REVIEW URRENT C OPINION
Robotics and regional anesthesia Mohamad Wehbe a, Marilu Giacalone b, and Thomas M. Hemmerling c
Purpose of review Robots in regional anesthesia are used as a tool to automate the performance of regional techniques reducing the anesthesiologist’s workload and improving patient care. The purpose of this review is to show the latest findings in robotic regional anesthesia. Recent findings The literature separates robots in anesthesia into two groups: pharmacological robots and manual robots. Pharmacological robots are mainly closed-loop systems that help in the titration of anesthetic drugs to patients undergoing surgery. Manual robots are mechanical robots that are used to support or replace the manual gestures performed by anesthesiologists. Although in the last decade researchers have focused on the development of decision support systems and closed-loop systems, more recent evidence supports the concept that robots can also be useful in performing regional anesthesia techniques. Summary Robots can improve the performance and safety in regional anesthesia. In this review, we present the developments made in robotic and automated regional anesthesia, and discuss the current state of research in this field. Keywords closed-loop systems for sedation, robot-assisted intubation, robot-assisted nerve block, robotic anesthesia
INTRODUCTION
AUTOMATED SYSTEMS FOR SEDATION
The notion of robots in medicine is not new, and the history of surgical robots began in 1985 with the Unimation Puma 200 robot used to perform computed-tomography-guided brain tumor biopsies [1]. In April 1997, the first robot-assisted surgical procedure on a patient was performed in Brussels, Belgium [2,3]. In anesthesia, however, development was slower, and the first attempt in automation was the introduction of computerized pharmacokinetic model-driven continuous infusion pumps [4,5]. These attempts resulted in the first targetcontrolled infusion (TCI) device for administering propofol. Research has focused on the closed-loop systems in anesthesia. In contrast to TCI, closedloop systems control the drug dose (effect) by continuously checking the controlling parameter, such as the depth of consciousness for propofol infusion. Although their performance was tested clinically, and showed to be on par with manual anesthesia, closed-loop systems are still used for research purposes and have not yet been used in clinical practice [6]. More recently, research has demonstrated that robots may also be useful in regional anesthesia.
Most regional anesthesia techniques require sedation. Automated systems for anesthesia are closedloop systems; these systems are a feedback control system that monitors one or more input variables, the output signal (or a function of the output signal) and reduces the error (difference between the input and output) to bring the output of the system to a desired value [7]. A block diagram of a closed-loop system is illustrated in Fig. 1. The only commercially available automated system for sedation at present is the SEDASYS system (Ethicon Endo-Surgery, Cincinnati, Ohio, USA), which is a computer-assisted personalized sedation
www.co-anesthesiology.com
a
Division of Experimental Surgery, McGill University, Montreal, Canada, Department of Anesthesia, University Pisa, Pisa, Italy and cDepartment of Anesthesia, Division of Experimental Surgery & Arnold and Blema Steinberg Medical Simulation Centre, McGill University, Montreal, Canada b
Correspondence to Thomas M. Hemmerling, MD, DEAA, Montreal General Hospital, Room C10 - 153, 1650 Cedar Avenue, Montreal, QC, Canada H3G 1A4. Tel: +1 514 934 1934 ext 43677; e-mail: [email protected]; website: www.newanesthesia.com Curr Opin Anesthesiol 2014, 27:544–548 DOI:10.1097/ACO.0000000000000117 Volume 27 Number 5 October 2014
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Robotics and regional anesthesia Wehbe et al.
KEY POINTS The application of closed-loop systems improves the titration of drugs administered in all phases of sedation, based on the objective data derived from monitoring. Robotic assistance in anesthesia consists of mechanical robots, which support or replace the human gestures in several fields of regional anesthesia. Robotic neuraxial and peripheral nerve blocks are as feasible as manual blocks, with increased accuracy and precision, as well as autocontrolling and provision of training tools.
system [8,9]. The SEDASYS system integrates the monitoring of pulse oximetry, capnometry, ECG, noninvasive blood pressure, and patient responsiveness, with the delivery of oxygen and propofol [8]. The SEDASYS system is designed to facilitate the safe administration of propofol to induce minimalto-moderate sedation to relatively healthy adults undergoing elective colonoscopy or esophagogastroduodenoscopy (EGD) [10]. The SEDASYS system is operated by a physician-led team whose members are trained in various aspects of general anesthesia [10]. The device also incorporates an automated responsiveness monitor (ARM) to assess patient responsiveness. The ARM delivers at preset time intervals, an auditory request asking the patient to squeeze the handset he or she is holding, together with a mild vibration. If the patient fails to respond by squeezing the handset, the auditory request becomes louder and the vibration more vigorous. The ARM calculates the patient’s response time [10]. The SEDASYS system will not allow propofol infusion unless oxygen is being delivered to the patient. Signs of oversedation trigger the system to increase the oxygen delivery rate. Also, the system automatically decreases the propofol rate when responsiveness to the ARM is lost [10]. In a study published in 2011 by Pambianco et al. [9], the SEDASYS system was used to perform sedation on 496 patients undergoing routine EGD and colonoscopy. A total of 504 patients of the control group received traditional sedation with benzodiazepine and opioids. The
Input
+
–
study proved that the SEDASYS system reduces the risks of oversedation, and patients receiving sedation with the SEDASYS system experienced fewer and less significant oxygen desaturation than those in the control group. The US Food and Drug Administration granted premarket approval on May 3, 2013 and approval of modifications on June 23, 2014 [11].
ROBOTIC ASSISTANCE IN ANESTHESIA The use of robots has been successfully applied both clinically in endotracheal intubation and as a teaching tool. Another area in which robotic assistance is being developed is represented by regional anesthesia. One of the first attempts to apply robotics to regional anesthesia was carried out by Cleary et al. [12], who developed a robotic needle driver for spinal blocks (nerve roots and facet blocks). Their equipment consisted of a robotic needle driver mounted on an interventional table and a joystick located in a control panel separated from the robot. A robot controller with safety features was installed in a computer and connected to the robot by cables. First, the authors identified 12 targets in the paraspinal space of a cadaver by putting 12 metal markers in six nerve roots and six facet roots, three for each side, and verified the correct position of the targets through fluoroscopy. Second, they positioned a needle within 3 mm from the target orienting the robotic driver by the joystick. Needle trajectory and depth were guided by fluoroscopy. As a result, all needles were located within 3 mm from the target, with a mean distance of 1.44 0.66 mm [12]. Later, the same group applied this device to the performance of spinal blocks in patients [13]. They compared the performance of such blocks in two groups of patients, 10 undergoing manual block and 10 undergoing robotic block with the equipment described above. The results showed similar accuracy and post-treatment pain score between the two groups, concluding that robotic spinal blocks are as feasible as manual blocks [13]. Subsequently, other researchers developed a more general device for the guidance of soft-tissue injections, as regional anesthesia is [14]. In this
Controller
Actuator
Output
FIGURE 1. Block diagram of a simple closed-loop control system.
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Regional anesthesia
study, first, they established a control algorithm given a predetermined needle trajectory, then, a robotic arm (C-Arm) drove a flexible, spinal needle toward the target (an animal specimen) and performed the puncture under a closed-loop control from a software guided by real-time X-ray images. This system aimed to create a pathway for needle driving given the initial coordinates and to optimize the plan for minimal pressure on tissues, also taking into account the possible obstacles [14]. Other applications of robotics to regional anesthesia have concerned peripheral nerve blocks, with subsequent development. In a similar fashion to what was mentioned above, Tighe et al. [15] used the da Vinci Surgical System to perform a robotically assisted ultrasound-guided nerve block. This was done in a simulated environment as a single-injection nerve block, and placement of a perineural catheter into an ultrasound phantom under ultrasound guidance. As with their other study mentioned above, they used the da Vinci S Surgical System to perform the procedure. They tested first the ability of the robotic system to manipulate the equipment involved in a peripheral nerve block. After this test, they placed the ultrasound phantom on an operating room stretcher under the da Vinci. They manually placed the ultrasound probe, and after identifying the simulated perineural structures in the phantom, they stabilized the probe with the da Vinci system. Three arms were used to maneuver most of the equipment relevant to the nerve block. The ultrasound probe was connected to the da Vinci in order to allow for simultaneous visualization of ultrasound images and da Vinci video input. This video feed was also used to place the perineural catheter by means of a Tuohy needle [15]. Their study proved that robotically assisted regional anesthesia is feasible; however, the use of a multimilliondollar system to perform regional anesthesia, along with the number of personnel needed to accomplish this task (two engineers, an anesthesiologist, and a urologist), is not practical. A system consisting of equipment specifically designed to perform robot-assisted, ultrasoundguided nerve blocks is the Magellan, designed and developed at the McGill University in Canada [16]. The Magellan has four components: a standard nerve block needle and a syringe mounted via a custom clamp to a robotic arm (JACO arm, Kinova, Canada), an ultrasound machine, a joystick (Thrust Master, New York, USA), and a control software. This system, shown in Fig. 2, was designed to work with any ultrasound machine with a video output [17]. The ultrasound video output is captured and displayed on the user interface of the control software. The system is provided with safety features which 546
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FIGURE 2. The Magellan robotic nerve block system. Reproduced with permission from [17].
pose no risk for patients in the case of errors or failure [16]. This system was tested in 13 patients undergoing surgery below the knee under sciatic nerve block anesthesia [18 ]. Nerve identification was performed manually using a standard ultrasound probe. Once the sciatic nerve was identified, the probe was held in position and the Magellan was operated by a trained anesthesiologist. A Tuohy needle was attached to a 50-ml syringe of bupivacaine 0.25% (35 ml), which was attached, in turn, to one end of the robotic arm using a customized holder. For every 10 ml of injected bupivacaine, the needle was repositioned to obtain an optimal ultrasound view of the local anesthetic spread. Among the 13 patients enrolled in the study, three underwent bilateral lower limb surgery, performing a total of 16 blocks. All 16 robot-assisted nerve blocks were successful. They had a local anesthetic spread around the nerve sheath, directly visualized on the ultrasound video. Mean performance time resulted to be 189 s, and no complication occurred [18 ]. In addition, the Magellan system has been recently shown to be a valid means for training in regional anesthesia. In five persons with a different level of training in nerve blocks, repeated trials of ultrasound-guided nerve blocks on a phantom showed a negative slope of their learning curve, which means a decrease in the time to perform a nerve block for each consecutive trial. This decrease was significantly greater for robot-assisted blocks than manual procedures [19]. Automation in regional anesthesia also concerns the detection of peripheral nerves in ultrasound images, as part of the decision-making process concerning the performance of a peripheral nerve block. The accuracy in the detection of the target nerve is critical for the proper distribution of the local anesthetic and the success of the block. Software has been developed to automatically detect peripheral nerves in ultrasound images, and its &&
&&
Volume 27 Number 5 October 2014
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Robotics and regional anesthesia Wehbe et al.
performance evaluated in agreement with that of an experienced anesthesiologist [20]. Tests were performed in 80 ultrasound images of the sciatic nerve at the popliteal fossa. Firstly, the authors verified whether there had been any overlap between the manually and the automatically detected area; secondly, they measured the overlap in such terms that the smaller the difference, the higher the accuracy. As a result, they found a percentage of overlap between the manual and the automatic way ranging from 69 to 100%, with a difference in the measurement ranging from 1 ml to 1 cm. This difference can be clinically acceptable for the correct spreading of the local anesthetic all around the nerve [20]. A subsequent study confirmed this percentage of overlap, identifying a difference of 0.4 cm in 98% of overlap between manual and automated detected area, which is clinically acceptable for nerve block needle placement [21]. That being so, it is possible that in the future nerve blocks will be performed in a completely automatic way, from nerve detection to the puncture and the injection of local anesthetics.
AUTOMATION AND PATIENT SAFETY In the 2000 report, To Err Is Human [22], the Institute of Medicine estimated that between 44 000 and 98 000 Americans die each year as a result of medical errors. Errors are viewed as unsafe acts arising primarily from aberrant mental process such as forgetfulness, inattention, poor motivation, carelessness, negligence, and recklessness [23]. The main source of human error in anesthesia is the high number of variables an anesthesiologist has to monitor: up to 100 parameters, whereas the human brain cannot simultaneously process more than four or five parameters [24]. Automation and decision support systems could be used to reduce medical errors. Automated systems provide increased precision and faster computation compared with humans, they also do not fatigue. Decision support systems reduce the amount of data clinicians have to monitor; they notify clinicians when critical events occur with treatment options, allowing them to be alert at all time during surgery. According to a recent review analyzing 70 studies, clinical practices were improved by 68% of cases when decision support systems were integrated into the clinicians’ work [25].
CONCLUSION Robots in anesthesia can be separated into two types: pharmacological robots and manual robots. Pharmacological robots are mainly closed-loop
systems that help to administer anesthetic drugs, whereas manual robots are robots that are used to support or replace a manual gesture performed by anesthesiologists. There are several challenges facing further implementation of robotics in regional anesthesia and sedation: compared with surgical robotics, there is a relatively small amount of research being done in this field. Consequently, little funding opportunities exist for these projects. Also, a wide range of regulatory, business, and clinical issues need to be resolved before anesthetic robots can be introduced into the market and incorporated into general practice [26]. Acknowledgements None. Conflicts of interest There are no conflicts of interest.
REFERENCES AND RECOMMENDED READING Papers of particular interest, published within the annual period of review, have been highlighted as: & of special interest && of outstanding interest 1. Kwoh YS, Hou J, Jonckheere EA, Hayati S. A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery. IEEE Trans Biomed Eng 1988; 35:153–160. 2. Himpens J, Leman G, Cadiere GB. Telesurgical laparoscopic cholecystectomy. Surg Endosc 1998; 12:1091. 3. Satava RM. Surgical robotics: the early chronicles: a personal historical perspective. Surg Laparosc Endosc Percutan Tech 2002; 12:6–16. 4. Schwilden H. A general method for calculating the dosage scheme in linear pharmacokinetics. Eur J Clin Pharmacol 1981; 20:379–386. 5. Larson MD. History of anesthetic practice. In: Miller RD, editor. Miller’s anesthesia, 7th ed. Philadelphia: Churchill Livingstone; 2009. volume 1, chapter 1. 6. Hemmerling TM. Automated anesthesia. Curr Opin Anaesthesiol 2009; 22:757–763. 7. Ogata K. Modern control engineering. Upper Saddle River, New Jersey: Prentice-Hall; 2010. 8. Pambianco DJ, Whitten CJ, Moerman A, et al. An assessment of computerassisted personalized sedation: a sedation delivery system to administer propofol for gastrointestinal endoscopy. Gastrointest Endosc 2008; 68:542–547. 9. Pambianco DJ, Vargo JJ, Pruitt RE, et al. Computer-assisted personalized sedation for upper endoscopy and colonoscopy: a comparative, multicenter randomized study. Gastrointest Endosc 2011; 73:765–772. 10. Technology ASGE Commitee. Computer-assisted personalized sedation. Gastrointest Endosc 2011; 73:423–427. 11. http://www.fda.gov/medicaldevices/productsandmedicalprocedures/device approvalsandclearances/recently-approveddevices/ucm353950.htm [Accessed 20 July 2014] 12. Cleary K, Stoianovici D, Patriciu A, et al. Robotically assisted nerve and facet blocks: a cadaveric study. Acad Radiol 2002; 9:821–825. 13. Cleary K, Watson V, Lindisch D, et al. Precision placement of instruments for minimally invasive procedures using a ‘needle driver’ robot. Int J Med Robot Comp 2005; 1:40–47. 14. Glozman D, Shoham M. Image-guided robotic flexible needle steering. IEEE Trans Robot 2007; 23:459–467. 15. Tighe PJ, Badiyan SJ, Luria IBS, et al. Robot-assisted regional anesthesia: a simulated demonstration. Anesth Analg 2010; 111:813–816. 16. Morse J, Wehbe M, Taddei R, et al. Magellan: technical description of a new system for robot-assisted nerve blocks. J Comput 2013; 8:1401– 1405. 17. Hemmerling TM, Terrasini N, Cyr S. Robotization. In: Ehrenfeld JM, Cannessions M, editors. Monitoring technologies in acute care environments. Springer; 2014. pp. 409–419.
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Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Regional anesthesia 18. Hemmerling TM, Taddei R, Wehbe M, et al. First robotic ultrasound-guided nerve blocks in humans using the Magellan system. Anesth Analg 2013; 116:491–494. This article describes the clinical application of a robot-assisted nerve block systems performed on humans.
&&
19. Morse J, Terasini N, Wehbe M, et al. Comparison of success rates, learning curves, and inter-subject performance variability of robot-assisted and manual ultrasound-guided nerve block needle guidance in simulation. Br J Anaesth 2014; 112:1092–1097. 20. Wehbe M, Philippona C, Morse J, et al. Automated versus manual detection of the sciatic nerve. Abstract of the American Society of Anesthesiologists 2012. Available at: http://www.asaabstracts.com/strands/asaabstracts/abstract.htm; jsessionid¼6FFCEE5B5EE0B6AED88460043E158AC1?year¼2012&index ¼8&absnum¼6638. [Accessed 8 May 2014]
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21. Wehbe M, Morse J, Zaouter C, et al. Automatic ultrasound nerve detection. Abstract of the Society for Technology in Anesthesia 2012. Available at: file:///Users/tmhemmerling/Downloads/Abstracts_of_Papers_Presented_at_ the_2012_Annual.1.pdf. [Accessed 8 May 2014] 22. Kohn LT, Corrigan JM, Donaldson MS. To err is human: building a safer health system. Washington, DC: The National Academies Press; 2000. 23. Reason J. Human error: models and management. Br Med J 2000; 320:768– 770. 24. Halford GS, Baker R, McCredden JE, Bain JD, et al. How many variables can humans process? Psychol Sci 2005; 16:70–76. 25. Kawamoto K, Houlihan CA, Balas EA, et al. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. Br Med J 2005; 330:765. 26. Manberg PJ, Vozella CM, Kelley SD. Regulatory challenges facing closed-loop anesthetic drug infusion devices. Clin Pharmacol Ther 2008; 84:166–169.
Volume 27 Number 5 October 2014
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Robotics and regional anesthesia Mohamad Wehbe a, Marilu Giacalone b, and Thomas M. Hemmerling c
Purpose of review Robots in regional anesthesia are used as a tool to automate the performance of regional techniques reducing the anesthesiologist’s workload and improving patient care. The purpose of this review is to show the latest findings in robotic regional anesthesia. Recent findings The literature separates robots in anesthesia into two groups: pharmacological robots and manual robots. Pharmacological robots are mainly closed-loop systems that help in the titration of anesthetic drugs to patients undergoing surgery. Manual robots are mechanical robots that are used to support or replace the manual gestures performed by anesthesiologists. Although in the last decade researchers have focused on the development of decision support systems and closed-loop systems, more recent evidence supports the concept that robots can also be useful in performing regional anesthesia techniques. Summary Robots can improve the performance and safety in regional anesthesia. In this review, we present the developments made in robotic and automated regional anesthesia, and discuss the current state of research in this field. Keywords closed-loop systems for sedation, robot-assisted intubation, robot-assisted nerve block, robotic anesthesia
INTRODUCTION
AUTOMATED SYSTEMS FOR SEDATION
The notion of robots in medicine is not new, and the history of surgical robots began in 1985 with the Unimation Puma 200 robot used to perform computed-tomography-guided brain tumor biopsies [1]. In April 1997, the first robot-assisted surgical procedure on a patient was performed in Brussels, Belgium [2,3]. In anesthesia, however, development was slower, and the first attempt in automation was the introduction of computerized pharmacokinetic model-driven continuous infusion pumps [4,5]. These attempts resulted in the first targetcontrolled infusion (TCI) device for administering propofol. Research has focused on the closed-loop systems in anesthesia. In contrast to TCI, closedloop systems control the drug dose (effect) by continuously checking the controlling parameter, such as the depth of consciousness for propofol infusion. Although their performance was tested clinically, and showed to be on par with manual anesthesia, closed-loop systems are still used for research purposes and have not yet been used in clinical practice [6]. More recently, research has demonstrated that robots may also be useful in regional anesthesia.
Most regional anesthesia techniques require sedation. Automated systems for anesthesia are closedloop systems; these systems are a feedback control system that monitors one or more input variables, the output signal (or a function of the output signal) and reduces the error (difference between the input and output) to bring the output of the system to a desired value [7]. A block diagram of a closed-loop system is illustrated in Fig. 1. The only commercially available automated system for sedation at present is the SEDASYS system (Ethicon Endo-Surgery, Cincinnati, Ohio, USA), which is a computer-assisted personalized sedation
www.co-anesthesiology.com
a
Division of Experimental Surgery, McGill University, Montreal, Canada, Department of Anesthesia, University Pisa, Pisa, Italy and cDepartment of Anesthesia, Division of Experimental Surgery & Arnold and Blema Steinberg Medical Simulation Centre, McGill University, Montreal, Canada b
Correspondence to Thomas M. Hemmerling, MD, DEAA, Montreal General Hospital, Room C10 - 153, 1650 Cedar Avenue, Montreal, QC, Canada H3G 1A4. Tel: +1 514 934 1934 ext 43677; e-mail: [email protected]; website: www.newanesthesia.com Curr Opin Anesthesiol 2014, 27:544–548 DOI:10.1097/ACO.0000000000000117 Volume 27 Number 5 October 2014
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Robotics and regional anesthesia Wehbe et al.
KEY POINTS The application of closed-loop systems improves the titration of drugs administered in all phases of sedation, based on the objective data derived from monitoring. Robotic assistance in anesthesia consists of mechanical robots, which support or replace the human gestures in several fields of regional anesthesia. Robotic neuraxial and peripheral nerve blocks are as feasible as manual blocks, with increased accuracy and precision, as well as autocontrolling and provision of training tools.
system [8,9]. The SEDASYS system integrates the monitoring of pulse oximetry, capnometry, ECG, noninvasive blood pressure, and patient responsiveness, with the delivery of oxygen and propofol [8]. The SEDASYS system is designed to facilitate the safe administration of propofol to induce minimalto-moderate sedation to relatively healthy adults undergoing elective colonoscopy or esophagogastroduodenoscopy (EGD) [10]. The SEDASYS system is operated by a physician-led team whose members are trained in various aspects of general anesthesia [10]. The device also incorporates an automated responsiveness monitor (ARM) to assess patient responsiveness. The ARM delivers at preset time intervals, an auditory request asking the patient to squeeze the handset he or she is holding, together with a mild vibration. If the patient fails to respond by squeezing the handset, the auditory request becomes louder and the vibration more vigorous. The ARM calculates the patient’s response time [10]. The SEDASYS system will not allow propofol infusion unless oxygen is being delivered to the patient. Signs of oversedation trigger the system to increase the oxygen delivery rate. Also, the system automatically decreases the propofol rate when responsiveness to the ARM is lost [10]. In a study published in 2011 by Pambianco et al. [9], the SEDASYS system was used to perform sedation on 496 patients undergoing routine EGD and colonoscopy. A total of 504 patients of the control group received traditional sedation with benzodiazepine and opioids. The
Input
+
–
study proved that the SEDASYS system reduces the risks of oversedation, and patients receiving sedation with the SEDASYS system experienced fewer and less significant oxygen desaturation than those in the control group. The US Food and Drug Administration granted premarket approval on May 3, 2013 and approval of modifications on June 23, 2014 [11].
ROBOTIC ASSISTANCE IN ANESTHESIA The use of robots has been successfully applied both clinically in endotracheal intubation and as a teaching tool. Another area in which robotic assistance is being developed is represented by regional anesthesia. One of the first attempts to apply robotics to regional anesthesia was carried out by Cleary et al. [12], who developed a robotic needle driver for spinal blocks (nerve roots and facet blocks). Their equipment consisted of a robotic needle driver mounted on an interventional table and a joystick located in a control panel separated from the robot. A robot controller with safety features was installed in a computer and connected to the robot by cables. First, the authors identified 12 targets in the paraspinal space of a cadaver by putting 12 metal markers in six nerve roots and six facet roots, three for each side, and verified the correct position of the targets through fluoroscopy. Second, they positioned a needle within 3 mm from the target orienting the robotic driver by the joystick. Needle trajectory and depth were guided by fluoroscopy. As a result, all needles were located within 3 mm from the target, with a mean distance of 1.44 0.66 mm [12]. Later, the same group applied this device to the performance of spinal blocks in patients [13]. They compared the performance of such blocks in two groups of patients, 10 undergoing manual block and 10 undergoing robotic block with the equipment described above. The results showed similar accuracy and post-treatment pain score between the two groups, concluding that robotic spinal blocks are as feasible as manual blocks [13]. Subsequently, other researchers developed a more general device for the guidance of soft-tissue injections, as regional anesthesia is [14]. In this
Controller
Actuator
Output
FIGURE 1. Block diagram of a simple closed-loop control system.
0952-7907 ß 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
www.co-anesthesiology.com
545
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Regional anesthesia
study, first, they established a control algorithm given a predetermined needle trajectory, then, a robotic arm (C-Arm) drove a flexible, spinal needle toward the target (an animal specimen) and performed the puncture under a closed-loop control from a software guided by real-time X-ray images. This system aimed to create a pathway for needle driving given the initial coordinates and to optimize the plan for minimal pressure on tissues, also taking into account the possible obstacles [14]. Other applications of robotics to regional anesthesia have concerned peripheral nerve blocks, with subsequent development. In a similar fashion to what was mentioned above, Tighe et al. [15] used the da Vinci Surgical System to perform a robotically assisted ultrasound-guided nerve block. This was done in a simulated environment as a single-injection nerve block, and placement of a perineural catheter into an ultrasound phantom under ultrasound guidance. As with their other study mentioned above, they used the da Vinci S Surgical System to perform the procedure. They tested first the ability of the robotic system to manipulate the equipment involved in a peripheral nerve block. After this test, they placed the ultrasound phantom on an operating room stretcher under the da Vinci. They manually placed the ultrasound probe, and after identifying the simulated perineural structures in the phantom, they stabilized the probe with the da Vinci system. Three arms were used to maneuver most of the equipment relevant to the nerve block. The ultrasound probe was connected to the da Vinci in order to allow for simultaneous visualization of ultrasound images and da Vinci video input. This video feed was also used to place the perineural catheter by means of a Tuohy needle [15]. Their study proved that robotically assisted regional anesthesia is feasible; however, the use of a multimilliondollar system to perform regional anesthesia, along with the number of personnel needed to accomplish this task (two engineers, an anesthesiologist, and a urologist), is not practical. A system consisting of equipment specifically designed to perform robot-assisted, ultrasoundguided nerve blocks is the Magellan, designed and developed at the McGill University in Canada [16]. The Magellan has four components: a standard nerve block needle and a syringe mounted via a custom clamp to a robotic arm (JACO arm, Kinova, Canada), an ultrasound machine, a joystick (Thrust Master, New York, USA), and a control software. This system, shown in Fig. 2, was designed to work with any ultrasound machine with a video output [17]. The ultrasound video output is captured and displayed on the user interface of the control software. The system is provided with safety features which 546
www.co-anesthesiology.com
FIGURE 2. The Magellan robotic nerve block system. Reproduced with permission from [17].
pose no risk for patients in the case of errors or failure [16]. This system was tested in 13 patients undergoing surgery below the knee under sciatic nerve block anesthesia [18 ]. Nerve identification was performed manually using a standard ultrasound probe. Once the sciatic nerve was identified, the probe was held in position and the Magellan was operated by a trained anesthesiologist. A Tuohy needle was attached to a 50-ml syringe of bupivacaine 0.25% (35 ml), which was attached, in turn, to one end of the robotic arm using a customized holder. For every 10 ml of injected bupivacaine, the needle was repositioned to obtain an optimal ultrasound view of the local anesthetic spread. Among the 13 patients enrolled in the study, three underwent bilateral lower limb surgery, performing a total of 16 blocks. All 16 robot-assisted nerve blocks were successful. They had a local anesthetic spread around the nerve sheath, directly visualized on the ultrasound video. Mean performance time resulted to be 189 s, and no complication occurred [18 ]. In addition, the Magellan system has been recently shown to be a valid means for training in regional anesthesia. In five persons with a different level of training in nerve blocks, repeated trials of ultrasound-guided nerve blocks on a phantom showed a negative slope of their learning curve, which means a decrease in the time to perform a nerve block for each consecutive trial. This decrease was significantly greater for robot-assisted blocks than manual procedures [19]. Automation in regional anesthesia also concerns the detection of peripheral nerves in ultrasound images, as part of the decision-making process concerning the performance of a peripheral nerve block. The accuracy in the detection of the target nerve is critical for the proper distribution of the local anesthetic and the success of the block. Software has been developed to automatically detect peripheral nerves in ultrasound images, and its &&
&&
Volume 27 Number 5 October 2014
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Robotics and regional anesthesia Wehbe et al.
performance evaluated in agreement with that of an experienced anesthesiologist [20]. Tests were performed in 80 ultrasound images of the sciatic nerve at the popliteal fossa. Firstly, the authors verified whether there had been any overlap between the manually and the automatically detected area; secondly, they measured the overlap in such terms that the smaller the difference, the higher the accuracy. As a result, they found a percentage of overlap between the manual and the automatic way ranging from 69 to 100%, with a difference in the measurement ranging from 1 ml to 1 cm. This difference can be clinically acceptable for the correct spreading of the local anesthetic all around the nerve [20]. A subsequent study confirmed this percentage of overlap, identifying a difference of 0.4 cm in 98% of overlap between manual and automated detected area, which is clinically acceptable for nerve block needle placement [21]. That being so, it is possible that in the future nerve blocks will be performed in a completely automatic way, from nerve detection to the puncture and the injection of local anesthetics.
AUTOMATION AND PATIENT SAFETY In the 2000 report, To Err Is Human [22], the Institute of Medicine estimated that between 44 000 and 98 000 Americans die each year as a result of medical errors. Errors are viewed as unsafe acts arising primarily from aberrant mental process such as forgetfulness, inattention, poor motivation, carelessness, negligence, and recklessness [23]. The main source of human error in anesthesia is the high number of variables an anesthesiologist has to monitor: up to 100 parameters, whereas the human brain cannot simultaneously process more than four or five parameters [24]. Automation and decision support systems could be used to reduce medical errors. Automated systems provide increased precision and faster computation compared with humans, they also do not fatigue. Decision support systems reduce the amount of data clinicians have to monitor; they notify clinicians when critical events occur with treatment options, allowing them to be alert at all time during surgery. According to a recent review analyzing 70 studies, clinical practices were improved by 68% of cases when decision support systems were integrated into the clinicians’ work [25].
CONCLUSION Robots in anesthesia can be separated into two types: pharmacological robots and manual robots. Pharmacological robots are mainly closed-loop
systems that help to administer anesthetic drugs, whereas manual robots are robots that are used to support or replace a manual gesture performed by anesthesiologists. There are several challenges facing further implementation of robotics in regional anesthesia and sedation: compared with surgical robotics, there is a relatively small amount of research being done in this field. Consequently, little funding opportunities exist for these projects. Also, a wide range of regulatory, business, and clinical issues need to be resolved before anesthetic robots can be introduced into the market and incorporated into general practice [26]. Acknowledgements None. Conflicts of interest There are no conflicts of interest.
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