Development of a Surgical Knife Attachment with Proximity Indicators

Transcription

1 Development of a Surgical Knife Attachment with Proximity Indicators Daiki YANO 1, Masanao KOEDA 1, Katsuhiko ONISHI 1 and Hiroshi NOBORIO 1 1 Osaka Electro-Communication University, Japan koeda@osakac.ac.jp Abstract. To prevent liver surgical accidents, we have been developing a surgery navigation system with two depth cameras with different characteristics. In this paper, we describe our developed surgical knife attachment which indicates the proximity of the blood vessels in the liver by light and sound. The method to calibrate the tip position of the knife in our camera system is also mentioned. Using this attachment, some experiments to navigate operator were conducted and the results indicated that the navigation worked correctly within the target range. Keywords: Liver Surgery Support, Navigation, Proximity, Alert, Calibration 1 Introduction The liver is a large and soft organ. Several blood vessels (arteries, veins, portals, etc.) present in the liver are not externally visible. Surgeons use X-ray imaging, computed tomography (CT) or magnetic resonance imaging (MRI) to preoperatively determine the position of these vessels in the liver. During surgery, incision points are located by touching the targeted incision site using fingers and feeling for a pulse-beat. The accuracy of this method is poor and can result in bleeding and injury to the blood vessels. Several surgical support and navigation systems are commercially available [1-3]. These systems determine the position of the surgical tools, synchronize with the tomographic images captured prior to surgery, and navigate the tool to the target position. These systems are mainly used for orthopedic, dental, or brain surgery. The body parts targeted in orthopedic or dental surgery are rigid and exhibit negligible deformation. The tissue targeted during brain surgery is soft and is subject to deformation. During surgery, the hard skull bone, which shields the brain, is fixed to the operating table, which results in minimal deformation. These surgery support and navigation systems are successfully implemented in practice owing to the negligible level of deformation achieved before and during the surgery. The liver is soft and continuously deforms during an operation due to the patient's breathing, organ pulsation, the incision process, and the manual operation of the sur- adfa, p. 1, Springer-Verlag Berlin Heidelberg 2011

2 geon. The shape of the liver must be constantly measured during surgery. Existing support systems are insufficient and cannot be reliably applied to liver surgery. Research on liver surgery support systems has been limited, and no effective system have been developed yet. We have been developing a liver surgery support system with Kansai Medical University Hospital. The proposed system aims to remove the cancer tissue completely and save the liver without causing injury to the inner vessels. In this paper, our developed knife attachment is described. It indicates the proximity of the blood vessels by illuminating light emitting diodes (LEDs) and by generating audible beeping sounds to prevent blood vessel injury (Fig. 1). 2 Liver surgical support system The proposed system consists of two depth cameras with different characteristics. The first camera is lower precision but a wide measurement range used for determining the shape of the liver during surgery. We preoperatively prepare a three-dimensional (3D) model using CT or MRI data. The model contains the shape of the liver, inner blood vessels, and tumors. By matching the low precision depth image with the 3D model during surgery, the position of the invisible blood vessels and tumors is estimated. The details are given in [4-7]. The second camera is higher precision and performs single point measurements using single markers [8] to determine the tip position of the surgical knife. By merging the camera and 3D model information, the distance between the knife tip and the vessels or tumors is calculated and the proximity of the knife to the arteries or portals is determined. The distance between the knife tip and tumor can be calculated [9] and the navigation to remove cancers preformed. To indicate the proximity to the vessels or tumors, we have developed a surgical knife attachment with LEDs and an audible alarm. We chose a versatile attachment device, which uses a clamp for easy attachment of a knife or other surgical tools. Fig. 1. Overview of our liver surgical support system

3 3 Surgical knife attachment with proximity indicators Multiple markers (Fig. 2) are attached to the top of the knife to estimate the tip position during surgery. The attachment is connected to a clamp (GoPro Sportsman Mount), which is easily clipped to the end of a surgical tool (Fig. 3). When the knife approaches a liver part that must not be cut, such as an artery or a portal, the attachment generates an alarm by gradually turning on lighting LEDs and producing a beeping sound. The attachment contains a micro-computer (Arduino Nano), a LED bar module (OSX10201-GYR1) [10], and a piezoelectric speaker (Figs. 4 and 5). The LED module has 10 LEDs arranged in the order of five green, three yellow and two red. The cubic case is fabricated from plastic by using a 3D printer, and measures approximately [mm]. The micro-computer is connected to a primary PC through a USB 2.0 interface. This interface is used to supply power and transmit the proximity data indicated by the number of illuminated LEDs. The micro-computer controls the LEDs and the frequency of the beeping sound (Fig. 6). For simplicity, the connection between the PC and micro-computer is currently hardwired. It is not difficult, however, to convert to a wireless interface for future implementations. Fig. 2. Design and size of markers on the surgical knife attachment Fig. 3. Surgical knife attachment with proximity indicators (The markers in the left image are for demonstration.)

4 Fig. 4. Circuit diagram Fig. 5. Inner structure of the attachment (left: main case, right: top lid)

5 (a) All LEDs are off (b) 2 LEDs are on (c) 4 LEDs are on (d) 6 LEDs are on (e) 8 LEDs are on (f) All 10 LEDs are on Fig. 6. Experimental results of trajectory of each subject

6 4 Knife tip position calibration The knife tip position is estimated from the markers on the surface of the cubic attachment. Prior to surgery, the relative vectors from each marker to the tip of the knife are calibrated. The calibration procedure is simple and recalibration can be performed as required. Camera and knife coordinate systems are defined as c and k respectively. One of the markers attached to the knife is designated as M knife, and the fixed marker on the table is designated as M table. To acquire a relative vector from M knife to the knife tip, c the knife tip is placed at the origin point p table of M table, and the position and posture c c of each marker are measured in c. The position P knife and orientation R knife of the c marker attached to the knife M knife are measured in c. The relative vector P rel is calculated by the following equation.p rel k c c c P rel = P table P knife c To convert P rel to k coordinates, the following is used. P k c rel = (R knife ) 1 c P rel c Finally, the knife tip position P tip in c is estimated as follows. c c P tip = R knife P k c rel + P knife If multiple markers are detected and multiple tip positions are estimated at the same time, the positions are averaged. The estimation error in the knife tip position is less than 1[mm]. The details of the error evaluation are given in [11]. 5 Navigation experiment and result We conducted experiments to validate operator navigation using the attachment. The task is to trace an invisible target circle with the tip of the knife based on the LED information. The beeping sound was not used for this experiment. The target circle is set on a flat horizontal table in front of the subject (Fig. 7). The diameter of the circle is 100 [mm]. To measure the navigation error precisely, the attachment cube was fixed to a hard steel rod (130[mm] in length, 6[mm] in diameter) using a strong adhesive (Fig. 8). The LED array is illuminated incrementally in 1 [mm] step as the distance to the target circle is reduced. All LEDs are illuminated when the tip touches the target circle. The six subjects (A to F) are not surgeons, they are undergraduate or postgraduate students, in their twenties, from the Osaka Electro-Communication University. With (x tip, y tip ) as the knife tip position, (x c, y c ) as the center of the circle, and r as the radius of the circle, a distance L between the knife tip and the circle is calculated from the following equation. L = r (x c x tip ) 2 + (y c y tip ) 2 The LED's are gradually illuminated between 1 L 10 [mm]. The LED array contains 10 LEDs; therefore, we can navigate over a range in ±10 [mm] of the circle. The experimental results of the trajectory of the tip position are shown in Fig. 9. The red circle is the target circle and the purple dots show the trajectory. The LEDs turn on

7 within the range between the blue and yellow circles. The average navigation errors and standard deviation for each subject are shown in Fig. 10. The results show that the maximum error is 14 [mm], and the error remained within a LED illumination range of 20 [mm]. These results confirm that the LED based navigation works correctly. Fig. 7. Experiment environment Fig. 8. Tool for navigation experiment

8 (a) Subject A (b) Subject B (c) Subject C (d) Subject D (e) Subject E (f) Subject F Fig. 9. Experimental results of trajectory of each subject

9 maximum error Subject Fig. 10. Navigation errors 6 Preliminary experiment for sterilization A sterile surgical environment is important. We conducted a preliminary experiment to determine if the marker can be measured while covered with a transparent sterile sheet. The initial results showed that when the marker was loosely covered, there were measurement failures due to light reflection or refraction. However, by ensuring that the marker was tightly covered with no wrinkling (Fig. 11), no problems were encountered and stable measurements were achieved. The transparent sterile sheet used in this experiment was for medical use and was provided by Kyoto University Hospital. Fig. 11. Marker block covered by transparent sterile sheet

10 7 Conclusion We developed a surgical knife attachment that indicates the proximity of the blood vessels by illuminating LEDs and generating beeping sounds to prevent blood vessel injury. To validate operator navigation using this device, navigation experiments using six subject were conducted. Based on the results we conclude that the navigation of this device works well. The maximum navigation error is limited to 14 [mm]. In the future, we will improve the accuracy of navigation, downsize the device, and conduct experiments in an actual surgery support setting. Acknowledgement This research was supported by Grants-in-Aid for Scientific Research (No ) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. References [1] Knee Navigation Application - Brainlab : [2] ClaroNav - Dental and ENT Navigation Solutions : [3] Surgical Theater - Surgical Navigation Advanced Platform (SNAP) : [4] H. Noborio, K. Onishi, M. Koeda, K. Mizushino, T. Kunii, M. Kaibori, M. Kon and Y. Chen: "A Fast Surgical Algorithm Operating Polyhedrons Using Z-Buffer in GPU", In Proceedings of the 9th Asian Conference on Computer Aided Surgery (ACCAS2013), pp , [5] K. Watanabe, M. Yagi, A. Shintani, S. Nankaku, K. Onishi, M. Koeda, H. Noborio, M. Kon, K. Matsui and M. Kaibori: "A New 2D Depth-Depth Matching Algorithm whose Translation and Rotation Freedoms are Separated", In Proceedings of the International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS2015), Track 3: Bioinformatics, Medical Imaging and Neuroscience, pp , [6] H. Noborio, K. Watanabe, M. Yagi, Y. Ida, S. Nankaku, K. Onishi, M. Koeda, M. Kon, K. Matsui and M. Kaibori: "Experimental Results of 2D Depth-Depth Matching Algorithm Based on Depth Camera Kinect v1", In Proceedings of the International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS2015), Track 3: Bioinformatics, Medical Imaging and Neuroscience, pp , [7] K. Onishi, H. Noborio, M. Koeda, K. Watanabe, K. Mizushino, T. Kunii, M. Kaibori, K. Matsui and M. Kon: "Virtual Liver Surgical Simulator by Using Z-Buffer

11 for Object Deformation", Universal Access in Human-Computer Interaction. Access to Learning, Health and Well-Being, Springer, ISBN , pp , [8] MicronTracker : [9] H. Noborio, T. Kunii and K. Mizushino: "GPU-Based Shortest Distance Algorithm For Liver Surgery Navigation", In Proceedings of the 10th Anniversary Asian Conference on Computer Aided Surgery, pp , [10] OSX10201-GYR1 data sheet : [11] M. Doi, D. Yano, M. Koeda, H. Noborio, K. Onishi, K. Mizushino, M. Kayaki, K. Matsui and M. Kaibori: "Knife Tip Position Estimation for Liver Surgery Support System", In Proceedings of Japanese Society for Medical Virtual Reality (JSMVR2016), pp , (In Japanese)