in 1920 in the play “Rossum's Universal Robots” by Karel
Capek.[1 ] While initially the connotation of robotics in neurosurgery was akin to “forced
labor,” it has since evolved by leaps and bounds to grow beyond the confines of the
“master–slave” concept. The first practical application of robotics in surgery was
described in fact in the field of neurosurgery by Kwoh et al on April 11, 1985.[2 ] A computed tomography (CT) guided brain biopsy of a malignant tumor came positive
in the first sample, and this set the stage for its use in various surgical specialties.
Robotics-based neurosurgery is challenging because of anatomical constraints and the
lack of a uniform subject-based education and training. The goal lies in seamlessly
integrating robotics into the existing armamentarium of technological adjuncts. All
stakeholders need to be on the same page from the early process of development in
order to produce technologies with wider reach and applicability. This article documents
the journey and reviews salient milestones and some important robotic solutions up
to the present day.
Early Developments Leading up to the Deployment of Robotic Technology in Neurosurgery
The quest for precision and accuracy while working within complex and often invisible
neural substrates resulted in the spawning of the field of image-guided surgery. This
started as frame-based stereotaxy as early as 1908 when Victor Horsley and Henry Clarke
invented the first stereotactic system and culminated in the development of a very
advanced and accurate polar coordinate-centric frame-based stereotactic device by
Prof. Lars Leksell in 1949.[3 ] Subsequent advances in imaging (CT, magnetic resonance imaging [MRI]) and evolution
in technology in the latter half of the 20th century gave rise to frameless stereotaxy
(neuronavigation). It was a matter of time before computer-aided surgery metamorphosed
into computer-directed surgery. Simultaneously neurosurgeons started adopting less
invasive approaches. The concept of minimally invasive neurosurgery stemmed from the
series of stereotactic biopsies described by various neurosurgeons in the early 1990s[4 ] but was popularized after the introduction of “keyhole surgical approaches” by Axel
Perneczky in 1998.[5 ] The next step in the evolution of minimally invasive neurosurgery was the wider
integration of robotics. These parallel and complimentary developments provided an
impetus to the nascent field of robotics as neurosurgery stepped into the new millennium.
Composition and Classification of Robotic Systems
The Robotic Institute of America formally defines the word robot as “a reprogrammable,
multifunctional manipulator designed to move materials, parts, tools, or other specialized
devices through various programmed motions for the performance of a variety of tasks.”[6 ] The basic components of a robotic system in neurosurgery include sensors, which
provide feedback (tactile, kinesthetic, and visual), a computing unit or data processing
center, controllers providing instruction to the effector robot, actuators converting
electrical energy into physical motion, and imaging input system.
Robotic systems in surgery were traditionally classified as per their underlying principles
into the following:
Active system: This type of robot has more autonomy than passive systems. The safe operation of
the actively powered robotic arm is a difficult task, but it provides a much wider
scope of joint mobility.
Intermediate system: The functioning here is shared between the surgeon and the robot. With the surgeon
operating and manipulating the instruments, the robot provides guidance and correction
of movements.
Passive system: Driven by the “master–slave” concept, the arm is locked in position during surgery
and completely controlled by the surgeon at all times. Considered to be safer than
the actively powered robots, they are limited by the range of motions the arm can
provide.
A more intuitive and practically useful classification groups them as per their mode
of functioning and the required level of neurosurgeons' participation:
Surgeon supervised and controlled ([Fig. 1 ]): It can be equated with a preplanned surgical procedure with the neurosurgeon plotting
the movements of the robotic arm beforehand. This matrix is then downloaded onto the
robotic system and the robot performs the planned movements with the neurosurgeon
overseeing/supervising the same in person. This corresponds to the “active” system.
Telesurgical robots ([Fig. 2 ]): In this type, the neurosurgeon controls the surgical movements of the robot real
time from a console (similar to the “passive” systems). The operating surgeon need
not be in the same room and can control the maneuvers via an online network. There
is provision for haptic feedback and live video transmission for the surgeon to simulate
a life-like experience.
Shared controlled systems ([Fig. 3 ]): The robot and the neurosurgeon perform the task together with the surgeon in control
of the movement and the robot providing concurrent stabilizing forces.
Fig. 1 Supervisory-controlled robot system. The surgeon enters the plan in a computer using
the patient's data before the actual surgery. The plan then gets downloaded to the
robotic system, which then implements the plan under supervision and close observation
of the surgical team.
Fig. 2 Telesurgical robot system. The surgeon (master) maneuvers the robotic arms (slave)
from the computer console room under guidance of real-time imaging and the tactile
feedback elicited via haptic technology.
Fig. 3 Shared-control robot system. The surgeon and the robot jointly sharing the surgical
task. Primary control remains with the surgeon, while the robot provides assistance
in the form of armrest, steadying the hand movements, etc.
Materials and Methods
Robotic systems specific to neurosurgical maneuvers can be grossly considered to be
of three major types, with each distinct from another:
There are various articles in the literature discussing about the robotic research
programs in neurosurgery encompassing those that could not be executed as well as
programs that are commercially available worldwide.[7 ]
[8 ] A nonsystematic literature search using the keywords “robotic,” “minimally invasive,”
and “neurosurgery” was performed in PubMed. The major robotic systems described in
neurosurgery were then reviewed looking at the year it was described and their original
application in neurosurgery. A chronological description of the promising robotic
systems introduced in neurosurgery is discussed further in a narrative fashion.
Neurosurgical Robots
PUMA-200 (Programmable Universal Manipulation Arm or Programmable Universal Machine Assembly).
This active robotic system was conceptualized by Kwoh et al in 1988.[2 ] The motions it provided via its six revolute joints were waist, shoulder, elbow,
wrist, and flange rotation, and wrist bend, which was quite comparable to human motions.
Once the target was locked by the robotic arm, the surgeon could choose the safest
trajectory without worrying about a change in the position of the target. Buoyed by
its initial success, the PUMA 200 was also used for holding and manipulating surgical
retractors while achieving radical excision of thalamic astrocytomas in six children
in 1991.[9 ] This system was the pioneer in practical surgical application of robotics.
Neuromate: This was the first robotic system to achieve Food and Drug Administration (FDA) approval
in 1997 in the United States and to achieve Conformité Européenne (CE) certification
in Europe. First described in 1987 in Grenoble University by Benabid et al,[10 ]
[11 ]
[12 ] this passive system consisted of a single arm and was widely used for stereotactic
biopsies (frame based or frameless) along with deep brain stimulation (DBS) for movement
disorder surgery.[13 ] A frameless fiducial registration system (Neurolocate) compatible with this system
has been described in 2017, which led to a quicker, more accurate and touch-free registration
process.[14 ]
Minerva: Developed in 1995 by Glauser et al,[15 ] this was the first real-time image guidance robotic system for complex stereotactic
biopsy procedures. Being linked to the CT gantry, the overall procedural time was
reduced since the CT scan could be taken in real time while performing a biopsy. However,
the marked radiation exposure, nonusability of the CT gantry for other patients during
the procedure, and the bulky stereotactic frame led to a fall in its acceptance.
CyberKnife: This system, although conceptualized much earlier by Prof. John Adler from the United
States, was described in the literature in 1997.[16 ]
[17 ] This was the first system to provide conformal radiosurgery dosages in a frameless
manner along with real-time imaging guidance.
Robot-Assisted Microsurgery System (RAMS): In 1999, the existing robotic technology of National Aeronautics and Space Administration
(NASA)[18 ] was utilized to create a master–slave type of robot with the slave robotic arm having
10 joints and the master arm having 8 joints. The prototype offered to scale down
the tremors and provide precision to the tune of 10 microns (cf. 70 microns for the
most accurate of human surgical hands). When this prototype was tested on 10 rats
for endarterectomies, it was found to increase the duration of procedure with no obvious
advantage over the human techniques.[19 ]
Leksell Gamma Knife Model C: Lars Leksell is a name synonymous with the field of gamma knife radiosurgery. His
first system was described in 1967; thereafter, this version was set up in 1999 and
included an automatic patient positioning system (APS). This robotic function drastically
cut down on the procedural time obviating the need for manually changing coordinates
with every change of plan.[20 ]
[21 ] The subsequent version known as Leksell Gamma Knife Perfexion introduced in 2006
involves fully automated patient position system (PPS) rather than only the head as
in the previous system.
da Vinci: This is the most commonly used master-controlled console-based robotic system today
after being introduced in 2000. As compared to other surgical branches (laparoscopic
and other minimally invasive procedures), its application in neurosurgery is yet to
gain a foothold due to reasons such as large size of the system and limited number
of instruments.[22 ]
Evolution-1: Described in 2002 by Zimmermann et al.,[23 ] this was the first to cater specifically to navigated neuroendoscopy to hold and
maneuver the endoscopic instruments with precision. The solitary robotic arm can be
steered with a remotely controlled joystick. In 2004, it was successfully used for
endoscopic third ventriculostomies (ETV) in six patients by the same group.[24 ]
NeuRobot: Till 2002, none of the robotic systems had multiple arms. Neither were they capable
of microsurgical application nor were they telesurgically controllable. NeuRobot designed
by Goto et al[25 ]
[26 ]
[27 ] as a master–slave system incorporated all these features. Introduced as a telecontrolled
micromanipulator system for minimally invasive microneurosurgery, it consisted of
four main parts: an input device, a manipulator, a supporting device, and a three-dimensional
(3D) display system. The manipulator device (slave) included three 1-mm dissecting
forceps and a 3D endoscope. Clinically, it was first attempted for partial meningioma
excision, ETV, and sylvian fissure dissection apart from remote controlled surgical
stimulation of a rat's brain.[28 ]
Georgetown Needle Driver Robot: This was the first system specific for spinal surgeries developed by Cleary et al
in 2002.[29 ] The robotic arm (mounted on the operating table and controlled via a joystick) was
used for percutaneous nerve blocks and facet joint blocks under fluorescence guidance
and was later expanded for CT-guided lung biopsies.[30 ]
SOCRATES: This was the first telementoring (robotic arm being controlled by a mentor from another
institute) system in neurosurgery and another telerobotic system after NeuRobot. Experience
with six cases consisting of craniotomies, endarterectomy, and laminectomy operated
using the SOCRATES system was published by Mendez et al in 2005.[31 ] The audio and video feedback was real time without any lag between the mentor and
operating surgeon.
SpineAssist Miniature Robotic System: The most popular and advanced of spinal robotic systems, this was introduced in 2006
by Barzilay et al (Mazor Robotics, Israel).[32 ] A multicenter study from 14 institutions verified that this system improved the
placement accuracy of screws and reduced the neurological complications.[33 ] The system provides 6 degrees of freedom (DOF) and is made up of a miniature hexapod
(2.5 cm, 250 g) fixed on bony spinous process. The Mazor workstation is used for planning
the screw placement on 3D models.
Pathfinder: This robot was first validated by Eljamel in 2007.[34 ] It consists of a single arm on a stable base. Pathfinder differed from the others
introduced till then in having an inbuilt camera sensor system for tracking position.
It fixed onto the Mayfield clamp and the image registration relied on fiducials and
surface targets on the patient's skull rather than any form of imaging. The initial
study was conducted on phantoms and it was found to be more accurate than the frameless
navigation machines as well as the frame-based stereotactic devices.
NeuroArm: Launched in 2008,[35 ] this is widely considered the most advanced robotic system. NeuroArm was the first
neurosurgical system to incorporate and allow MRI within it. To enable MRI compatibility,
the arms are made up of titanium and polyether ether ketone (PEEK) material. The arms
rest on a mobile supporting base and the end effector arm can hold a variety of instruments
needed for microneurosurgery. The first clinical series using this system in 35 cases
was published in 2013 with 1 adverse event reported.[36 ]
Neurosurgical robot with offset forceps: School of Engineering Department, University of Tokyo, in 2008, described a robot
for deep surgical fields using offset variants of forceps of 2.5 mm diameter that
do not interfere with the microscope's vision.[37 ]
Renaissance Robotic System: This was the second-generation version of the SpineAssist system produced by the
same parent company in 2011.[38 ] This version is faster, ergonomically better, smaller in size, and more accurate
than the SpineAssist robot. Apart from the fixation techniques, biopsy of spinal tumors
can also be done via this system. It is presently the most widely used spinal robotic
system.
Spine Bull's-Eye Robot: This is another spinal robotic system designed by Zhang et al in 2012. A 97.1% accuracy
was reported by their group for thoracic pedicle guidewire insertion.[39 ]
EXPERT: This passively controlled arm holder was first described by Goto et al in 2013.[40 ] The inbuilt position modes were transfer, arm hold, and arm free. A second-generation
version was described (iARMS) in 2017 by Ogiwara et al[41 ] ([Fig. 4 ]). With a heavy base, to prevent tilting over, the system supports and follows the
surgeon's arm to reduce fatigability. The initial experience in 43 cases of endoscopic
endonasal surgery showed that the surgeon did not feel any heavy handedness during
surgical movements, nor was there any need to toggle switches in between major movements.
It was subsequently validated by 14 neurosurgeons in the coming year and the results
have been very positive.[42 ]
Robotic Stereotactic Assistance (ROSA): This single-arm robot provides very good dexterity and accuracy and shortens the
operative time in procedures, namely, DBS, stereoelectroencephalography (SEEG), repetitive
nerve stimulation (RNS), etc.[43 ] It is one of the few systems featuring an integrated haptic technology to create
a more life-like interface for surgeons and the only system that can be used for cranial
as well as spinal surgeries. Preliminary results of electrode placement for thermocoagulation
of hypothalamic hamartomas using ROSA have been satisfactory.[44 ] The largest reported series utilizing this system is of 116 pediatric cases, which
demonstrated reduced postoperative morbidity and improved surgical outcomes.[45 ]
Robotically Operated Video Optical Telescopic-Microscope (ROVOT-M): Described in 2017,[46 ] ROVOT-M provides an intuitive and more effective optical visualization system that
can be utilized in a wide spectrum of complex cranial neurosurgical procedures.[47 ]
ExcelsiusGPS: This spinal robotic system, marketed by Globus Medical since 2017, provides navigated
guidance for accurate pedicle screw placement validated clinically.[48 ]
RoBoSculpt: Developed in Eindhoven University of Technology in 2018, this robotic arm can provide
precision-based drilling of the skull base and cut down on the duration of neurosurgical/ear,
nose, and throat (ENT) procedures. It is yet to be clinically validated.[49 ]
REMEBOT: This latest passive robotic system has been described by Wang et al[50 ] in 2019 for optimal stereotactic localization and evacuation of intracranial hemorrhage.
MYTHRI: National Institute of Mental Health and Neurosciences (NIMHANS) and Indian Institute
of Information Technology (IIIT) in Bangalore, India, have described a neurosurgical
robotic system in 2020. This robot is unique in having two independent systems, that
is, a functioning multi-arm base with 3 DOF and a distal hyperflexible end that adds
further 2 DOF.[51 ]
Robot-Assisted Neurosurgical Suite: This is a joint initiative led by Bhabha Atomic Research Centre (BARC), Mumbai, India,
in collaboration with the Advanced Centre for Treatment Research and Education in
Cancer (ACTREC), Tata Memorial Centre, Mumbai, India, to extend indigenous and affordable
high-quality neurosurgical robotic technology in resource-constrained setups. The
system incorporates inbuilt image guidance technology and is designed to execute all
the presurgical planning procedures and certain aspects of high-precision robot-assisted
neurosurgery ([Fig. 5 ]). The Robot-Assisted Neurosurgical Suite is made up of the following important subunits:
Image registration and patient-specific 3D model algorithms for surgical planning.
Surgical coordinate measuring mechanism (SCMM).
High-definition visualization and integration of virtual SCMM and surgical tool for
image-guided surgery.
High-precision, 6 DOF robot.
Algorithms for conducting the robot-based autonomous neurosurgical procedures including
autonomous patient registration, neuronavigation, and robot-based neuroprocedure.[52 ]
Fig. 4 (A ) Use of iArmS in microneurosurgery in the locked position. (B ) Demonstration of its adaptability in various positions taken by the surgeon. (These
images are provided courtesy of Dr. Tetsuya Goto from Shinshu University.)
Fig. 5 Robot-assisted neurosurgical suite comprising the neurosurgical robot (Bhabha Atomic
Research Centre, Mumbai and Tata Memorial Centre, Mumbai), surgical coordinate measuring
mechanism, and visualization.
The technology supports high-precision and accuracy in performing intricate targeted
surgery. A 6 DOF parallel kinematic mechanism (6D-PKM) robot is used for neurosurgery.
The robot is a compact portable system weighing 150 N, and it can support and manipulate
a payload of 200 N. The repeatability of the robot is 10 µm, and absolute accuracy
is 60 µm. It is dexterous to approach a point from multiple directions or, in other
words, the end tool of the robot can be positioned and oriented at any desired posture
in the workspace.
The visualization includes multisectional views and transparent 3D view to provide
real-time feedback on the progress of the tool insertion. The image segmentation,
enhancement of regions of interest, dynamic linking of 3D image and cross-sectional
images, sections normal to the tool axis and passing through the tooltip, digitization
of the image, etc., are obtained for accurate patient assessment and surgical planning.
The important aspect is that the virtual surgical tool is integrated and the movement
of real surgical tool is shown in all the cross-sections and in the patient-specific
3D model in real time.
The neuro-suite is equipped with a robust real-time algorithm to measure the coordinates
of the point on the marker for robot-based autonomous registration and surgery. The
algorithm is built in two parts. The first part deals with the detection of markers.
The second part autonomously measures the coordinates of the reference point on the
marker. Multiple studies have been conducted where the algorithm was tested for extreme
conditions of uneven lighting, distorted color, surface distortions, and significant
random orientation of the marker.
The average time of the manual patient registration process has been observed to be
about 15 minutes. In all the experiments, the time taken for the autonomous phantom
registration was found to be within 5 minutes. The phantom was registered within 1-mm
accuracy in all the cases for all the poses. High-precision navigation to the target
in all the poses was demonstrated. The detailed results of various case studies have
been reported in the literature.[53 ]
[54 ] The localization module has no line-of-sight problem and thus has a minimum footprint
in the operating room in contrast to the existing camera-based navigation systems.
The structure of this suite is based on parallel architecture, while most of the existing
robots are based on serial structures. Parallel architectures inherently are compact,
possess high rigidity, and result in high accuracy. They can support high payload
for a given self-weight. However, their reachable workspace is small compared to the
serial counterpart. The phantom-based trials have been conducted at the laboratory
and subsequently validated in a simulated trial operation theater.[53 ]
[54 ] Presently, the neuro-suite is under advanced clinical trials at NIMHANS, Bangalore,
and ACTREC, Navi Mumbai, with clinical validation on humans and animals pending.
[Table 1 ] summarizes the major cranial robotic systems and [Fig. 6 ] gives a timeline of major events in their development.
Fig. 6 Timeline of significant technological development and evolution of robotic systems
in neurosurgery.
Table 1
Summary of the major cranial robotic systems
Year
Name
Company/university
Type
Functionality
Highlights
1985
PUMA 200
UNIMATION, subsidiary company of Westington Electric, Pittsburgh, United States
Telesurgical
Effector
First surgically applied robotic system. 3 degrees of freedom (DOF). 0.05-mm precision
1987
Neuromate
Integrated Surgical Systems, Renishaw Mayfield, Lyon, France
Telesurgical
Effector
First neurosurgical robot to receive FDA and CE approval. 5 DOF. Incorporates preoperative
imaging
1995
Minerva
Swiss Federal Institute of Technology, Lausanne, Switzerland
Supervised and controlled
Effector
First to provide real-time image guidance. 5 DOF
1997
CyberKnife
Accuray Inc., United States
Supervised and controlled
Effector
First robotic system to provide conformal radiosurgery in a frameless manner. 6 DOF
1999
RAMS
National Aeronautics and Space Administration's (NASA) Jet Propulsion Laboratory and
Microdexterity System Inc., United States
Telesurgical
Effector
First to provide robotic surgical suites system. 6 DOF
1999
Leksell Gamma Knife Model C
Elekta, Stockholm, Sweden
Telesurgical
Effector
First robotic system to provide conformal radiosurgery in the frame-based technique
2002
Evolution 1
Universal Robot Systems, Schwerin, Germany
Shared Control
Holder
First to incorporate neuroendoscopy. 6 DOF for pedicle screw and 4 DOF for neuroendoscopy
2002
NeuRobot
Shinshu University, Japan
Telesurgical
Effector
Consists of 3D rigid endoscope and 3 arms of 1 cm diameter. 3 DOF
2007
Pathfinder
Prosurgics Ltd., High Wycombe, UK
Supervised and controlled
Effector
Inbuilt camera sensor for tracking. 6 DOF
2008
NeuroArm
University of Calgary, Canada
Supervised and controlled
Effector
First to integrate robot with intraoperative MRI. 2 arms with each having 7 DOF
2013
Expert
Shinshu University, Japan
Telesurgical
Holder
First of its kind robotic arm holder proven to reduce tremors. 5 DOF
2014
ROSA
Zimmer Biomet/Medtech Innovative Surgical Technology
Shared control
Effector
Used for multiple indications (cranial and spinal). 6 DOF
2017
ROVOT-M
Aurora Institute Group, Milwaukee, United States
Shared control
Visualization
First navigated exoscope with a dynamic robotic arm not requiring to be manually repositioned
2019
REMEBOT
Remebot, China
Telesurgical
Holder and visualization
Provides 3D visualization and multimodal image fusion for planning ideal puncture
trajectory for hematoma evacuation
2020
Robot Assisted Neurosurgical Suite
Bhabha Atomic Research Centre (BARC), Mumbai, India, with Advanced Centre for Training
Research and Education in Cancer (ACTREC), Tata Memorial Centre, Mumbai, India
Supervised and controlled
Effector
First indigenous Indian robotic system in neurosurgery with inbuilt image guidance.
6 DOF (under clinical development)
Abbreviations: CE, Conformité Européenne; FDA, Food and Drug Administration; MRI,
magnetic resonance imaging; 3D, three dimensional.
Benefits and Challenges in Implementing Robotics in Neurosurgery
Apart from the generalized benefits of robots such as negation of tremor, improved
dexterity, and 3D visualization, advantages specific to neurosurgery are its potential
to provide increased micromanipulation, reproducibility, and telesurgery. Coupled
with instantaneous and rapidly adapting biosensing technology (haptics and optics),
it can enhance surgical precision, especially within constrained spaces. At the same
time, safety checks can be incorporated preventing inadvertent potentially harmful
maneuvers. Although there exists the possibility of better outcomes in handling monotonous
surgical tissue in a consistent manner, these outcomes still need to be validated
on a larger scale to enable wide applicability. The existing procedural standards,
infrastructure, education, and training are conventionally in accordance with human-based
surgery. It is a complex and challenging process to extrapolate this into robotic-based
neurosurgery. The Digital Imaging and Communications in Medicine (DICOM) standards,
which facilitate and guide human image-based surgical procedures, do not yet contain
information required for robot-based neurosurgery. Furthermore, the conventional assessment
of the surgical performance and outcome is highly qualitative in nature. Surgeons
are intuitively nurtured because of their training and subjective experience, whereas
robotic surgery is based entirely on objectivity. Accurate correlation and reconciliation
of the qualitative feel and cognitive judgment of surgeons with objective and quantitative
numbers for robot-based surgery are highly challenging. The skill set and training
required for each make of robot are different, and the stakeholders may not like to
invest in a specific and limited scope of training. Additionally, there are logistical
issues, which may not seem obvious, namely, providing larger operating room setups,
trained surgeons and support staff, increase in the operating time, etc. These limitations,
coupled with the significantly high costs of devices, make the proposition less attractive
as of today. In spite of the technological developments since its first description,
application of robotics in neurosurgery remains limited due to the intricate anatomy,
difficulty in differentiating normal from neoplastic brain tissue, achieving satisfactory
hemostasis, and possibility of mechanical failure in autonomous robots
Future Perspectives
The science of learning from experience and high-precision evaluation is being pursued
using artificial intelligence (AI) and deep learning. AI integration of sensory perception,
neural networks, and thought processing superceding mathematical algorithms coupled
with nanotechnology represents the horizon where we can expect the next major advancements
to occur with respect to robotic technology.[55 ] With time, smartphones may play an important role in augmenting surgical techniques
coupled with robotics. Telerobotic technology for long-distance surgeries such as
in warzones is also under development by Verb Surgical in collaboration with technology
from SRI International.[56 ] A finger attachment device has been recently described, which illustrates an example
where robotics can effectively alter the decision-making process independently.[57 ] This gives us a glimpse of the future where such robotic attachments may discriminate
tumor tissue from normal brain not just via their feel but with rapid pathological
assessment as well. Above all, health economics is likely to govern many of the implementable
developments in robotics, and cost-effectiveness studies (besides principle and efficacy
studies) are the need of the hour.
Although we have alluded to a few of the possibilities, the potential remains limitless.
Presently, robotic systems provide enhanced visualization and positioning of payloads
along with controlled deployment of predetermined payloads. At present, robotics plays
a role in accessing deep-rooted points with high accuracy for biopsy, DBS, positioning
neural implants, neurosurgical assistance in ultrasound navigation, etc. In the future,
it is anticipated that these functions will be integrated into commonly used neurosurgical
platforms along with intuitive performance of complex neurosurgical maneuvers with
real-time feedback.
Conclusion
Neurosurgical practice involves complex surgeries that are being attempted through
narrower corridors, partly due to advances in the tools and approaches and partly
due to the nonfeasibility of extended corridors. Robotics can provide an advantage
in this aspect where it seems that the limits of human surgical expertise have been
reached. In developing countries like India, a unified intent needs to be exhibited
by all the collaborators including designers, manufacturers, policy makers, and neurosurgeons
to push forward the realm of robotics into neurosurgical practice with a focus on
the operational feasibility and cost-effectiveness.
