THE INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY ORIGINAL Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. Published online 16 April 2014 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/rcs.1586
ARTICLE
Quantitative assessment of manual and robotic microcannulation for eye surgery using new eye model
Shinichi Tanaka1* Kanako Harada1 Yoshiki Ida1 Kyohei Tomita2 Ippei Kato2 Fumihito Arai2 Takashi Ueta3 Yasuo Noda3 Naohiko Sugita1 Mamoru Mitsuishi1
Abstract Background Microcannulation, a surgical procedure for the eye that requires drug injection into a 60–90 μm retinal vein, is difficult to perform manually. Robotic assistance has been proposed; however, its effectiveness in comparison to manual operation has not been quantified. Methods An eye model has been developed to quantify the performance of manual and robotic microcannulation. The eye model, which is implemented with a force sensor and microchannels, also simulates the mechanical constraints of the instrument’s movement. Ten subjects performed microcannulation using the model, with and without robotic assistance.
1
Department of Mechanical Engineering, The University of Tokyo, Japan
2
Department of Mechanical Science and Engineering, Nagoya University, Japan
3
Department of Ophthalmology, The University of Tokyo, Japan *Correspondence to: S. Tanaka, Room 71C1, Engineering Building #2, 7-3-1, Hongo, Bunkyo-ku, Tokyo-to, 1138656, Japan. E-mail: [email protected]
Results The results showed that the robotic assistance was useful for motion stability when the drug was injected, whereas its positioning accuracy offered no advantage. Conclusions An eye model was used to quantitatively assess the robotic microcannulation performance in comparison to manual operation. This approach could be valid for a better evaluation of surgical robotic assistance. Copyright © 2014 John Wiley & Sons, Ltd. Keywords systems
robotic surgery; regulatory science; eye surgery; microelectromechanical
Introduction
Accepted: 24 February 2014
Copyright © 2014 John Wiley & Sons, Ltd.
Microcannulation is a relatively new procedure that was developed to treat retinal vein occlusion, which can lead to loss of vision (1). To perform microcannulation, a surgeon positions the tip of a micropipette (< 30 μm) at the target retinal vein (< 100 μm) and holds it at this position for > 30 s to inject a thrombolytic drug, as illustrated in Figure 1a. The tip of the micropipette should be precisely controlled and stably held, and the force applied on the eye ground should be minimized. The manipulation of the micropipette in the eye cavity is difficult and is affected by the surgeon’s hand tremor, which has an amplitude of > 100 μm (2). To assist in such challenging tasks, several surgical robots have been developed, such as Steady-Hand (3) and Micron (4). We have also developed a master–slave microsurgical robotic system (5).
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Quantitative assessment of manual and robotic microcannulation
Figure 1. (a) Microcannulation; (b) accuracy measurement using graph paper; (c) in vitro test using an excised porcine eye
These robots have been designed to filter out the motion caused by the surgeon’s hand tremor and to improve the motion resolution and accuracy. In general, the feasibility of such surgical robots is evaluated in two steps: an evaluation of the fundamental functionality and in vitro/in vivo demonstrations. The fundamental functionalities of surgical robots, such as the working range, accuracy and force, are evaluated using sensors and simple models [see e.g. (6,7)] to show that the robots are capable of performing target tasks. Thereafter, in vitro and/or in vivo experiments that simulate actual surgery are conducted, using excised organ models or animal models to demonstrate that the functionalities are valid in a realistic scenario [see e.g. (8,9)]. We have also conducted these experiments to evaluate our master–slave microsurgical robotic system. Figure 1b shows the functionality evaluation, specifically the accuracy measurement, and Figure 1c shows an in vitro test using an excised porcine eye. The functionality test demonstrated that the master–slave microsurgical robotic system had a positioning accuracy of 69 μm (10). It was also found that the system contributed to better motion stability as a result of hand tremor cancellation and motion scaling, which resulted in better positioning control, particularly in the depth direction, reducing the applied force by 78%. The in vitro microcannulation experiment using a micropipette with a diameter of 30 μm showed the feasibility of robotic microcannulation in 70, 90 and 110 μm retinal veins (5). These assessments successfully showed the effectiveness of robotic eye surgery, but its effectiveness in comparison to manual operation in a realistic surgical set-up must still be evaluated. A functionality evaluation employing sensors and simple models is not realistic but can provide quantitative evaluations. In contrast, in vitro and/or in vivo evaluations are more realistic, but they often lack quantitative evaluation criteria. In addition, the results are influenced by the individual differences in animal organs, and the experiments cannot be repeated. Therefore, an assessment method that employs a realistic artificial model is needed to quantify the effectiveness of robotic surgery in comparison Copyright © 2014 John Wiley & Sons, Ltd.
to manual operation before performing in vitro and/or in vivo evaluations. In this study, we developed a new artificial eye model that is capable of sensing the force at the eye ground to evaluate manual and robotic microcannulation in a more realistic set-up. This model also employed a retinal vein model that was fabricated using microelectromechanical system technology.
Materials and methods An eye model containing a force sensor and retinal vein model was developed. Ten subjects performed microcannulation using the eye model, with and without the master–slave microsurgical robotic system. The results were compared to quantify the differences in the success rate, task completion time and maximum force applied on the eye ground.
Eye model The eye model consists of a sclera model, retinal vein model, force sensor (load cell) and mechanism that uses a permanent magnet and metal sphere designed to simulate the rotational motion of the eye, as shown in Figure 2. The sclera model is made of natural rubber with a simulated Young’s modulus of 2.7 ± 1.4 MPa to mimic the
Figure 2. Eye model: (a) sectional view; (b) fabricated model Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
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mechanical properties and size of the human sclera (11). Table 1 lists the specifications of the sclera model. A hole located on top of the model is used to insert a micropipette and to observe the microcannulation procedure with a microscope. The load cell (TC-USR-17, TEAC, Japan) measures the force applied on the eye ground of the model, and the sensing range is –300 to 300 mN, with a resolution of 0.03 mN. The eye model is placed under the facial cover of the commercial eye surgery training kit KITARO DryLab (Frontier Vision Co., Japan), as shown Table 1. Specifications of sclera model Material Thickness Hardness Outer diameter
Natural rubber 1.5 mm A 50 24 mm
Figure 3. Eye model with facial cover
in Figure 3, to simulate the geometrical constraints of the human facial shape. This also makes it possible to simulate the surgeon’s hand positioning during manual operation, which involves the surgeon placing his or her hand on the patient’s face to suppress hand tremor. The retinal vein model is composed of either 60 or 90 μm microchannels to simulate the diameter of the target retinal vein. The channels were fabricated using polydimethyl siloxane (PDMS) to simulate the feeling of puncturing a retinal vein. Regarding the fabrication methods for microvessels, Nakano et al. (12) proposed the fabrication of multiscale transparent arteriole and capillary vessel models with circular cross-sections of 10–500 μm, using photolithography. However, their fabrication process was complex and difficult. We therefore simplified the photolithography process and fabricated a retinal vein model with rectangular cross-sections, as shown in Figure 4. Microchannels were fabricated by replica moulding, using a PDMS sheet. First, a negative photoresist, SU-8 (Kayaku MicroChem Co.), was spincoated onto a Si wafer and baked on a hotplate. The wafer was then exposed to UV light through a photomask with a microchannel pattern, using a Karl Suss MJB3 Mask Aligner (SUSS Micro Tec AG), and subjected to a post-exposure bake (PEB). After the PEB, the wafer was developed in a PM thinner and rinsed in isopropyl alcohol. Thereafter, the prepolymer, PDMS Sylpot 184 (Dow Corning Co.), was poured onto the SU-8 master and cured at 90 °C for 15 min in a convection oven. After removing the cured PDMS sheet with the microchannels from the master, the sheet and a thin PDMS membrane (thickness 13 μm) were
Figure 4. Procedure to fabricate retinal vein model Copyright © 2014 John Wiley & Sons, Ltd.
Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
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Quantitative assessment of manual and robotic microcannulation
treated in air plasma using a plasma system, CUTE-MP/R (Femto Science Co.). Then, the treated surface of the cured PDMS sheet with the microchannels and the treated surface of the thin PDMS membrane were placed in contact. After baking at 145 °C for 15 min in a convection oven, the PDMS sheet with the microchannels was strongly bonded to the PDMS membrane. The size of the microchannels could be easily changed by redesigning the photomask. The developed microchannels are shown in Figure 5.
operator releases the foot pedal. The slave manipulator (5) also has seven DoFs. This manipulator has a remote centre of motion (RCM) at the cross-point of the α and β axes. By matching the RCM point with the robotic tool insertion point (i.e. the insertion point of the cannula) in the sclera, the operator can perform tasks without being aware of the mechanical constraints at the insertion point. Instead of a gripper, a micropipette is attached to this slave manipulator when a surgeon performs microcannulation.
Master–slave microsurgical robotic system
Experimental set-up
The master–slave microsurgical robotic system comprises a master manipulator and slave manipulator, as shown in Figure 6. The master manipulator (13) is composed of a commercial haptic device, Phantom Premium 1.0 (Sensable, USA) and a custom-made stylus with highresolution encoders. This manipulator has seven degrees of freedom (DoFs), including the gripping DoF, and measures the surgeon’s hand motion. The measured motion is scaled down with a motion-scaling ratio of 40:1 and sent to the slave manipulator using UDP/IP communication. A foot pedal is attached to the master manipulator, and the master–slave communication is terminated when the
Figure 5. Artificial retinal vein model: (a) 60 μm (pitch 200 μm); (b) 90 μm (pitch 200 μm)
The experimental set-ups for manual and robotic microcannulation are shown in Figure 7. The microcannulation was observed using a microscope and displayed on a 3D monitor. A micropipette with a 20 μm diameter tip was fabricated, and a coloured ethanol solution was used to simulate the thrombolytic drug injection. Eight engineering students and two ophthalmologists performed microcannulation, with and without the robotic system. First, the micropipette’s tip was set 1 mm away from the specified target point in a microchannel of the retinal vein model. Then, the subject was asked to move the micropipette to puncture the microchannel. Once the micropipette’s tip punctured the thin membrane of the microchannel and was properly inserted, the ethanol solution was manually delivered using the microinjector. The injection was visually detected by the colour of the solution. The subject continued to hold the micropipette in position for 30 s to simulate the actual drug injection time required for the treatment of retinal vein occlusion. The puncture and drug injection were considered successful when no leakage of the solution was observed. The experiment was performed for 60 and 90 μm microchannels and was repeated twice. The success rate, task completion time for the injection process, drug injection time and maximum force applied
Figure 6. Master–slave microsurgical robotic system: (a) master manipulator; (b) slave manipulator Copyright © 2014 John Wiley & Sons, Ltd.
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Figure 7. Experimental set-up: (a) for manual operation; (b) for robotic operation (b1, master manipulator; b2, slave manipulator)
to the eye ground were measured, and a comparison was made between the manual and robotic microcannulation tests. The drug injection time for a successful injection process was 30 s, as designed. When solution leakage was observed as a result of hand tremors causing the unwanted removal of the micropipette, the drug injection was immediately terminated. The statistical significances of the differences in the measured times and forces were analysed using a paired t-test.
Results The experimental results from the puncture process and the drug injection process were analysed. The puncture Table 2. Success rate of puncture Diameter (μm)
Method
Success rate (%)
60
Manual Robot Manual Robot
90 95 95 90
90
process was influenced largely by the accuracy and motion resolution, whereas the drug-injection process was mainly affected by the motion stability.
Puncture process Table 2 lists the puncture success rate and Tables 3 and 4 list the task completion times and the applied maximum forces for puncture, respectively. Figure 8 illustrates the averages and standard deviations (SDs) of the results. The manual and robot microcannulation tasks had success rates > 90%. The task completion time for the robotic microcannulation in the 60 μm microchannels was twice that of the manual task (p < 0.05). In the case of the 90 μm microchannels, the task completion time was also twice that of the manual task (p < 0.01). The applied maximum force for the robotic operation decreased to one-third that for the manual operation (p < 0.01) in the 60 μm microchannels and decreased to half that for the manual operation (p < 0.01) in the 90 μm microchannels.
Table 3. Task completion time (s) for puncture Manual operation 60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2 Average SD
Robotic operation 90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
11.3 11.6 5.4 12.7 15.8 13.4 15.8 12.7 11.3 6.6
7.3 16.9 12.5 7.1 58.2 9.3 16.4 27.5 24.1 8.0
12.9 17.0 7.2 34.4 22.2 35.4 14.7 18.1 9.6 8.1
15.5 20.2 15.4 17.3 36.4 12.1 10.5 11.2 3.7 4.3
20.8 12.9 19.5 117.4 32.5 28.5 25.5 78.8 30.2 31.4
35.3 14.3 19.8 58.0 35.4 38.0 23.1 31.3 26.5 9.9
45.0 35.9 10.5 36.9 46.8 96.0 16.2 24.4 14.4 30.2
37.8 61.1 54.8 25.8 29.6 42.0 33.3 29.1 17.4 19.3
15 12
Copyright © 2014 John Wiley & Sons, Ltd.
16 9.6
34 25
35.3 19.6
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Quantitative assessment of manual and robotic microcannulation Table 4. Maximum applied force (mN) for puncture Manual operation
Robotic operation
60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2 Average SD
90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
15.0 20.8 8.2 10.8 38.6 21.8 37.6 32.5 12.4 13.4
18.8 30.1 23.8 19.0 32.7 22.2 7.1 31.2 13.0 17.2
24.2 30.1 9.6 17.1 31.9 16.4 15.0 32.1 12.8 23.2
18.9 24.3 25.6 20.3 55.3 15.6 15.9 40.1 6.8 20.2
6.4 6.4 4.7 6.4 15.1 9.6 12.2 12.5 3.9 4.5
7.6 7.6 5.1 13.6 13.1 9.5 12.6 11.1 4.4 5.5
10.3 11.0 3.5 7.6 10.4 15.0 15.9 11.0 3.0 4.3
2.7 13.4 8.7 17.7 20.6 20.1 19.8 18.0 3.9 6.3
21 9.6
23 11
8.6 3.6
11 6.2
Figure 8. Experimental results for puncture: (a) task completion time; (b) maximum applied force
Drug injection process Table 5 lists the success rate for drug injection, and Tables 6 and 7 list the task completion times and applied maximum forces for puncture, respectively. Figure 9 illustrates the averages and SDs of the results. The drug injection success rate for the robotic operation was much higher than that for the manual operation. The drug injection time for the robotic operation was one and a half times that for the manual operation (p < 0.01 in the 60 μm microchannels and p < 0.05 in the 90 μm microchannels); the longer drug injection time is preferable for successful drug delivery. In the robotic operation, the task completion time reached the required drug injection time of 30 s in 18/19 trials in the 60 μm microchannels and 17/18 trials in the 90 μm microchannels. The maximum applied force for the robotic operation for drug Table 5. Success rate for drug injection Diameter (μm)
Method
Success rate (%)
60
Manual Robot Manual Robot
28 95 47 94
90
Copyright © 2014 John Wiley & Sons, Ltd.
injection decreased to one-third that for the manual operation (p < 0.01 in the 60 μm microchannels and p < 0.05 in the 90 μm microchannels); the reduced maximum applied force is also preferable for safe surgery.
Discussion The puncture process was successful in both the manual and the robotic microcannulation tasks, suggesting that the accuracy was sufficient in the manual operation and did not need to be improved by robotic assistance. This was because the mechanical constraints imposed on the cannula served as a tremor filter, which can explain how some surgeons can perform microcannulation regardless of hand tremor, although it is considered to be very difficult. In contrast, the task completion time for the puncture process was longer for the robotic microcannulation because the motion-scaling ratio was 40:1, and the robotic operation required a large hand motion at the master manipulator. The force applied on the eye ground was significantly smaller for robotic microcannulation because the motion stability was better. The robotic assistance was more useful for the drug-injection process, as demonstrated by the higher success rates. Moreover, the drug injection times in some of the manual tasks Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
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216 Table 6. Task completion time (s) for drug injection (N/A for unsuccessful puncture) Manual operation 60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2
Robotic operation 90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
11.2 7.8 30.0 24.8 3.3 4.0 N/A 29.0 30.0 9.5
5.5 26.4 30.0 16.9 2.8 20.6 N/A 18.5 30.0 30.0
10.0 16.0 N/A 30.0 2.4 3.2 30.0 5.4 30.0 30.0
11.1 23.2 30.0 27.3 30.0 7.8 30.0 9.5 30.0 30.0
30.0 30.0 N/A 30.0 30.0 30.0 30.0 30.0 30.0 30.0
4.4 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0
30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0
N/A 25.8 30.0 30.0 30.0 30.0 N/A 30.0 30.0 30.0
Average SD
18 11
20 11
29 5.9
29.8 1.00
Table 7. Maximum applied force (mN) for drug injection (N/A for unsuccessful puncture) Manual operation 60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2 Average SD
Robotic operation 90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
8.4 17.9 36.7 12.2 5.4 6.9 N/A 43.0 9.1 1.6
2.6 8.2 22.3 18.0 29.8 19.8 N/A 15.9 8.4 13.4
7.1 1.8 N/A 25.7 8.0 9.4 14.6 41.1 9.1 12.3
8.4 3.3 28.9 13.1 21.7 2.8 13.6 31.1 12.5 7.3
4.2 1.7 N/A 6.1 5.2 7.4 2.7 3.3 4.3 4.0
2.3 2.9 7.1 3.3 4.1 8.2 3.2 2.5 3.5 5.5
3.7 2.4 5.9 2.4 7.1 5.1 14.4 2.9 3.4 4.8
N/A 2.0 5.9 12.9 7.2 6.7 N/A 2.8 4.3 2.1
16 11
14 11
4.3 1.8
5.3 3.5
Figure 9. Experimental results for drug injection: (a) drug injection time; (b) maximum applied force
did not reach the required time (30 s), and the micropipette’s tip was removed from the microchannel prematurely. This was because the hand tremor was too large to stabilize the micropipette in such small microchannels. In contrast, the robot held the micropipette for the required time without applying a large force on the eye ground. Although many studies related to eye surgery robots have focused on improving accuracy, these results suggest that Copyright © 2014 John Wiley & Sons, Ltd.
the accuracy during manual operation can be sufficient, although better accuracy could alleviate the difficulty of the procedure. In contrast, robotic assistance could be useful for improving motion stability, especially when the instrument needs to be held for a certain period of time. Experiments using artificial models that replicate the actual surgical constraints are helpful both to assess a manual operation to quantify the requirements of robotic surgery Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
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Quantitative assessment of manual and robotic microcannulation
and to quantitatively evaluate the positive and negative effects of robotic surgery prior to animal experiments.
Funding No specific funding.
Conclusions In this paper, we described a new microcannulation assessment method using an eye model containing microchannels and a force sensor. The microcannulation procedure and its constraints were simulated using the model, and experiments were performed to quantify the differences between manual and robotic operations. It was found that the robotic operation made a significant contribution by enhancing the motion stability. More specifically, in tasks using the master–slave microsurgical robotic system, the force applied on the eye ground was decreased by > 60% compared to manual operation, and drug injection was also more successful. Our future work will involve improving the retinal vein model to more precisely mimic the shape and mechanical properties of an actual human retinal vein. We are also planning to implement additional sensors to measure other important skill assessment factors, such as the force applied on the sclera.
Acknowledgements This study was partially supported by the Global Centre of Excellence for Mechanical Systems Innovation (GMSI) at the University of Tokyo and a Grant-in-Aid for Scientific Research (S) 23226006.
Conflict of interest The authors have stated explicitly that there are no conflicts of interest in connection with this article.
Copyright © 2014 John Wiley & Sons, Ltd.
References 1. Allf BE, de Juan E, Jr. In vivo cannulation of retinal vessels. Graefes Arch Clin Exp Ophthalmol 1987; 225(3): 221–225. 2. Singhy SPN. Physiological tremor amplitude during retinal microsurgery. In Proceedings of the IEEE 28th Annual Northeast Bioengineering Conference, 20–21 April 2002, Philadelphia, USA; 171–172. 3. Üneri A, Balicki MA, Hand J, et al. New Steady-Hand eye robot with micro-force sensing for vitreoretinal surgery. In Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, 1 September 2010, Tokyo, Japan; 26–29. 4. Yang S, MacLachlan RA, Riviere CN. Design and analysis of 6 DOF handheld micromanipulator. In Proceedings of the IEEE International Conference on Robotics Automation, 14–18 May 2012, Saint Paul, USA; 1946–1951. 5. Ida Y, Sugita N, Ueta T, et al. Microsurgical robotic system for vitreoretinal surgery. Int J Comput Assist Radiol Surg 2012; 7 (1): 27–34. 6. Ang WT, Riviere CN, Khosla P. An active hand-held instrument for enhanced microsurgical accuracy. Lect Notes Comput Sci 2000; 1935: 878–886. 7. Nakano T, Sugita N, Ueta T, et al. A parallel robot to assist vitreoretinal surgery. Int J Comput Assist Radiol Surg 2009; 4 (6): 517–526. 8. Fleming I, Balicki M, Koo J, et al. Cooperative robot assistant for retinal microsurgery. Med Image Comput Comput Assist Interv 2008; 11(pt 2): 543–550. 9. Jensen PS, Grace KW, Attariwala R, et al. Toward robot-assisted vascular microsurgery in the retina. Graefes Arch Clin Exp Ophthalmol 1997; 235(11): 696–701. 10. Noda Y, Ida Y, Tanaka S, et al. Impact of robotic assistance on precision of vitreoretinal surgical procedures. PLoS One 2013; 8 (1): e54116. 11. Friberg TR, Lace JW. A comparison of the elastic properties of human choroid and sclera. Exp Eye Res 1998; 47(3): 429–436. 12. Nakano T, Itoyama T, Yoshida K, et al. Multiscale fabrication of a transparent circulation type blood vessel simulator. Biomicrofluidics 2010; 4(4): 046505. 13. Kamei Y, Harada K, Tanaka S, et al. Master manipulator with high usability designed for microsurgical robotic system. In Proceedings of the 27th International Congress and Exhibition on Computer Assisted Radiology and Surgery, 26–29 June 2013, Heidelberg, Germany; S127–128.
Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
ARTICLE
Quantitative assessment of manual and robotic microcannulation for eye surgery using new eye model
Shinichi Tanaka1* Kanako Harada1 Yoshiki Ida1 Kyohei Tomita2 Ippei Kato2 Fumihito Arai2 Takashi Ueta3 Yasuo Noda3 Naohiko Sugita1 Mamoru Mitsuishi1
Abstract Background Microcannulation, a surgical procedure for the eye that requires drug injection into a 60–90 μm retinal vein, is difficult to perform manually. Robotic assistance has been proposed; however, its effectiveness in comparison to manual operation has not been quantified. Methods An eye model has been developed to quantify the performance of manual and robotic microcannulation. The eye model, which is implemented with a force sensor and microchannels, also simulates the mechanical constraints of the instrument’s movement. Ten subjects performed microcannulation using the model, with and without robotic assistance.
1
Department of Mechanical Engineering, The University of Tokyo, Japan
2
Department of Mechanical Science and Engineering, Nagoya University, Japan
3
Department of Ophthalmology, The University of Tokyo, Japan *Correspondence to: S. Tanaka, Room 71C1, Engineering Building #2, 7-3-1, Hongo, Bunkyo-ku, Tokyo-to, 1138656, Japan. E-mail: [email protected]
Results The results showed that the robotic assistance was useful for motion stability when the drug was injected, whereas its positioning accuracy offered no advantage. Conclusions An eye model was used to quantitatively assess the robotic microcannulation performance in comparison to manual operation. This approach could be valid for a better evaluation of surgical robotic assistance. Copyright © 2014 John Wiley & Sons, Ltd. Keywords systems
robotic surgery; regulatory science; eye surgery; microelectromechanical
Introduction
Accepted: 24 February 2014
Copyright © 2014 John Wiley & Sons, Ltd.
Microcannulation is a relatively new procedure that was developed to treat retinal vein occlusion, which can lead to loss of vision (1). To perform microcannulation, a surgeon positions the tip of a micropipette (< 30 μm) at the target retinal vein (< 100 μm) and holds it at this position for > 30 s to inject a thrombolytic drug, as illustrated in Figure 1a. The tip of the micropipette should be precisely controlled and stably held, and the force applied on the eye ground should be minimized. The manipulation of the micropipette in the eye cavity is difficult and is affected by the surgeon’s hand tremor, which has an amplitude of > 100 μm (2). To assist in such challenging tasks, several surgical robots have been developed, such as Steady-Hand (3) and Micron (4). We have also developed a master–slave microsurgical robotic system (5).
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Quantitative assessment of manual and robotic microcannulation
Figure 1. (a) Microcannulation; (b) accuracy measurement using graph paper; (c) in vitro test using an excised porcine eye
These robots have been designed to filter out the motion caused by the surgeon’s hand tremor and to improve the motion resolution and accuracy. In general, the feasibility of such surgical robots is evaluated in two steps: an evaluation of the fundamental functionality and in vitro/in vivo demonstrations. The fundamental functionalities of surgical robots, such as the working range, accuracy and force, are evaluated using sensors and simple models [see e.g. (6,7)] to show that the robots are capable of performing target tasks. Thereafter, in vitro and/or in vivo experiments that simulate actual surgery are conducted, using excised organ models or animal models to demonstrate that the functionalities are valid in a realistic scenario [see e.g. (8,9)]. We have also conducted these experiments to evaluate our master–slave microsurgical robotic system. Figure 1b shows the functionality evaluation, specifically the accuracy measurement, and Figure 1c shows an in vitro test using an excised porcine eye. The functionality test demonstrated that the master–slave microsurgical robotic system had a positioning accuracy of 69 μm (10). It was also found that the system contributed to better motion stability as a result of hand tremor cancellation and motion scaling, which resulted in better positioning control, particularly in the depth direction, reducing the applied force by 78%. The in vitro microcannulation experiment using a micropipette with a diameter of 30 μm showed the feasibility of robotic microcannulation in 70, 90 and 110 μm retinal veins (5). These assessments successfully showed the effectiveness of robotic eye surgery, but its effectiveness in comparison to manual operation in a realistic surgical set-up must still be evaluated. A functionality evaluation employing sensors and simple models is not realistic but can provide quantitative evaluations. In contrast, in vitro and/or in vivo evaluations are more realistic, but they often lack quantitative evaluation criteria. In addition, the results are influenced by the individual differences in animal organs, and the experiments cannot be repeated. Therefore, an assessment method that employs a realistic artificial model is needed to quantify the effectiveness of robotic surgery in comparison Copyright © 2014 John Wiley & Sons, Ltd.
to manual operation before performing in vitro and/or in vivo evaluations. In this study, we developed a new artificial eye model that is capable of sensing the force at the eye ground to evaluate manual and robotic microcannulation in a more realistic set-up. This model also employed a retinal vein model that was fabricated using microelectromechanical system technology.
Materials and methods An eye model containing a force sensor and retinal vein model was developed. Ten subjects performed microcannulation using the eye model, with and without the master–slave microsurgical robotic system. The results were compared to quantify the differences in the success rate, task completion time and maximum force applied on the eye ground.
Eye model The eye model consists of a sclera model, retinal vein model, force sensor (load cell) and mechanism that uses a permanent magnet and metal sphere designed to simulate the rotational motion of the eye, as shown in Figure 2. The sclera model is made of natural rubber with a simulated Young’s modulus of 2.7 ± 1.4 MPa to mimic the
Figure 2. Eye model: (a) sectional view; (b) fabricated model Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
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mechanical properties and size of the human sclera (11). Table 1 lists the specifications of the sclera model. A hole located on top of the model is used to insert a micropipette and to observe the microcannulation procedure with a microscope. The load cell (TC-USR-17, TEAC, Japan) measures the force applied on the eye ground of the model, and the sensing range is –300 to 300 mN, with a resolution of 0.03 mN. The eye model is placed under the facial cover of the commercial eye surgery training kit KITARO DryLab (Frontier Vision Co., Japan), as shown Table 1. Specifications of sclera model Material Thickness Hardness Outer diameter
Natural rubber 1.5 mm A 50 24 mm
Figure 3. Eye model with facial cover
in Figure 3, to simulate the geometrical constraints of the human facial shape. This also makes it possible to simulate the surgeon’s hand positioning during manual operation, which involves the surgeon placing his or her hand on the patient’s face to suppress hand tremor. The retinal vein model is composed of either 60 or 90 μm microchannels to simulate the diameter of the target retinal vein. The channels were fabricated using polydimethyl siloxane (PDMS) to simulate the feeling of puncturing a retinal vein. Regarding the fabrication methods for microvessels, Nakano et al. (12) proposed the fabrication of multiscale transparent arteriole and capillary vessel models with circular cross-sections of 10–500 μm, using photolithography. However, their fabrication process was complex and difficult. We therefore simplified the photolithography process and fabricated a retinal vein model with rectangular cross-sections, as shown in Figure 4. Microchannels were fabricated by replica moulding, using a PDMS sheet. First, a negative photoresist, SU-8 (Kayaku MicroChem Co.), was spincoated onto a Si wafer and baked on a hotplate. The wafer was then exposed to UV light through a photomask with a microchannel pattern, using a Karl Suss MJB3 Mask Aligner (SUSS Micro Tec AG), and subjected to a post-exposure bake (PEB). After the PEB, the wafer was developed in a PM thinner and rinsed in isopropyl alcohol. Thereafter, the prepolymer, PDMS Sylpot 184 (Dow Corning Co.), was poured onto the SU-8 master and cured at 90 °C for 15 min in a convection oven. After removing the cured PDMS sheet with the microchannels from the master, the sheet and a thin PDMS membrane (thickness 13 μm) were
Figure 4. Procedure to fabricate retinal vein model Copyright © 2014 John Wiley & Sons, Ltd.
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treated in air plasma using a plasma system, CUTE-MP/R (Femto Science Co.). Then, the treated surface of the cured PDMS sheet with the microchannels and the treated surface of the thin PDMS membrane were placed in contact. After baking at 145 °C for 15 min in a convection oven, the PDMS sheet with the microchannels was strongly bonded to the PDMS membrane. The size of the microchannels could be easily changed by redesigning the photomask. The developed microchannels are shown in Figure 5.
operator releases the foot pedal. The slave manipulator (5) also has seven DoFs. This manipulator has a remote centre of motion (RCM) at the cross-point of the α and β axes. By matching the RCM point with the robotic tool insertion point (i.e. the insertion point of the cannula) in the sclera, the operator can perform tasks without being aware of the mechanical constraints at the insertion point. Instead of a gripper, a micropipette is attached to this slave manipulator when a surgeon performs microcannulation.
Master–slave microsurgical robotic system
Experimental set-up
The master–slave microsurgical robotic system comprises a master manipulator and slave manipulator, as shown in Figure 6. The master manipulator (13) is composed of a commercial haptic device, Phantom Premium 1.0 (Sensable, USA) and a custom-made stylus with highresolution encoders. This manipulator has seven degrees of freedom (DoFs), including the gripping DoF, and measures the surgeon’s hand motion. The measured motion is scaled down with a motion-scaling ratio of 40:1 and sent to the slave manipulator using UDP/IP communication. A foot pedal is attached to the master manipulator, and the master–slave communication is terminated when the
Figure 5. Artificial retinal vein model: (a) 60 μm (pitch 200 μm); (b) 90 μm (pitch 200 μm)
The experimental set-ups for manual and robotic microcannulation are shown in Figure 7. The microcannulation was observed using a microscope and displayed on a 3D monitor. A micropipette with a 20 μm diameter tip was fabricated, and a coloured ethanol solution was used to simulate the thrombolytic drug injection. Eight engineering students and two ophthalmologists performed microcannulation, with and without the robotic system. First, the micropipette’s tip was set 1 mm away from the specified target point in a microchannel of the retinal vein model. Then, the subject was asked to move the micropipette to puncture the microchannel. Once the micropipette’s tip punctured the thin membrane of the microchannel and was properly inserted, the ethanol solution was manually delivered using the microinjector. The injection was visually detected by the colour of the solution. The subject continued to hold the micropipette in position for 30 s to simulate the actual drug injection time required for the treatment of retinal vein occlusion. The puncture and drug injection were considered successful when no leakage of the solution was observed. The experiment was performed for 60 and 90 μm microchannels and was repeated twice. The success rate, task completion time for the injection process, drug injection time and maximum force applied
Figure 6. Master–slave microsurgical robotic system: (a) master manipulator; (b) slave manipulator Copyright © 2014 John Wiley & Sons, Ltd.
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Figure 7. Experimental set-up: (a) for manual operation; (b) for robotic operation (b1, master manipulator; b2, slave manipulator)
to the eye ground were measured, and a comparison was made between the manual and robotic microcannulation tests. The drug injection time for a successful injection process was 30 s, as designed. When solution leakage was observed as a result of hand tremors causing the unwanted removal of the micropipette, the drug injection was immediately terminated. The statistical significances of the differences in the measured times and forces were analysed using a paired t-test.
Results The experimental results from the puncture process and the drug injection process were analysed. The puncture Table 2. Success rate of puncture Diameter (μm)
Method
Success rate (%)
60
Manual Robot Manual Robot
90 95 95 90
90
process was influenced largely by the accuracy and motion resolution, whereas the drug-injection process was mainly affected by the motion stability.
Puncture process Table 2 lists the puncture success rate and Tables 3 and 4 list the task completion times and the applied maximum forces for puncture, respectively. Figure 8 illustrates the averages and standard deviations (SDs) of the results. The manual and robot microcannulation tasks had success rates > 90%. The task completion time for the robotic microcannulation in the 60 μm microchannels was twice that of the manual task (p < 0.05). In the case of the 90 μm microchannels, the task completion time was also twice that of the manual task (p < 0.01). The applied maximum force for the robotic operation decreased to one-third that for the manual operation (p < 0.01) in the 60 μm microchannels and decreased to half that for the manual operation (p < 0.01) in the 90 μm microchannels.
Table 3. Task completion time (s) for puncture Manual operation 60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2 Average SD
Robotic operation 90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
11.3 11.6 5.4 12.7 15.8 13.4 15.8 12.7 11.3 6.6
7.3 16.9 12.5 7.1 58.2 9.3 16.4 27.5 24.1 8.0
12.9 17.0 7.2 34.4 22.2 35.4 14.7 18.1 9.6 8.1
15.5 20.2 15.4 17.3 36.4 12.1 10.5 11.2 3.7 4.3
20.8 12.9 19.5 117.4 32.5 28.5 25.5 78.8 30.2 31.4
35.3 14.3 19.8 58.0 35.4 38.0 23.1 31.3 26.5 9.9
45.0 35.9 10.5 36.9 46.8 96.0 16.2 24.4 14.4 30.2
37.8 61.1 54.8 25.8 29.6 42.0 33.3 29.1 17.4 19.3
15 12
Copyright © 2014 John Wiley & Sons, Ltd.
16 9.6
34 25
35.3 19.6
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Quantitative assessment of manual and robotic microcannulation Table 4. Maximum applied force (mN) for puncture Manual operation
Robotic operation
60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2 Average SD
90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
15.0 20.8 8.2 10.8 38.6 21.8 37.6 32.5 12.4 13.4
18.8 30.1 23.8 19.0 32.7 22.2 7.1 31.2 13.0 17.2
24.2 30.1 9.6 17.1 31.9 16.4 15.0 32.1 12.8 23.2
18.9 24.3 25.6 20.3 55.3 15.6 15.9 40.1 6.8 20.2
6.4 6.4 4.7 6.4 15.1 9.6 12.2 12.5 3.9 4.5
7.6 7.6 5.1 13.6 13.1 9.5 12.6 11.1 4.4 5.5
10.3 11.0 3.5 7.6 10.4 15.0 15.9 11.0 3.0 4.3
2.7 13.4 8.7 17.7 20.6 20.1 19.8 18.0 3.9 6.3
21 9.6
23 11
8.6 3.6
11 6.2
Figure 8. Experimental results for puncture: (a) task completion time; (b) maximum applied force
Drug injection process Table 5 lists the success rate for drug injection, and Tables 6 and 7 list the task completion times and applied maximum forces for puncture, respectively. Figure 9 illustrates the averages and SDs of the results. The drug injection success rate for the robotic operation was much higher than that for the manual operation. The drug injection time for the robotic operation was one and a half times that for the manual operation (p < 0.01 in the 60 μm microchannels and p < 0.05 in the 90 μm microchannels); the longer drug injection time is preferable for successful drug delivery. In the robotic operation, the task completion time reached the required drug injection time of 30 s in 18/19 trials in the 60 μm microchannels and 17/18 trials in the 90 μm microchannels. The maximum applied force for the robotic operation for drug Table 5. Success rate for drug injection Diameter (μm)
Method
Success rate (%)
60
Manual Robot Manual Robot
28 95 47 94
90
Copyright © 2014 John Wiley & Sons, Ltd.
injection decreased to one-third that for the manual operation (p < 0.01 in the 60 μm microchannels and p < 0.05 in the 90 μm microchannels); the reduced maximum applied force is also preferable for safe surgery.
Discussion The puncture process was successful in both the manual and the robotic microcannulation tasks, suggesting that the accuracy was sufficient in the manual operation and did not need to be improved by robotic assistance. This was because the mechanical constraints imposed on the cannula served as a tremor filter, which can explain how some surgeons can perform microcannulation regardless of hand tremor, although it is considered to be very difficult. In contrast, the task completion time for the puncture process was longer for the robotic microcannulation because the motion-scaling ratio was 40:1, and the robotic operation required a large hand motion at the master manipulator. The force applied on the eye ground was significantly smaller for robotic microcannulation because the motion stability was better. The robotic assistance was more useful for the drug-injection process, as demonstrated by the higher success rates. Moreover, the drug injection times in some of the manual tasks Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
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216 Table 6. Task completion time (s) for drug injection (N/A for unsuccessful puncture) Manual operation 60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2
Robotic operation 90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
11.2 7.8 30.0 24.8 3.3 4.0 N/A 29.0 30.0 9.5
5.5 26.4 30.0 16.9 2.8 20.6 N/A 18.5 30.0 30.0
10.0 16.0 N/A 30.0 2.4 3.2 30.0 5.4 30.0 30.0
11.1 23.2 30.0 27.3 30.0 7.8 30.0 9.5 30.0 30.0
30.0 30.0 N/A 30.0 30.0 30.0 30.0 30.0 30.0 30.0
4.4 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0
30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0
N/A 25.8 30.0 30.0 30.0 30.0 N/A 30.0 30.0 30.0
Average SD
18 11
20 11
29 5.9
29.8 1.00
Table 7. Maximum applied force (mN) for drug injection (N/A for unsuccessful puncture) Manual operation 60 μm
Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Student 7 Student 8 Surgeon 1 Surgeon 2 Average SD
Robotic operation 90 μm
60 μm
90 μm
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
Trial 1
Trial 2
8.4 17.9 36.7 12.2 5.4 6.9 N/A 43.0 9.1 1.6
2.6 8.2 22.3 18.0 29.8 19.8 N/A 15.9 8.4 13.4
7.1 1.8 N/A 25.7 8.0 9.4 14.6 41.1 9.1 12.3
8.4 3.3 28.9 13.1 21.7 2.8 13.6 31.1 12.5 7.3
4.2 1.7 N/A 6.1 5.2 7.4 2.7 3.3 4.3 4.0
2.3 2.9 7.1 3.3 4.1 8.2 3.2 2.5 3.5 5.5
3.7 2.4 5.9 2.4 7.1 5.1 14.4 2.9 3.4 4.8
N/A 2.0 5.9 12.9 7.2 6.7 N/A 2.8 4.3 2.1
16 11
14 11
4.3 1.8
5.3 3.5
Figure 9. Experimental results for drug injection: (a) drug injection time; (b) maximum applied force
did not reach the required time (30 s), and the micropipette’s tip was removed from the microchannel prematurely. This was because the hand tremor was too large to stabilize the micropipette in such small microchannels. In contrast, the robot held the micropipette for the required time without applying a large force on the eye ground. Although many studies related to eye surgery robots have focused on improving accuracy, these results suggest that Copyright © 2014 John Wiley & Sons, Ltd.
the accuracy during manual operation can be sufficient, although better accuracy could alleviate the difficulty of the procedure. In contrast, robotic assistance could be useful for improving motion stability, especially when the instrument needs to be held for a certain period of time. Experiments using artificial models that replicate the actual surgical constraints are helpful both to assess a manual operation to quantify the requirements of robotic surgery Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
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Quantitative assessment of manual and robotic microcannulation
and to quantitatively evaluate the positive and negative effects of robotic surgery prior to animal experiments.
Funding No specific funding.
Conclusions In this paper, we described a new microcannulation assessment method using an eye model containing microchannels and a force sensor. The microcannulation procedure and its constraints were simulated using the model, and experiments were performed to quantify the differences between manual and robotic operations. It was found that the robotic operation made a significant contribution by enhancing the motion stability. More specifically, in tasks using the master–slave microsurgical robotic system, the force applied on the eye ground was decreased by > 60% compared to manual operation, and drug injection was also more successful. Our future work will involve improving the retinal vein model to more precisely mimic the shape and mechanical properties of an actual human retinal vein. We are also planning to implement additional sensors to measure other important skill assessment factors, such as the force applied on the sclera.
Acknowledgements This study was partially supported by the Global Centre of Excellence for Mechanical Systems Innovation (GMSI) at the University of Tokyo and a Grant-in-Aid for Scientific Research (S) 23226006.
Conflict of interest The authors have stated explicitly that there are no conflicts of interest in connection with this article.
Copyright © 2014 John Wiley & Sons, Ltd.
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Int J Med Robotics Comput Assist Surg 2015; 11: 210–217. DOI: 10.1002/rcs
