- Project NeuroArm, Department of Clinical Neuroscience and The Hotchkiss Brain Institute, University of Calgary, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6, Canada
Correspondence Address:
Garnette R. Sutherland
Project NeuroArm, Department of Clinical Neuroscience and The Hotchkiss Brain Institute, University of Calgary, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6, Canada
DOI:10.4103/2152-7806.151321
Copyright: © 2015 Sutherland GR. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.How to cite this article: Sutherland GR, Maddahi Y, Gan LS, Lama S, Zareinia K. Robotics in the neurosurgical treatment of glioma. Surg Neurol Int 13-Feb-2015;6:
How to cite this URL: Sutherland GR, Maddahi Y, Gan LS, Lama S, Zareinia K. Robotics in the neurosurgical treatment of glioma. Surg Neurol Int 13-Feb-2015;6:. Available from: http://sni.wpengine.com/surgicalint_articles/robotics-in-the-neurosurgical-treatment-of-glioma/
Abstract
Background:The treatment of glioma remains a significant challenge with high recurrence rates, morbidity, and mortality. Merging image guided robotic technology with microsurgery adds a new dimension as they relate to surgical ergonomics, patient safety, precision, and accuracy.
Methods:An image-guided robot, called neuroArm, has been integrated into the neurosurgical operating room, and used to augment the surgical treatment of glioma in 18 patients. A case study illustrates the specialized technical features of a teleoperated robotic system that could well enhance the performance of surgery. Furthermore, unique positional and force information of the bipolar forceps during surgery were recorded and analyzed.
Results:The workspace of the bipolar forceps in this robot-assisted glioma resection was found to be 25 × 50 × 50 mm. Maximum values of the force components were 1.37, 1.84, and 2.01 N along x, y, and z axes, respectively. The maximum total force was 2.45 N. The results indicate that the majority of the applied forces were less than 0.6 N.
Conclusion:Robotic surgical systems can potentially increase safety and performance of surgical operation via novel features such as virtual fixtures, augmented force feedback, and haptic high-force warning system. The case study using neuroArm robot to resect a glioma, for the first time, showed the positional information of surgeon's hand movement and tool-tissue interaction forces.
Keywords: Force feedback, glioma, haptic warning, intraoperative magnetic resonance imaging, robot-assisted microsurgery, virtual fixture
INTRODUCTION
The complex nature of the brain possesses considerable challenges to neurosurgeons.[
Treatment protocols for glioma vary based on the cell origin, composition, and tumor grade. For the majority, maximum resection of the tumor remains the initial step in the treatment regimen. Surgical intervention can be challenging due to lack of tumor margin demarcation, making it difficult for a surgeon to achieve complete resection without some degree of compromise to surrounding tissues and associated neurological deficit.[
Surgical resection of high-grade glioma is typically followed by adjuvant radiation and/or chemotherapy.[
Technologies that enhance tumor resection are important in achieving optimal outcome. Since the mid-1990s, intraoperative magnetic resonance imaging (iMRI) systems have been translated into the neurosurgical operative room to improve intraoperative lesion localization and resection control.[
This report provides an insight into challenges related to robot-assisted surgery, potential benefits of robotics, position and force data obtained from a neuroArm procedure for glioma, and ongoing advances that can be used in robotic systems to improve safety and performance. For the first time, positional information of surgeon's hand movement and tool-tissue interaction forces are reported. The position and force ranges of the robotic arm have been quantified, which may be used as a reference for further training purposes in robot-assisted glioma surgery, and for design and development of new surgical tools.
Glioma Surgery improved by robotics
Surgical robots provide surgeons the benefit of features such as tremor filters and motion scaling to enhance surgical performance. The neuroArm's sensory immersive workstation allows the surgeon to interact with imaging data without interrupting the rhythm of surgery. The workstation comprising of haptic hand-controllers, three dimensional (3D) MRI display with tool overlay, a stereoscopic view of the operative field and a virtual image of the manipulators relative to the patient. An additional monitor includes images from the surgical site including the manipulators and operating team. To date, the system has been used in 56 cases, primarily for central nervous system (CNS) neoplasia and cavernous angioma [
Navigating narrow surgical corridors
A distinct advantage of using a robot in neurosurgery is that the precision and accuracy of machine technology is combined with the executive capacity of the human brain (a teleoperated robotic system with the surgeon in the loop).[
The neuroArm includes a specialized tremor filter, developed in software, that enables smooth displacement of robotic arms. At the workstation, the surgeon uses hand-controllers to manipulate the robotic arms. A low-pass filter is applied to the command signals so that high frequency components representative of physiological tremor (>6 Hz) can be filtered.[
Another feature of neuroArm that helps the surgeon maneuver surgical tools attached to the end-effector of the robot more precisely is motion scaling.[
Brain shift
Brain shift during surgery makes surgical navigation based on preoperative images invalid. This issue is usually in part managed by the experience of the surgeon. In those units that possess iMRI systems, new images can be acquired during surgery to assess the extent of tumor resection and to re-register the navigation system. In many cases, as illustrated in
Surgeon fatigue
As shown on the left panel of
Other benefits of robotic surgery
Image-guided robotic surgery provides a platform for case documentation, safety, and education. These will become increasingly integrated into neurosurgical practice as advances in technology, machine control, and computer processing occur.[
Collecting data for case rehearsal and training
A surgical robotic system can record positional and force data during surgery, which is not possible in conventional surgery. This recorded data can be used for quality assurance and case rehearsal. Case rehearsal in a virtual reality simulator may be of a particular value in making a novice surgeon's initial experience with robotic surgery safer, less stressful and more efficient.
Positional and force data collected during robotic surgery can also contribute to the development of surgical simulators. A simulator that provides touch sensation via haptic hand controllers, allows surgeons to practice surgery with or without a robotic platform, thus acquiring experience in a fail-safe environment. In any haptic hand-controller, the force feedback to be generated by the haptic device actuators first needs to be computed in software based on the physical properties of the tissue models. The computed force is sent as command signals to the actuators of the hand-controllers. Intraoperative force and positional data, acquired during robotic procedures, can be used to define the mechanical properties of virtual tissue models and assist in development of realistic tissue deformation and tool-tissue interaction in the virtual environment.[
Technical methods to increase safety
Implementing the concept of virtual fixture
The concept of virtual fixtures is a technique that could greatly improve safety during robot-assisted surgery. Virtual fixtures could be defined in software to assist the surgeon performing a tele-manipulation task. Such a feature can limit the position or force to guide surgery while tasks are being performed.[
Virtual fixtures were employed by Rosenberg for a teleoperation task and found to improve operator performance by up to 70%.[
With respect to robot-assisted glioma surgery, brain shift during the operation, for example, invalidates the navigation technology based on preoperative images.[
Technically, a no-go zone has no effect on the robot when its end-effector is out of the defined no-go zone. Therefore, the surgeon can guide the robot end-effector as long as the surgical tool is not going to penetrate into the no-go zone, that is, the corridor virtual wall.
Figure 5
Example of a no-go zone virtual fixture (shown as circular solid lines) and robot positional configuration. Several no-go zones can be defined for a surgical task. The region of interest, in which the robot performs surgery, is shown with dotted area. Dashed areas are critical structures in brain, for example, speech cortex and motor cortex
Implementing the concept of augmentation force
The virtual fixture helps the operator keep the surgical tool in a safe zone during surgery. They are normally defined at the sensory immersive workstation-haptic hand-controller, maintaining the surgeon's hand in a safe zone; thus, the surgical tool, at the slave manipulator, stays within the anticipated safe zone. This allows the surgeon to move the hand-controller implement faster when desired while relying on the fact that the patient would be safe in the presence of the virtual fixture.[
Haptic warning system
While performing surgery, application of excessive force to nontargeted structures in the brain might cause unintended damage to healthy brain tissues. In robot-assisted neurosurgery, forces of tool-tissue interaction can be measured and relayed to the surgeon's workstation. In neuroArm, each robotic arm is equipped with two titanium Nano17 force sensors (ATI Technologies Inc.) to measure these forces in real-time [
Clinical case study
Experimental setup
NeuroArm[
An Omega 7 haptic device provides 7 degrees of freedom (DOFs) positional sensing and 4 DOFs force feedback. The haptic device implement covers the natural range of motion of the human hand pivoting around the wrist, and is compatible with bi-manual teleoperation console design. The haptic device, comprised of a parallel mechanism, has the capability of producing force up to 12 N, and a grasping force feedback up to 8 N. During teleoperation of neuroArm, the surgeon who is located at the workstation uses hand-controllers to command the neuroArm manipulators. As a safety feature, the foot pedals have to remain engaged to allow the robot to move. Haptic capability of the hand-controllers allows the surgeon to experience the tool-tissue interaction remotely.
Test procedure
The results are taken from a robot-assisted glioma surgical operation performed by neuroArm. Total duration of robot-assisted surgery, excluding craniotomy and wound closue was about 33 min. The surgical tasks were a combination of manipulation, coagulation and pick and place motions of cotton strips.
RESULTS
Figure 9
Force measured by the force sensor for the trajectory given in
Results of the glioma case in four dimensions
The workspace of the bipolar forceps over 2000-s of surgery is shown in
CONCLUSIONS
This report addresses the importance of continuing the translation of robotic technology into neurosurgery. Robotic surgical systems provide an advantage when surgical corridors are narrow, brain shift is inevitable and or when conventional surgery demands for an ergonomic posture for the surgeon. Unique solutions to increasing safety and performance of the operation were exemplified. In particular the use of virtual fixtures, using augmented force feedback to reduce the possible positional errors, and the addition of a haptic high-force warning system. The case study using neuroArm robot to resect a glioma, for the first time, showed the positional information of surgeon's hand movement and tool-tissue interaction forces. The mean values of these interactive forces were much less than 1N in x, y, or z directions. The position and force ranges of the robotic arm were quantified, and may be use to reference training in robot-assisted glioma surgery.
ACKNOWLEDGMENTS
The authors would like to thank Dr. Fang Wei Yang and the operating room staff at Foothills Hospital with the preparation and setup of the neuroArm robot during the glioma case, and Ms. Alison Shepherd for assistance with the preparation of the manuscript. This work was supported by Canada Foundation for Innovation, Western Economic Diversification and Alberta Advanced Education and Technology.
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