Robotic Assisted Surgery
Robotic assisted surgery is one of the newest areas of innovation in minimally invasive surgery. Robots used in surgery offer the potential for safer and more easily repeatable surgeries, minimizing the risk to the patient. Surgical robots can be broken down into two categories: active and passive. Active robots are autonomous, while passive robots require more interaction from the surgeon or user. This article briefly reviews some of the current technology used for passive and active robotics.
Robots used for surgery offer the potential for safer and less invasive procedures to be performed. A surgical robot may be set up next to the surgeon to assist, or may eliminate the need of a surgeon in the operating room altogether. Many of the types of surgical robots listed below are the newest developments in minimally invasive surgeries. Compared to open surgeries, during minimally invasive surgeries the surgeon performs the procedure with less injury to the body. This allows the patient to heal faster, and decreases the risk of infection. Some of the downsides of minimally invasive surgeries are the high cost of the tools, and the training required so that surgeon may use these tools (Sobh & Xiong, 2012).
The first non-robotic minimally invasive surgery technique was the laparoscopic approach and is often called the “zeroth” generation of robotic surgery. Laparoscopy is the process by which access to the pathology location is gained through small incisions made in the abdominal cavity. An elongated tool is inserted into each of the incisions, and an endoscopic camera is inserted into one of the incisions as well. Depending on the type and complexity of the surgery, three to six ports are typically used (Bergeles & Yang, 2014).
The advantages of laparoscopic surgery include an expedited recovery time for the patient, decreased risk of infection, and less stress on the patient’s body; however, laparoscopy is limited in its abilities. The endoscopic camera used in laparoscopic surgery does not give a stereoscopic view, which provides surgeons with depth perception. In addition, hand-eye coordination that surgeons are used to during open surgery is gone because their hands are outside of the patient. Finally, the tools do not have the same degrees of freedom of movement that a wrist does. Surgical robots strive to restore these missing aspects and improve upon laparoscopic surgery.
Developments in electrical and computer engineering have allowed for the possibility of advancing and developing surgical robots, a new field of minimally invasive surgery. Because surgical robots can be sterilized and have more precision than humans, they offer the potential to decrease the risk during surgery and of post-operative complications for the patient. Another advantage of robotic surgery is the potential for tele-surgery, where the surgeon is in a different location than the robot. This could be used in military applications, so surgeons could remotely and safely operate on wounded soldiers (Hussain & Malik, 2014).
The field of surgical robotics can be broken down into passive and active robots. Active robots are defined to autonomously perform surgeries, and they require little to no intervention by the surgeon. Passive robots are unable to perform surgery without the intervention of a surgeon. Passive robots are often used to define a surgical entry path or specifically to increase the surgeon’s accuracy and precision (Bergeles & Yang, 2014). Below, a brief survey of several passive surgical robots will be discussed, followed by a discussion of active robots.
The first passive robot was called the PUMA 200 and was used to define the entry orientation and location of a surgical needle, and then turned off while the surgeon performed the rest of the surgery (Bergeles & Yang, 2014). The PUMA 200 gave surgeons within one-millimeter precision when defining the entry orientation and location of the surgical needle, much more precise than a trained surgeon can achieve. A later but similar robot, called the NeuroMate, was developed for use exclusively in neurosurgeries (Bergeles & Yang, 2014). This type of passive surgery works well with neurological and orthopedic surgeries as opposed to soft-tissue surgeries. From patient to patient, the structure of the skull and skeletal system does not change dramatically, thus a positioning robot can translate easily.
One of the most popular categories of passive robots is the hand-held robot because they are the most similar to the tools surgeons are used to. Hand-held robots can be broken down into five major categories. Tremor suppression devices can detect their own motion and filter out erroneous motion. They then cause the surgical end-effectors to compensate for this motion. This is a tool often used in microsurgery, such as retinal surgery. In order to be able to accurately detect a wide range of motion, the device needs to have a high bandwidth – a problem that can be solved with the use of electrical and computer engineering (Payne & Yang, 2014). One device that has been implemented as a hand-held tremor suppression device is the Micron. The Micron was intended for use in microsurgeries, especially retinal surgery. It actuates its own tip to cancel tremor. Because it is a hand-held mechanically ungrounded device, the Micron only preserves 1:1 force feedback, meaning that the force exerted on the tool can be directly felt by the operator. In microsurgeries, such as retinal, it would be valuable to have a scaled force feedback because the tool tip is so small and the tissue is so soft. Implementing this in mechanically ungrounded devices is still an ongoing area of research (MacLachlan et al., 2012).
Another type of hand-held device is guidance systems, which are used to constrain tool motion and are often used in conjunction with image guidance systems. They can constrain a surgical tool toward or away from a pre-defined point. For example, the NavioPFS is used for partial knee replacement. The cutting tool is retracted when the constraint boundary is approached, so the surgeon does not cut too deep (Payne & Yang, 2014). One advantage of the NavioPFS is that it has planning and robotics-assisted bone-preparation embedded into the device, so the surgeon can make a more precise surgical plan because of the added information fron the NavioPFS (Gregori, Lethbridge, & Simone, 2013). However, as with many of these new surgical robotics, the NavioPFS does have a learning curve. It was found that on average it took surgeons eight procedures to reach two out of three consecutive cases within a 95% confidence interval (Wallace et al., 2014).
The third type of hand-held device is the articulated mechatronic device, which is used to help restore dexterity to the surgeon. The Laparo-Angle is used in laparoscopic surgeries and uses motor actuation to articulate the tip of a laparoscopic tool to control roll, yaw, and triggering functions. The surgeon is able to achieve seven degrees of freedom, which makes positioning and controlling the device easier and makes the device feel more natural. However, by adding various controls that make the Laparo-Angle function more as a surgeon’s hand would, it has added complexity to the device and lengthened the learning curve (Rao, Rao, Bhagwat, 2011).
A fourth type of hand-held device is the force control systems, which are used for active tool-tissue contact stabilization, especially in beating heart surgery. Yuen et al. (2009) developed a mechatronic force control device to be used in beating heart surgery, which can deal with the periodic motion of the heart and a high bandwidth. This device uses force control of the instrument against the surgical target. In addition, it feeds forward tissue motion information generated by real-time 3D ultrasound, improving the performance of the force controls (Yuen et al., 2009).
Finally, haptic feedback devices use force sensing and integrated actuation to provide force-feedback. Hand-held devices inherently provide haptic feedback because the surgeon handles them, but the goal is to enhance tool-tissue interactions (Payne & Yang, 2014). For example, the MicroTactus developed by Yao et al. (2005) senses tool-tissue interactions with an accelerometer and a magnetic actuator. The magnetic actuator amplifies the signals from the accelerometer to provide vibrotactile feedback to the surgeon. This allows the surgeon to get a better sense of the surface they are dealing with, and cuts or surface patterns that may exist. One problem that still needs to be addressed for this device is that the amount of gain, or amplification, in the system was limited, so it would be unable to detect the smallest of signals (Yao Hayward, & Ellis, 2005). Passive robots offer surgeons improved performance while keeping the surgical instruments as close to traditional tools as possible.
The first active robot developed was the ROBODOC, which works in conjunction with the ORTHODOC. This robot acquires a CT scan in order to develop a surgical plan, and then autonomously performs the surgery. The only time the surgeon intervenes is to overlook the surgical plan and make any necessary changes (Bergeles & Yang, 2014). These two robots are used for orthopedic surgeries, specifically for total joint replacement. The ORTHODOC acquires the CT scan, and converts it to a 3D bone image. This allows surgeons to look at different implants and positions for the implant so the best option can be selected for the patient. The ROBODOC then drills into the bone with sub-millimeter accuracy, as defined by the ORTHODOC’s plan (“Transforming Total Joint Replacement with Active Robots”).
A study comparing the use of the ROBODOC/ORTHODOC versus a manual hand-rasping technique during the implantation of a cementless total hip arthroplasty found some advantages to the robotic approach, but with more generally mixed results (Nakamura, Sugano, Nishii, Kakimoto, & Miki, 2010). For example, one year after the operation only 1.3% of patients with the robotic surgery complained of thigh pain, compared to 5.6% of patients with the manual surgery. In addition, the limb-length inequality was found to be on average 5mm in the robotic patients, and closer to 6mm in the manual patients. Interestingly, the robotic method took approximately 120 minutes while the hand-rasping method took only approximately 108 minutes. The number of post-operative hip dislocations was seen in 5.3% of the patients who underwent the robotic surgery, and only in 1.4% of the patients who underwent the hand-rasping method. Clearly, while the ROBODOC is not a flawless method of surgery, it does offer potential for making orthopedics surgery more consistent and safer (Nakamura, Sugano, Nishii, Kakimoto, & Miki, 2010).
One of the most popular active robots is called the daVinci. The daVinci is considered a tele-operated robot, meaning the surgeon is able to remotely control a patient-side slave robot through manipulation of the master manipulator (Yang, Wang, Liu, & Wu, 2013). While the ROBODOC and ORHTODOC are used primarily for orthopedic surgeries, the daVinci is used for a range of surgeries, including cardiac, colorectal, general, head and neck, thoracic, and urological surgeries. The daVinci has two main units; the first is the surgeon’s control unit. This houses the display, the surgeon’s user interface, and the electronic controller. The second unit has four slave manipulators, or essentially arms. Three of these arms are for telemanipulation and have the tools to perform the surgery, while the fourth has an endoscopic camera for visualization (Freschi et al., 2013).
One of the advantages of the daVinci is that the surgeon operates with their gaze towards their hands, which helps restore their hand-eye coordination. In addition, the arms have seven degrees of freedom in order to more accurately mimic a surgeon’s hand movement. The endoscopic camera is a 3D endoscope with two separate optic channels, connected to a pair of charged-coupled device chip cameras. The optic channels are separated by 6mm, creating a true stereoscopic image. This significantly helps the surgeon with orientation and manipulation. In addition, the images are filtered to eliminate noise, and are displayed on high-resolution monitors (Yang, Wang, Liu, & Wu, 2013). These advances in the field of optics and image processing fall into the category of electrical and computer engineering. While these technologies present the surgeon with a more realistic surgical field, the daVinci still lacks haptic feedback (Bergeles & Yang, 2014).
One of the newer fields in robot surgery is that of untethered microsurgeons. These include capsule endoscopes, which are a millimeter device that can be used to explore the GI tract. The capsule is passively propelled by peristalsis in the GI tract, and can be used for imaging as it moves along. This can assist doctors in making more accurate diagnoses, without invasive procedures. Other capsules have the ability to navigate their way using on board locomotion, some external energy transfer, or possible magnetic steering. One challenge is that the technique used for imaging must be small enough to fit inside the capsule. Endoscopy is orders of magnitude too large, so a different method must be employed. An MRI can verify the placement of the capsule because the magnetic microrobot would appear in the MRI as a detectable artifact. Active robots have the potential for decreasing human error during surgery by adding a precise and accurate interface between the surgeon and patient.
Whether robotic surgery is better than traditional surgery depends heavily on the patient, and the surgery they need. However, surgical robotics have come a long way from where they started, and continue to open doors to less invasive procedures. Many of these advancements have been thanks to both electrical and computer engineering, as well as the computer science needed to control them, and the mechanical engineering required to create the machines. As for the electrical and computer engineering, digital image and signal processing is required for the imaging, as well as an understanding of optics required creating the stereoscopic view. Since these are robots, a heavy level of circuitry is required to create them. As these aspects of electrical and computer engineering continue to advance, so will the field of surgical robotics, making robot assisted surgery increasingly prevalent.
- Bergeles, C., & Yang, G.-Z. (2014). From passive tool holders to microsurgeons: safer, smaller, smarter surgical robots. IEEE Transactions on Bio-Medical Engineering, 61(5), 1565–76. DOI: 10.1109/TBME.2013.2293815
- Freschi, C., Ferrari, V., Melfi, F., Ferrari, M., Mosca, F., & Cuschieri, A. (2013). Technical review of the da Vinci surgical telemanipulator. The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS, 9(4), 396–406. DOI: 10.1002/rcs.1468
- Gregori, A., Lethbridge, R., & Simone, A. (2013). Case Study: Totals Aren’t Always an Inevitability. Retrieved from http://bluebelttech.com/products/navio/research-results/. Available at http://bluebelttech.com/site/wp-content/pdfs/Case_Study_Totals_Arent_Always_An_Inevitability.pdf
- Hussain, A., Malik, A., Halim, M. U., & Ali, A. M. (2014). The use of robotics in surgery: a review. International Journal of Clinical Practice, 68(11), 1376–82. DOI: 10.1111/ijcp.12492
- MacLachlan, R. A., Becker, B., Tabares, J. C., Podnar, G., Lobes, L., & Riviere, C. (2012). Robotics Institute: Micron: an actively stabilized handheld tool for microsurgery. Retrieved from https://www.ri.cmu.edu/publication_view.html?pub_id=7422&menu_code=0307. DOI: 10.1109/TRO.2011.2169634
- Payne, C. J., & Yang, G.-Z. (2014). Hand-Held Medical Robots. The Journal of the Biomedical Engineering Society. DOI: 10.1007/s10439-014-1042-4
- Rao, P. P., Rao, P. P., & Bhagwat, S. (2011). Single-incision laparoscopic surgery – current status and controversies. Journal of Minimal Access Surgery, 7(1), 6–16. PMCID: 3002008
- Sobh, T., & Xiong, X. (2012). Prototyping of Robotic Systems – Applications of Design and Implementation. IGI Global. OCLC WorldCat Permalink: http://www.worldcat.org/oclc/894718325
- Wallace, D., Gregori, A., Picard, F., Bellemans, J., Lonner, J., Marquez, R., … Jaramaz, B. (2014). The Learning Curve of a Novel Handheld Robotic System for Unicondylar Knee Arthroplasty. Bone & Joint Journal Orthopaedic Proceedings Supplement, 96-B(SUPP 16), 13. Retrieved from http://www.bjjprocs.boneandjoint.org.uk/content/96-B/SUPP_16/13.abstract
- Xu, Y., & Wang, H. (2014). Image processing based surgical navigation system building. In 2014 IEEE Workshop on Electronics, Computer and Applications (pp. 991–994). IEEE. DOI: 10.1109/IWECA.2014.6845789
- Yao, H.-Y., Hayward, V., & Ellis, R. E. (2005). A tactile enhancement instrument for minimally invasive surgery. Computer Aided Surgery : Official Journal of the International Society for Computer Aided Surgery, 10(4), 233–9. DOI: 10.3109/10929080500230403
- Yang, R., Wang, Z., Liu, S., & Wu, X. (2013). Design of an Accurate Near Infrared Optical Tracking System in Surgical Navigation. Journal of Lightwave Technology, 31(2), 223–231. DOI: 10.1109/JLT.2012.2227943
- Yuen, S. G., Yip, M. C., Vasilyev, N. V, Perrin, D. P., Del Nido, P. J., & Howe, R. D. (2009). Robotic Force Stabilization for Beating Heart Intracardiac Surgery. Medical Image Computing and Computer-Assisted Intervention : MICCAI … International Conference on Medical Image Computing and Computer-Assisted Intervention, 5761(2009), 26–33. DOI: 10.1007/978-3-642-04268-3_4
See also (Links to other SHP articles):
- Lenk, Will
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