Precision and effort in robot-assisted placement of pedicle screws compared to standard surgical navigation: a cadaveric study

doi:10.21203/rs.3.rs-4274972/v1

Precision and effort in robot-assisted placement of pedicle screws compared to standard surgical navigation: a cadaveric study

2024 · doi:10.21203/rs.3.rs-4274972/v1

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Abstract

Abstract Background: Aim was to compare image-guided navigation with a robot-assisted solution for performing MISS regardarding precision, required time and subjective aspects. Methods: 90 pedicles were instrumented on two torsos, half with navigation, half robot-assisted. Results: Precision analysis between both solutions didn’t show a significant difference. Time measurement showed a significantly longer duration per wire for the robot-arm on the first torso and a not significant longer duration on the second torso, where a significant reduction in the mean duration was shown. There was no significant difference in the subjective impressions comparing navigation and robot except the possibility to change the procedure. Conclusion: Precision of both methods is suitable for clinical use. A time advantage using the robot-arm couldn`t be demonstrated in the present study. A significant learning curve was shown, so a reduction in the longer duration on the robot can be expected. Further studies in clinical use are necessary.

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Precision and effort in robot-assisted placement of pedicle screws compared to standard surgical navigation: a cadaveric study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Precision and effort in robot-assisted placement of pedicle screws compared to standard surgical navigation: a cadaveric study Julia Katharina Sippel, Johannes Groh, Lars Bräuer, Mario Perl, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4274972/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Background: Aim was to compare image-guided navigation with a robot-assisted solution for performing MISS regardarding precision, required time and subjective aspects. Methods: 90 pedicles were instrumented on two torsos, half with navigation, half robot-assisted. Results: Precision analysis between both solutions didn’t show a significant difference. Time measurement showed a significantly longer duration per wire for the robot-arm on the first torso and a not significant longer duration on the second torso, where a significant reduction in the mean duration was shown. There was no significant difference in the subjective impressions comparing navigation and robot except the possibility to change the procedure. Conclusion: Precision of both methods is suitable for clinical use. A time advantage using the robot-arm couldn`t be demonstrated in the present study. A significant learning curve was shown, so a reduction in the longer duration on the robot can be expected. Further studies in clinical use are necessary. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Medicine is constantly evolving. 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Groh","Id":"88bc214d-301f-4bfe-ac4b-46d57831287b","ModifiedOn":"2022-03-28T12:25:18","Project":{"$ref":"5"}},"UseNumberingTypeOfParentDocument":false}],"FormattedText":{"$id":"19","Count":1,"TextUnits":[{"$id":"20","FontStyle":{"$id":"21","Superscript":true},"ReadingOrder":1,"Text":"1"}]},"Tag":"CitaviPlaceholder#394e4c83-8f8b-4e83-9208-545fb855af4a","Text":"1","WAIVersion":"6.11.0.0"}} , that has become ever less invasive, bringing the well-known benefits of reduced approaches, blood loss, soft tissue damage, and thus reduced hospitalization time 1 . As advantageous minimal invasive spine surgery (MISS) has proven for the patient, technically there are challenges in orientation and assurance of correct implant placement. Several technical adjuncts have been developed to address these shortcomings, most noticeably improvements in intraoperative imaging, especially 3D-imaging. During the last decade, optical navigation has additionally become increasingly established to be used in combination with 3D-imaging. This has been shown to increase precision and reduce intraoperative radiation exposure for the patient and especially the surgeon 2,3 . A time advantage could also be shown for optical navigation, especially with multi-level constructs{Rohe, 2022 #8} 4 . Robotic systems have also become commercially available to be used in combination with navigation. Although, the first robot for spinal surgery was launched already in 2004 5 , it has only been recently that these systems became feasible for routine use. Various design concepts are currently commercially available, including a compact design, comparable to a conventional articulated arm, which can be mounted on a standard operating table in a space- and weight-saving manner. In almost all procedures on the spine, the positioning of the pedicle screws is crucial. Rates of malposition vary in the literature and depend on the type of procedure (scoliosis surgery, trauma surgery, degenerative surgery) and range from about 4% 6,7 to 42% 8 . Misalignment mainly causes nervous complications; the rates range here up to 15% 9 . The aim of the current study was to compare a clinical standard setting of image-guided navigation (Curve, Brainlab AG, Munich) with a robot-assisted solution (Cirq, Brainlab AG, Munich) for performing minimally invasive percutaneous pedicle screw placement in all levels of the spine in regard of precision and required time. Although there are some clinical reports regarding this robotic system available, a structured evaluation in comparison to the gold standard in navigated procedures has not been published to our knowledge. The experimental study was designed as a non-inferiority trial. Materials And Methods The study was carried out in cooperation with the Institute for Functional and Clinical Anatomy, Friedrich-Alexander-University Erlangen-Nuremberg, on two human specimens. The consent for the use for scientific purposes was given by the individuals during their lifetime in accordance with the standards of the Anatomical Institute. The study was conducted on two fresh-frozen torsos. The experimental setup was the same in each case. Four surgeons of different clinical experience in complex spinal surgery (1-20 years), pedicles of vertebrae C4-S1 and the SI-joint were instrumented using 1.9mm K-wires (n=90). One side was instrumented with conventional navigation (Curve, Brainlab AG, Munich), the opposite side by the same surgeon with the robot-assisted solution (Cirq, Brainlab AG, Munich). The specimens were positioned on a mobile radiolucent carbon-fiber surgical table in prone position. The navigation camera, the patient reference, the C-arm reference and the display monitor were the same for both procedures. The experimental setup is shown in figure 1. The number of vertebrae to be instrumented was determined by the number of vertebral bodies imaged per scan (4-7 vertebral bodies). The assignment of the surgeon to the corresponding section was randomized. First, a 3D scan of the target section was performed with a flat detector C-arm (Cios Spin, Siemens Healthineers AG, Erlangen). Preoperative screw planning was then carried out on this data set in accordance with clinical standards. In the group of conventionally navigated pedicle screws, the trajectories were located using the pointer tool (see figure 2). A 1.5cm paramedian skin incision was performed over the entry point with sharp opening of the fascia and blunt dissection at the pedicle entry point. The corresponding hand-held drill guide (see figure 3) was then used to locate the entry point again. If the trajectory matched correctly, the guide was used to drill with the corresponding 2.6mm drill bit and insert the respective 1.9mm K-wire into the drill hole. In the group of robot-assisted instrumentation, the trajectory for the skin incision was also located using the corresponding pointer. A 1.5cm paramedian skin incision on the opposite side was performed over the entry point with sharp opening of the fascia and blunt dissection at the pedicle entry point. The robotic arm was then guided close to the planned trajectory (see figures 4 and 5) and the fine adjustment to control the trajectory was performed by the robotic system. After correct adjustment, the robotized sleeve was used to drill the 2.6mm hole with the appropriate drill bit and insert the respective 1.9mm K-wire into the drill hole. On the first torso, conventional navigation was used on the left side, on the second torso on the right side. After finishing both sides, a 3D scan was carried out for radiological evolution. The navigation application which was used offers the feature of automated image fusion. The preoperative (planning) 3D scan containing the planned trajectories and the control 3D scan containing the definitive wire positions were merged into a single data set so that the trajectories previously planned as described above could be compared with the final wire position (see figure 6). First, the correct fusion was checked manually. Subsequently, the measurement tools available in the navigation application were used to measure the parameters listed below for any deviations using the dual control principle. The following parameters were used for evaluation: Time from beginning of finding the trajectory to completion of wire positioning Distance of the wire to the planned trajectory in the pedicle in sagittal and axial projection (see figure 7) Deviation of the angle of the wire to the planned trajectory in sagittal and axial projection Each subject was given a standardized questionnaire on subjective aspects of the system Clinical experience (years) Number of spinal procedures performed Subjectively required attention (1-5, 1=low attention, 5=high attention) Reliability in positioning of implants and of the application (1-5, 1=low safety, 5=high safety) Trust in the system (1-5, 1=low trust, 5=high trust) Simplicity of application (1-5, 1=not simple, 5=very simple) Possibility to dynamically change the procedure (1-5, 1=no change possible, 5=change possible at any time) Recommendation (1-5, 1=no recommendation, 5=full recommendation) Freedom of action (1-5, 1=low freedom of action, 5=high freedom of action) Freetext/note In addition, the wire position was assessed corresponding to the Gertzbein and Robbins classifications. Transpedicular screw position is graded from A to E based on the extent by which the screw breaches the cortex of the pedicle: A: fully intrapedicular position without breach of the pedicle cortex B: exceeding the pedicle cortex 6 mm or is outside of the pedicle Grade A and B can be considered as a satisfactory operation result. In grade C to E, neurological symptoms may occur and can be evaluated as an unsatisfactory surgical result 10 . The statistical evaluation of the measurements was carried out in MS Excel (Microsoft Corporation, Redmond, USA). Results Precision: For the precision analysis, 89 of the 90 wires were available, since during the 3D scan one of the applied wires was dislocated and thus it was no longer evaluable in the control scan. A total of 14% (6) of the wires set by the robot needed revision (defined as Gertzbein/Robbins C-E): 5 on the first torso and 1 on the second torso. 4% (2) of the wires set by conventional navigation needed revision due to Gertzbein/Robbins C-E, both on the first torso (see table 1). The measured deviation of the wire from the trajectory of the robot on the first torso was 1.1mm (min 0mm; max 7mm; SD ±1.5mm), the angular deviation 1.2° (min. 0°; max. 7°; SD ±1.7°) (see table 2). On the second torso, the deviation was on average 0.9mm (min. 0mm; max. 5mm; SD ±1.1mm), the angular deviation 0.8° (min. 0°; max. 4°; SD ±1.0°) (see table 3). The difference in distance and angle deviation was not significant between the individual torsos (distance: p=0.12, angle p=0.07). The deviation of the wire during navigation was 1.1mm (min. 0mm; max. 5mm; SD ±1.3mm), the angular deviation was on average 1.5° (min. 0°, max. 6°; SD ±1.6°) (see table 2). On the second torso, the deviation was on average 1.0mm (min. 0mm; max. 6mm; SD ±1.4mm), the angular deviation analogous to the first torso 1.5° (min. 0°; max. 7°; SD ±1.6°) (see table 3). The difference in distance and angle deviation was not significant between the individual torsos/days (distance: p=0.37, angle p=0.45). The comparison between the robot arm and conventional navigation on the first torso didn’t show a significant difference (distance: p=0.39, angle: p=0.24). On the second torso, the difference in the distance was again not significant (p=0.29), in the angular deviation the robot was significantly more precise (p=0.005). Averaged over both torsos, the following values were obtained: The average distance deviation of the robot was 1.0mm (min. 0mm; max. 7mm; SD ±1.3mm). The angular deviation was 1.0° (min. 0°; max. 7°; SD ±1.4°) (see table 4). The deviation in conventional navigation was 1.0mm (min. 0mm; max. 6mm; SD ±1.3mm), the angular deviation 1.5° (min. 0mm; max. 7mm; SD ±1.6°) (see table 4). The distance deviation was the same on average for both methods, there was no significant difference (p=0.44). The difference in angular deviation was significant (p=0.01). Table 1: Gertzbein/Robbins classification related to the K-wires Gertzbein and Robbins classification Number of K-wires robot Number of K-wires navigation A 38 43 B 0 0 C 3 0 D 3 2 E 0 0 Table 2: Precision analysis torso 1 Torso 1 average min. max. SD Distance deviation navigation 1.1 mm 0 mm 5 mm ±1.3 mm Distance deviation robot 1.1 mm 0 mm 7 mm ±1.5 mm Angular deviation navigation 1.5° 0° 5° ±1.6° Angular deviation robot 1.2° 0° 7° ±1.7° Table 3: Precision analysis torso 2 Torso 2 average min. max. SD Distance deviation navigation 1.0 mm 0 mm 6 mm ±1.4 mm Distance deviation robot 0.9 mm 0 mm 5 mm ±1.1 mm Angular deviation navigation 1.5° 0° 7° ±1.6° Angular deviation robot 0.8° 0° 4° ±1.1° Table 4: Total precision analysis Total average min. max. SD Distance deviation navigation 1.0 mm 0 mm 6 mm ±1.3 mm Distance deviation robot 1.0 mm 0 mm 7 mm ±1.3 mm Angular deviation navigation 1.5° 0° 7° ±1.6° Angular deviation robot 1.0° 0° 7° ±1.4° A significant difference in precision between the individual test subjects could not be shown in an ANOVA analysis (Analysis of Variance) between the test subjects for either the hand-guided navigation or the robot arm (distance deviation robot p=0.3; distance deviation navigation p=0.4; angle deviation robot p=0.5; angle deviation robot p=0.9). A clear correlation between the experience of the test subjects and the individual precision could not be shown (see table 5). Table 5: Correlation between precision and experience correlation coefficient Distance deviation navigation -0.36 Distance deviation robot 0.01 Angular deviation navigation 0.13 Angular deviation robot 0.58 Time: The time measurement showed a significantly longer duration per wire on the first torso of an average of 120s for the robot arm (236s (min. 86s; max. 536s; SD ±131s) vs. 116s (min. 62s; max. 242s; SD ±47s), p<0.001). The second torso showed a not significant average of 16 s longer time per wire in the robotically assisted procedure (154s (min. 89s; max .355s; SD ±68s) vs. 138s (min. 68s; max. 322s; SD ±60s), p=0.2) (see tables 6,7 and figure 8). The time difference per wire in navigation was not significant across both torsos (p=0.09). For the vertebral bodies instrumented with the robot arm, there was a significant reduction in the mean duration of positioning per wire by 81s (p=0.007). Table 6: Time per wire on first torso Torso 1 average min. max. SD Time per wire navigation 116s 62s 242s ± 47s Time per wire robot 236s 86s 536s ± 131s Table 7: Time per wire on second torso Torso 2 average min. max. SD Time per wire navigation 138s 68s 322s ± 60s Time per wire robot 154s 89s 355s ± 68s In an ANOVA analysis, no significant difference in time per wire was found between the test subjects in either group (navigation or robot) (navigation p=0.3, robot p=0.06). In the hand-guided navigation group, there was an inverse correlation between clinical experience and the average time per wire with a correlation coefficient of -0.97. In the group of robot-assisted wire placement, this correlation could not be verified (correlation coefficient -0.37). Subjective impression: The handling was consistently rated as good by all test persons. In the freetext the lack of possibility to deviate from the planned trajectory in the robotarm was criticized. There was no significant difference in the subjective impressions comparing navigation and robot except the possibility to change the procedure, here could be found a significantly more positive evaluation in favor of hand-guided navigation (p=0.04) (see tables 8 and 9). Table 8: Subjective impression navigation Navigation average min. max. SD Subjectively required attention 4 3 5 1.2 Safety in the positioning 3.5 2 4 1.0 Trust in the system 4 3 5 1.2 Simplicity of application 4 4 4 0.0 Possibility to change the procedure 4.5 3 5 1.0 Recommendation 4.5 3 5 1.0 Freedom of action 4.5 4 5 0.6 Table 9: Subjective impression robot Robot average min. max. SD Subjectively required attention 4 3 5 1.2 Safety in the positioning 3.75 3 4 0.5 Trust in the system 3.5 3 5 1.0 Simplicity of application 4.25 4 5 0.5 Possibility to change the procedure 2.75 1 4 1.3 Recommendation 4.5 3 5 1.0 Freedom of action 4.25 3 5 1.0 Discussion A statistically significant difference in the precision between positioning with the robotic arm and conventional navigation could not be shown. What is noticeable, though, in the data is the higher rate of wire misplacement (Gertzbein/Robbins C-E) of the robot compared to manual navigation, especially on the first torso. The above wire malpositions were mainly located in the upper cervical spine. Since decapitated human specimens were used in this study, the trajectories did not correspond to the usual clinical trajectories and were partially parallel to the table. It was not always possible to approach the wire positions correctly due to the larger structure of the front of the robotic arm. On the second torso, this was optimized by a correspondingly improved positioning of the torso, which was reflected by an improved wire position on the upper cervical spine. To achieve adequate precision, correct positioning and preoperative preparation must also be ensured for the robot. The precision of both methods is suitable for clinical use. The precision of the Cirq in our study on the second torso corresponds to the above optimizations with the systems of other manufacturers 11 . A time advantage using the robotic arm could not be demonstrated in the present study, which is in line with the current study situation. For example, a meta-analysis by Zhang et al. from 2019 showed comparable precision of different robotic systems in spinal surgery with simultaneously prolonged surgery 12 . However, the significant learning curve leads to several hypotheses. Firstly, it is to be expected that the observed longer duration per wire levels out due to the steep learning curve. This hypothesis is supported by the work of Pojskic et al. who were also able to show a clear learning curve with the Cirq (here in clinical use) 13 . In their analysis of the Cirq, Gabrovsky et al. were able to demonstrate a significant correlation between the experience of the respective surgeon with the robotic arm and the time per wire and screw 14 . Chesney et al. were also able to demonstrate this significant learning curve in a series of 714 screws placed with the Cirq 15 . It could also be shown that an initial prolongation of the surgery when using a new and (for the surgeon) unknown tool can be observed regardless of the clinical experience of the respective surgeon. The subjective survey of the participants also showed that a free hand during the procedure was rated as positive. Conversely, however, it was also criticized that the design of the robot's "assisting hand" offers few opportunities for manual manipulation and thus for dynamic changes to the surgical plan. This should be possible with any technical aid in the operation room and should be mentioned here as a problem of the robot-assisted procedure. The high purchase price and running costs of a robotic solution compared to navigation also need to be discussed. The use of navigation and the use of the robot can be mapped via a separate OPS code in Germany (5-988.3 and 5-987), coding and therefore reimbursement of both operations by the health insurance funds is currently pending. This means that the costs of the robotic arm are amortized more slowly compared to navigation due to its higher acquisition costs. Due to the comparable precision of navigation and robots, similar revision rates can be expected. Further studies are needed to investigate a long-term time advantage after completion of the learning curve and thus to examine the extent to which a reduction in operating time results in cost savings. Limitations The study was conducted on decapitated human specimens. This showed an altered alignment around the remaining cervical spine as well as an altered anatomy with abnormal trajectories. For example, as described above, some trajectories were almost parallel to the operating table, which does not correspond to the usual clinical picture. Accordingly, the times and precision at these altitudes must be critically assessed. The study was conducted in a realistic setting. Nevertheless, not all aspects of a real surgery that could have an influence on the result (surgical drapes, surgical staff, structural conditions) can be represented here. Conclusion There were no differences between the test subjects in terms of time and precision. Existing navigation and robotic solutions are therefore also suitable for young residents and can and should be an integral part of clinical training. Nevertheless, it is important to learn and master the instruments in order to recognize technical problems and, if the technology fails, to be able to perform the procedure safely and quickly without risk to the patient 11 . Regarding minimally invasive spine surgery, the fluoroscopic technique of pedicle screw placement with a Jamshidi needle is also the standard for kyphoplasty, which continues to be of great importance in spinal surgery and is one of the basics for every spinal surgeon 11 . Robotic- and Navigation assisted spine surgery show promising results and great potential for further investigations and they seem to be a safe and beneficial method for accurate pedicle screw placement. Declarations Ethics The study was carried out in cooperation with the Institute for Functional and Clinical Anatomy, Friedrich-Alexander-University Erlangen-Nuremberg, on two human specimens. The consent for the use for scientific purposes was given by the individuals during their lifetime in accordance with the standards of the Anatomical Institute. Data availability statement The data that support the findings of this study are available from the corresponding author, Johannes Groh, upon reasonable request. Conflict of interest Julia Katharina Sippel declares no conflict of interest. Johannes Groh declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany. Lars Bräuer declares no conflict of interest. Mario Perl declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany. Holger Stadthalter declares paid consultant for Brainlab AG, Munich, Germany. Funding statement No funding or research grants were received in the course of study, research or assembly of the manuscript. Author contribution statement Julia Katharina Sippel, Johannes Groh and Holger Stadthalter carried out the experiment. Johannes Groh, Holger Stadthalter and Lars Bräuer conceived and planned the experiments. Julia Katharina Sippel and Johannes Groh wrote the manuscript. Lars Bräuer and Mario Perl helped supervise the project. Holger Stadthalter supervised the project. All authors provided critical feedback and helped shape the research, analysis and manuscript. References Staub BN, Sadrameli SS. The use of robotics in minimally invasive spine surgery. J Spine Surg. 2019;5(Suppl 1):S31-S40. Kantelhardt SR, Martinez R, Baerwinkel S, Burger R, Giese A, Rohde V. Perioperative course and accuracy of screw positioning in conventional, open robotic-guided and percutaneous robotic-guided, pedicle screw placement. Eur Spine J. 2011;20(6):860-868. Konieczny MR, Krauspe R. Navigation Versus Fluoroscopy in Multilevel MIS Pedicle Screw Insertion: Separate Analysis of Exposure to Radiation of the Surgeon and of the Patients. Clin Spine Surg. 2019;32(5):E258-E265. Rohe S, Strube P, Holzl A, Bohle S, Zippelius T, Lindemann C. Cone-Beam Navigation Can Reduce the Radiation Exposure and Save Fusion Length-Dependent Operation Time in Comparison to Conventional Fluoroscopy in Pedicle-Screw-Based Lumbar Interbody Fusion. J Pers Med. 2022;12(5). Mao JZ, Agyei JO, Khan A, et al. Technologic Evolution of Navigation and Robotics in Spine Surgery: A Historical Perspective. World Neurosurg. 2021;145:159-167. Hicks JM, Singla A, Shen FH, Arlet V. Complications of pedicle screw fixation in scoliosis surgery: a systematic review. Spine (Phila Pa 1976). 2010;35(11):E465-470. Sarwahi V, Wendolowski SF, Gecelter RC, et al. Are We Underestimating the Significance of Pedicle Screw Misplacement? Spine (Phila Pa 1976). 2016;41(9):E548-555. Merloz P, Tonetti J, Pittet L, Coulomb M, Lavallee S, Sautot P. Pedicle screw placement using image guided techniques. Clin Orthop Relat Res. 1998(354):39-48. Kreinest M, Rillig J, Kuffer M, Grutzner PA, Tinelli M, Matschke S. Comparison of pedicle screw misplacement following open vs. percutaneous dorsal instrumentation after traumatic spinal fracture. Eur J Trauma Emerg Surg. 2021;47(3):727-732. Neubauer J KK, Knipe H. Gertzbein and Robbins classification. Reference article, Radiopaedia.org. 2020; https://radiopaedia.org/articles/82155. Schwendner M, Meyer B, Krieg SM. [Robot-assisted pedicle screw placement]. Oper Orthop Traumatol. 2023;35(1):37-42. Zhang Q, Han XG, Xu YF, et al. Robotic navigation during spine surgery. Expert Rev Med Devices. 2020;17(1):27-32. Pojskic M, Bopp M, Nimsky C, Carl B, Sabeta B. Initial Intraoperative Experience with Robotic-Assisted Pedicle Screw Placement with Cirq((R)) Robotic Alignment: An Evaluation of the First 70 Screws. J Clin Med. 2021;10(24). Gabrovsky N, Ilkov P, Laleva M. Cirq(R) robotic assistance for thoracolumbar pedicle screw placement - feasibility, accuracy, and safety. Brain Spine. 2023;3:101717. Chesney K, Triano M, Dowlati E, Zhang I, Felbaum DR, Aulisi EF. Cirq robotic arm-assisted transpedicular instrumentation with intraoperative navigation: technical note and case series with 714 thoracolumbar screws. J Robot Surg. 2022;16(4):893-898. Additional Declarations Competing interest reported. Julia Katharina Sippel declares no conflict of interest. Johannes Groh declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany. Lars Bräuer declares no conflict of interest. Mario Perl declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany. Holger Stadthalter declares paid consultant for Brainlab AG, Munich, Germany. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 18 Apr, 2024 Submission checks completed at journal 17 Apr, 2024 First submitted to journal 16 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4274972","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":292581296,"identity":"01417e45-a883-42db-ba44-9e49608a06fa","order_by":0,"name":"Julia Katharina Sippel","email":"","orcid":"","institution":"Friedrich-Alexander-Universität Erlangen-Nürnberg, Faculty of Medicine, Department of Orthopedic and Trauma Surgery","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"Katharina","lastName":"Sippel","suffix":""},{"id":292581297,"identity":"e230356c-fb98-476e-ae6f-c12f708140e8","order_by":1,"name":"Johannes 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Julia Katharina Sippel declares no conflict of interest.\nJohannes Groh declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany.\nLars Bräuer declares no conflict of interest.\nMario Perl declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany.\nHolger Stadthalter declares paid consultant for Brainlab AG, Munich, Germany.","formattedTitle":"Precision and effort in robot-assisted placement of pedicle screws compared to standard surgical navigation: a cadaveric study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMedicine is constantly evolving. This especially applies to spinal surgery\n \u003c!--[if supportFields]\u003e\u003cspan style='font-family:\"Franklin Gothic Book\",sans-serif'\u003e\u003cspan style='mso-element:field-begin'\u003e\u003c/span\u003eADDIN CitaviPlaceholder{{"$id":"1","$type":"SwissAcademic.Citavi.Citations.WordPlaceholder, SwissAcademic.Citavi","Entries":[{"$id":"2","$type":"SwissAcademic.Citavi.Citations.WordPlaceholderEntry, SwissAcademic.Citavi","Id":"610142b8-31e1-4edb-a980-d368cfe73174","RangeLength":1,"ReferenceId":"88bc214d-301f-4bfe-ac4b-46d57831287b","Reference":{"$id":"3","$type":"SwissAcademic.Citavi.Reference, SwissAcademic.Citavi","AbstractComplexity":0,"AbstractSourceTextFormat":0,"Authors":[{"$id":"4","$type":"SwissAcademic.Citavi.Person, SwissAcademic.Citavi","FirstName":"Jennifer","LastName":"Mao","MiddleName":"Z.","Protected":false,"Sex":1,"CreatedBy":"_Johannes Groh","CreatedOn":"2022-03-28T10:23:12","ModifiedBy":"_Johannes 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SwissAcademic.Citavi","Eissn":"1878-8769","Name":"World neurosurgery","Pagination":0,"Protected":false,"UserAbbreviation1":"World Neurosurg","CreatedBy":"_Johannes Groh","CreatedOn":"2022-03-28T10:23:12","ModifiedBy":"_Johannes Groh","Id":"5a77cbc9-9e58-4f3e-8d1f-7395fe06fa4c","ModifiedOn":"2022-03-28T10:23:12","Project":{"$ref":"5"}},"Publishers":[],"PubMedId":"32916361","Quotations":[],"Rating":0,"ReferenceType":"JournalArticle","ShortTitle":"Mao, Agyei et al. 2021 – Technologic Evolution of Navigation","ShortTitleUpdateType":0,"SourceOfBibliographicInformation":"PubMed","StaticIds":["98348a99-3d15-4221-91d3-4ddfb9b58484"],"TableOfContentsComplexity":0,"TableOfContentsSourceTextFormat":0,"Tasks":[],"Title":"Technologic Evolution of Navigation and Robotics in Spine Surgery: A Historical Perspective","Translators":[],"Volume":"145","Year":"2021","YearResolved":"2021","CreatedBy":"_Johannes Groh","CreatedOn":"2022-03-28T10:23:12","ModifiedBy":"_Johannes Groh","Id":"88bc214d-301f-4bfe-ac4b-46d57831287b","ModifiedOn":"2022-03-28T12:25:18","Project":{"$ref":"5"}},"UseNumberingTypeOfParentDocument":false}],"FormattedText":{"$id":"19","Count":1,"TextUnits":[{"$id":"20","FontStyle":{"$id":"21","Superscript":true},"ReadingOrder":1,"Text":"1"}]},"Tag":"CitaviPlaceholder#394e4c83-8f8b-4e83-9208-545fb855af4a","Text":"1","WAIVersion":"6.11.0.0"}}\u003cspan style='mso-element:field-separator'\u003e\u003c/span\u003e\u003c/span\u003e\u003c![endif]--\u003e\n \u003c!--[if supportFields]\u003e\u003cspan style='font-family:\"Franklin Gothic Book\",sans-serif'\u003e\u003cspan style='mso-element: field-end'\u003e\u003c/span\u003e\u003c/span\u003e\u003c![endif]--\u003e, that has become ever less invasive, bringing the well-known benefits of reduced approaches, blood loss, soft tissue damage, and thus reduced hospitalization time\u003csup\u003e1\u003c/sup\u003e. As advantageous minimal invasive spine surgery (MISS) has proven for the patient, technically there are challenges in orientation and assurance of correct implant placement. Several technical adjuncts have been developed to address these shortcomings, most noticeably improvements in intraoperative imaging, especially 3D-imaging. During the last decade, optical navigation has additionally become increasingly established to be used in combination with 3D-imaging. This has been shown to increase precision and reduce intraoperative radiation exposure for the patient and especially the surgeon\u003csup\u003e2,3\u003c/sup\u003e. A time advantage could also be shown for optical navigation, especially with multi-level constructs{Rohe, 2022 #8}\u003csup\u003e4\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRobotic systems have also become commercially available to be used in combination with navigation. Although, the first robot for spinal surgery was launched already in 2004\u003csup\u003e5\u003c/sup\u003e, it has only been recently that these systems became feasible for routine use. Various design concepts are currently commercially available, including a compact design, comparable to a conventional articulated arm, which can be mounted on a standard operating table in a space- and weight-saving manner.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn almost all procedures on the spine, the positioning of the pedicle screws is crucial. Rates of malposition vary in the literature and depend on the type of procedure (scoliosis surgery, trauma surgery, degenerative surgery) and range from about 4%\u003csup\u003e6,7\u003c/sup\u003e to 42%\u003csup\u003e8\u003c/sup\u003e. Misalignment mainly causes nervous complications; the rates range here up to 15%\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe aim of the current study was to compare a clinical standard setting of image-guided navigation (Curve, Brainlab AG, Munich) with a robot-assisted solution (Cirq, Brainlab AG, Munich) for performing minimally invasive percutaneous pedicle screw placement in all levels of the spine in regard of precision and required time. Although there are some clinical reports regarding this robotic system available, a structured evaluation in comparison to the gold standard in navigated procedures has not been published to our knowledge.\u003c/p\u003e\n\u003cp\u003eThe experimental study was designed as a non-inferiority trial.\u003c/p\u003e\n"},{"header":"Materials And Methods","content":"\u003cp\u003eThe study was carried out in cooperation with the Institute for Functional and Clinical Anatomy, Friedrich-Alexander-University Erlangen-Nuremberg, on two human specimens. The consent for the use for scientific purposes was given by the individuals during their lifetime in accordance with the standards of the Anatomical Institute.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The study was conducted on two fresh-frozen torsos. The experimental setup was the same in each case. Four surgeons of different clinical experience in complex spinal surgery (1-20 years), pedicles of vertebrae C4-S1 and the SI-joint were instrumented using 1.9mm K-wires (n=90). One side was instrumented with conventional navigation (Curve, Brainlab AG, Munich), the opposite side by the same surgeon with the robot-assisted solution (Cirq, Brainlab AG, Munich). The specimens were positioned on a mobile radiolucent carbon-fiber surgical table in prone position. The navigation camera, the patient reference, the C-arm reference and the display monitor were the same for both procedures. The experimental setup is shown in figure 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe number of vertebrae to be instrumented was determined by the number of vertebral bodies imaged per scan (4-7 vertebral bodies). The assignment of the surgeon to the corresponding section was randomized.\u003c/p\u003e\n\u003cp\u003eFirst, a 3D scan\u0026nbsp;of the target section\u0026nbsp;was performed with a flat detector C-arm (Cios Spin, Siemens Healthineers AG, Erlangen). Preoperative screw planning was then carried out on this data set in accordance with clinical standards.\u003c/p\u003e\n\u003cp\u003eIn the group of conventionally navigated pedicle screws, the trajectories were located using the pointer tool (see figure 2). A\u0026nbsp;1.5cm paramedian\u0026nbsp;skin incision was performed over the entry point with sharp opening of the fascia and blunt dissection at the pedicle entry point. The corresponding hand-held drill guide (see figure 3) was then used to locate the entry point again. If the trajectory matched correctly, the guide was used to drill with the corresponding 2.6mm drill bit and insert the respective 1.9mm K-wire into the drill hole.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the group of robot-assisted instrumentation, the trajectory for the skin incision was also located using the corresponding pointer. A 1.5cm paramedian skin incision on the opposite side was performed over the entry point with sharp opening of the fascia and blunt dissection at the pedicle entry point. The robotic arm was then guided close to the planned trajectory (see figures 4 and 5) and the fine adjustment to control the trajectory was performed by the robotic system. After correct adjustment, the robotized sleeve was used to drill the 2.6mm hole with the appropriate drill bit and insert the respective 1.9mm K-wire into the drill hole.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the first torso, conventional navigation was used on the left side, on the second torso on the right side. After finishing both sides, a 3D scan was carried out for radiological evolution.\u003c/p\u003e\n\u003cp\u003eThe navigation application which was used offers the feature of automated image fusion. The preoperative (planning) 3D scan containing the planned trajectories and the control 3D scan containing the definitive wire positions were merged into a single data set so that the trajectories previously planned as described above could be compared with the final wire position (see figure 6). First, the correct fusion was checked manually. Subsequently, the measurement tools available in the navigation application were used to measure the parameters listed below for any deviations using the dual control principle.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The following parameters were used for evaluation:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eTime from beginning of finding the trajectory to completion of wire positioning\u003c/li\u003e\n \u003cli\u003eDistance of the wire to the planned trajectory in the pedicle in sagittal and axial projection (see figure 7)\u003c/li\u003e\n \u003cli\u003eDeviation of the angle of the wire to the planned trajectory in sagittal and axial projection\u003c/li\u003e\n \u003cli\u003eEach subject was given a standardized questionnaire on subjective aspects of the system\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"1\"\u003e\n \u003cli\u003eClinical experience (years)\u003c/li\u003e\n \u003cli\u003eNumber of spinal procedures performed\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSubjectively required attention (1-5, 1=low attention, 5=high attention)\u003c/li\u003e\n \u003cli\u003eReliability in positioning of implants and of the application (1-5, 1=low safety, 5=high safety)\u003c/li\u003e\n \u003cli\u003eTrust in the system (1-5, 1=low trust, 5=high trust)\u003c/li\u003e\n \u003cli\u003eSimplicity of application (1-5, 1=not simple, 5=very simple)\u003c/li\u003e\n \u003cli\u003ePossibility to dynamically change the procedure (1-5, 1=no change possible, 5=change possible at any time)\u003c/li\u003e\n \u003cli\u003eRecommendation (1-5, 1=no recommendation, 5=full recommendation)\u003c/li\u003e\n \u003cli\u003eFreedom of action (1-5, 1=low freedom of action, 5=high freedom of action)\u003c/li\u003e\n \u003cli\u003eFreetext/note\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eIn addition, the wire position was assessed corresponding to the Gertzbein and Robbins classifications.\u0026nbsp;Transpedicular screw position is graded from A to E based on the extent by which the screw breaches the cortex of the pedicle:\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eA: fully intrapedicular position without breach of the pedicle cortex\u003c/li\u003e\n \u003cli\u003eB: exceeding the pedicle cortex \u0026lt;2 mm\u003c/li\u003e\n \u003cli\u003eC: exceeding the pedicle cortex 2-4 mm\u003c/li\u003e\n \u003cli\u003eD: exceeding the pedicle cortex 4-6 mm\u003c/li\u003e\n \u003cli\u003eE: exceeding the pedicle cortex \u0026gt;6 mm or is outside of the pedicle\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eGrade A and B can be considered as a satisfactory operation result. In grade C to E, neurological symptoms may occur and can be evaluated as an unsatisfactory surgical result\u003csup\u003e10\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The statistical evaluation of the measurements was carried out in MS Excel (Microsoft Corporation, Redmond, USA).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePrecision:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the precision analysis, 89 of the 90 wires were available, since during the 3D scan one of the applied wires was dislocated and thus it was no longer evaluable in the control scan.\u003c/p\u003e\n\u003cp\u003eA total of 14% (6) of the wires set by the robot needed revision (defined as Gertzbein/Robbins C-E): 5 on the first torso and 1 on the second torso. 4% (2) of the wires set by conventional navigation needed revision due to Gertzbein/Robbins C-E, both on the first torso (see table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe measured deviation of the wire from the trajectory of the robot on the first torso was 1.1mm (min 0mm; max 7mm; SD \u0026plusmn;1.5mm), the angular deviation 1.2\u0026deg; (min. 0\u0026deg;; max. 7\u0026deg;; SD \u0026plusmn;1.7\u0026deg;) (see table 2).\u003c/p\u003e\n\u003cp\u003eOn the second torso, the deviation was on average 0.9mm (min. 0mm; max. 5mm; SD \u0026plusmn;1.1mm), the angular deviation 0.8\u0026deg; (min. 0\u0026deg;; max. 4\u0026deg;; SD \u0026plusmn;1.0\u0026deg;)\u0026nbsp;(see table 3). The difference in distance and angle deviation was not significant between the individual torsos (distance: p=0.12, angle p=0.07).\u003c/p\u003e\n\u003cp\u003eThe deviation of the wire during navigation was 1.1mm (min. 0mm; max. 5mm; SD \u0026plusmn;1.3mm), the angular deviation was on average 1.5\u0026deg; (min. 0\u0026deg;, max. 6\u0026deg;; SD \u0026plusmn;1.6\u0026deg;) (see table 2).\u003c/p\u003e\n\u003cp\u003eOn the second torso, the deviation was on average 1.0mm (min. 0mm; max. 6mm; SD \u0026plusmn;1.4mm), the angular deviation analogous to the first torso 1.5\u0026deg; (min. 0\u0026deg;; max. 7\u0026deg;; SD \u0026plusmn;1.6\u0026deg;) (see table 3). The difference in distance and angle deviation was not significant between the individual torsos/days (distance: p=0.37, angle p=0.45).\u003c/p\u003e\n\u003cp\u003eThe comparison between the robot arm and conventional navigation on the first torso didn\u0026rsquo;t show a significant difference (distance: p=0.39, angle: p=0.24).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the second torso, the difference in the distance was again not significant (p=0.29), in the angular deviation the robot was significantly more precise (p=0.005).\u003c/p\u003e\n\u003cp\u003eAveraged over both torsos, the following values were obtained:\u003c/p\u003e\n\u003cp\u003eThe average distance deviation of the robot was 1.0mm (min. 0mm; max. 7mm; SD \u0026plusmn;1.3mm). The angular deviation was 1.0\u0026deg; (min. 0\u0026deg;; max. 7\u0026deg;; SD \u0026plusmn;1.4\u0026deg;) (see table 4).\u003c/p\u003e\n\u003cp\u003eThe deviation in conventional navigation was 1.0mm (min. 0mm; max. 6mm; SD \u0026plusmn;1.3mm), the angular deviation 1.5\u0026deg; (min. 0mm; max. 7mm; SD \u0026plusmn;1.6\u0026deg;) (see table 4). The distance deviation was the same on average for both methods, there was no significant difference (p=0.44). The difference in angular deviation was significant (p=0.01).\u003c/p\u003e\n\u003cp\u003eTable 1: Gertzbein/Robbins classification related to the K-wires\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.202492211838006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGertzbein and Robbins classification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of K-wires robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of K-wires navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.202492211838006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.202492211838006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.202492211838006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.202492211838006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.202492211838006%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.398753894081%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2: Precision analysis torso 1\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTorso 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaverage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e5 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.3 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e7 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.5 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.5\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e5\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.6\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.2\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e7\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.7\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3: Precision analysis torso 2\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTorso 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaverage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e6 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.4 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0.9 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e5 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.1 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.5\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e7\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.6\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0.8\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e4\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.1\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 4: Total precision analysis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaverage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e6 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.3 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e7 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.3 mm\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.5\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e7\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.6\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e1.0\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e0\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e7\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn;1.4\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;A significant difference in precision between the individual test subjects could not be shown in an ANOVA analysis (Analysis of Variance) between the test subjects for either the hand-guided navigation or the robot arm (distance deviation robot p=0.3; distance deviation navigation p=0.4; angle deviation robot p=0.5; angle deviation robot p=0.9).\u003c/p\u003e\n\u003cp\u003eA clear correlation between the experience of the test subjects and the individual precision could not be shown (see table 5).\u003c/p\u003e\n\u003cp\u003eTable 5: Correlation between precision and experience\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.401869158878505%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.598130841121495%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ecorrelation coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.401869158878505%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.598130841121495%\" valign=\"top\"\u003e\n \u003cp\u003e-0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.401869158878505%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistance deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.598130841121495%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.401869158878505%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.598130841121495%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.401869158878505%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAngular deviation robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.598130841121495%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTime:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe time measurement showed a significantly longer duration per wire on the first torso of an average of 120s for the robot arm (236s (min. 86s; max. 536s; SD \u0026plusmn;131s) vs. 116s (min. 62s; max. 242s; SD \u0026plusmn;47s), p\u0026lt;0.001). The second torso showed a not significant average of 16 s longer time per wire in the robotically assisted procedure (154s (min. 89s; max .355s; SD \u0026plusmn;68s) vs. 138s (min. 68s; max. 322s; SD \u0026plusmn;60s), p=0.2) (see tables 6,7 and figure 8).\u003c/p\u003e\n\u003cp\u003eThe time difference per wire in navigation was not significant across both torsos (p=0.09).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the vertebral bodies instrumented with the robot arm, there was a significant reduction in the mean duration of positioning per wire by 81s (p=0.007).\u003c/p\u003e\n\u003cp\u003eTable 6: Time per wire on first torso\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTorso 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaverage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime per wire navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e116s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e62s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e242s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn; 47s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime per wire robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e236s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e86s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e536s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn; 131s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 7: Time per wire on second torso\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTorso 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaverage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime per wire navigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e138s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e68s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e322s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn; 60s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime per wire robot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e154s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e89s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e355s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026plusmn; 68s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In an ANOVA analysis, no significant difference in time per wire was found between the test subjects in either group (navigation or robot) (navigation p=0.3, robot p=0.06).\u003c/p\u003e\n\u003cp\u003eIn the hand-guided navigation group, there was an inverse correlation between clinical experience and the average time per wire with a correlation coefficient of -0.97.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the group of robot-assisted wire placement, this correlation could not be verified (correlation coefficient -0.37).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eSubjective impression:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe handling was consistently rated as good by all test persons. In the freetext the lack of possibility to deviate from the planned trajectory in the robotarm was criticized. There was no significant difference in the subjective impressions comparing navigation and robot except the possibility to change the procedure, here could be found a significantly more positive evaluation in favor of hand-guided navigation (p=0.04) (see tables 8 and 9).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 8: Subjective impression navigation\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNavigation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaverage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubjectively required attention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSafety in the positioning\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrust in the system\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimplicity of application\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePossibility to change the procedure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecommendation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFreedom of action\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 9: Subjective impression robot\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRobot\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eaverage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emin.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emax.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubjectively required attention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSafety in the positioning\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrust in the system\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimplicity of application\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePossibility to change the procedure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecommendation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.267080745341616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFreedom of action\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.683229813664596%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA statistically significant difference in the precision between positioning with the robotic arm and conventional navigation could not be shown.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhat is noticeable, though, in the data is the higher rate of wire misplacement (Gertzbein/Robbins C-E) of the robot compared to manual navigation, especially on the first torso. The above wire malpositions were mainly located in the upper cervical spine. Since decapitated human specimens were used in this study, the trajectories did not correspond to the usual clinical trajectories and were partially parallel to the table. It was not always possible to approach the wire positions correctly due to the larger structure of the front of the robotic arm. On the second torso, this was optimized by a correspondingly improved positioning of the torso, which was reflected by an improved wire position on the upper cervical spine. \u0026nbsp;To achieve adequate precision, correct positioning and preoperative preparation must also be ensured for the robot.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe precision of both methods is suitable for clinical use. The precision of the Cirq in our study on the second torso corresponds to the above optimizations with the systems of other manufacturers\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eA time advantage using the robotic arm could not be demonstrated in the present study, which is in line with the current study situation. For example, a meta-analysis by Zhang et al. from 2019 showed comparable precision of different robotic systems in spinal surgery with simultaneously prolonged surgery\u003csup\u003e12\u003c/sup\u003e. However, the significant learning curve leads to several hypotheses. Firstly, it is to be expected that the observed longer duration per wire levels out due to the steep learning curve. This hypothesis is supported by the work of Pojskic et al. who were also able to show a clear learning curve with the Cirq (here in clinical use)\u003csup\u003e13\u003c/sup\u003e. In their analysis of the Cirq, Gabrovsky et al. were able to demonstrate a significant correlation between the experience of the respective surgeon with the robotic arm and the time per wire and screw\u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eChesney et al. were also able to demonstrate this significant learning curve in a series of 714 screws placed with the Cirq\u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIt could also be shown that an initial prolongation of the surgery when using a new and (for the surgeon) unknown tool can be observed regardless of the clinical experience of the respective surgeon.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe subjective survey of the participants also showed that a free hand during the procedure was rated as positive. Conversely, however, it was also criticized that the design of the robot\u0026apos;s \u0026quot;assisting hand\u0026quot; offers few opportunities for manual manipulation and thus for dynamic changes to the surgical plan. This should be possible with any technical aid in the operation room and should be mentioned here as a problem of the robot-assisted procedure.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe high purchase price and running costs of a robotic solution compared to navigation also need to be discussed. The use of navigation and the use of the robot can be mapped via a separate OPS code in Germany (5-988.3 and 5-987), coding and therefore reimbursement of both operations by the health insurance funds is currently pending. This means that the costs of the robotic arm are amortized more slowly compared to navigation due to its higher acquisition costs. Due to the comparable precision of navigation and robots, similar revision rates can be expected. Further studies are needed to investigate a long-term time advantage after completion of the learning curve and thus to examine the extent to which a reduction in operating time results in cost savings.\u0026nbsp;\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThe study was conducted on decapitated human specimens. This showed an altered alignment around the remaining cervical spine as well as an altered anatomy with abnormal trajectories. For example, as described above, some trajectories were almost parallel to the operating table, which does not correspond to the usual clinical picture. Accordingly, the times and precision at these altitudes must be critically assessed. The study was conducted in a realistic setting. Nevertheless, not all aspects of a real surgery that could have an influence on the result (surgical drapes, surgical staff, structural conditions) can be represented here.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThere were no differences between the test subjects in terms of time and precision. Existing navigation and robotic solutions are therefore also suitable for young residents and can and should be an integral part of clinical training. Nevertheless, it is important to learn and master the instruments in order to recognize technical problems and, if the technology fails, to be able to perform the procedure safely and quickly without risk to the patient\u003csup\u003e11\u003c/sup\u003e. Regarding minimally invasive spine surgery, the fluoroscopic technique of pedicle screw placement with a Jamshidi needle is also the standard for kyphoplasty, which continues to be of great importance in spinal surgery and is one of the basics for every spinal surgeon\u003csup\u003e11\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eRobotic- and Navigation assisted spine surgery show promising results and great potential for further investigations and they seem to be a safe and beneficial method for accurate pedicle screw placement.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study was carried out in cooperation with the Institute for Functional and Clinical Anatomy, Friedrich-Alexander-University Erlangen-Nuremberg, on two human specimens. The consent for the use for scientific purposes was given by the individuals during their lifetime in accordance with the standards of the Anatomical Institute.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData availability statement\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, Johannes Groh, upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Conflict of interest\u003c/p\u003e\n\u003cp\u003eJulia Katharina Sippel declares no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJohannes Groh declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany.\u003c/p\u003e\n\u003cp\u003eLars Br\u0026auml;uer declares no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMario Perl declares grants and speaker Honorarium from Siemens Healthineers, Erlangen, Germany.\u003c/p\u003e\n\u003cp\u003eHolger Stadthalter declares paid consultant for Brainlab AG, Munich, Germany.\u003c/p\u003e\n\u003cp\u003eFunding statement\u003cbr\u003e\u0026nbsp;No funding or research grants were received in the course of study, research or assembly of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Author contribution statement\u003c/p\u003e\n\u003cp\u003eJulia Katharina Sippel, Johannes Groh and Holger Stadthalter carried out the experiment. Johannes Groh, Holger Stadthalter and Lars Br\u0026auml;uer conceived and planned the experiments. Julia Katharina Sippel and Johannes Groh wrote the manuscript. Lars Br\u0026auml;uer and Mario Perl helped supervise the project. Holger Stadthalter supervised the project. All authors provided critical feedback and helped shape the research, analysis and manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eStaub BN, Sadrameli SS. The use of robotics in minimally invasive spine surgery. \u003cem\u003eJ Spine Surg. \u003c/em\u003e2019;5(Suppl 1):S31-S40.\u003c/li\u003e\n\u003cli\u003eKantelhardt SR, Martinez R, Baerwinkel S, Burger R, Giese A, Rohde V. Perioperative course and accuracy of screw positioning in conventional, open robotic-guided and percutaneous robotic-guided, pedicle screw placement. \u003cem\u003eEur Spine J. \u003c/em\u003e2011;20(6):860-868.\u003c/li\u003e\n\u003cli\u003eKonieczny MR, Krauspe R. Navigation Versus Fluoroscopy in Multilevel MIS Pedicle Screw Insertion: Separate Analysis of Exposure to Radiation of the Surgeon and of the Patients. \u003cem\u003eClin Spine Surg. \u003c/em\u003e2019;32(5):E258-E265.\u003c/li\u003e\n\u003cli\u003eRohe S, Strube P, Holzl A, Bohle S, Zippelius T, Lindemann C. Cone-Beam Navigation Can Reduce the Radiation Exposure and Save Fusion Length-Dependent Operation Time in Comparison to Conventional Fluoroscopy in Pedicle-Screw-Based Lumbar Interbody Fusion. \u003cem\u003eJ Pers Med. \u003c/em\u003e2022;12(5).\u003c/li\u003e\n\u003cli\u003eMao JZ, Agyei JO, Khan A, et al. Technologic Evolution of Navigation and Robotics in Spine Surgery: A Historical Perspective. \u003cem\u003eWorld Neurosurg. \u003c/em\u003e2021;145:159-167.\u003c/li\u003e\n\u003cli\u003eHicks JM, Singla A, Shen FH, Arlet V. Complications of pedicle screw fixation in scoliosis surgery: a systematic review. \u003cem\u003eSpine (Phila Pa 1976). \u003c/em\u003e2010;35(11):E465-470.\u003c/li\u003e\n\u003cli\u003eSarwahi V, Wendolowski SF, Gecelter RC, et al. Are We Underestimating the Significance of Pedicle Screw Misplacement? \u003cem\u003eSpine (Phila Pa 1976). \u003c/em\u003e2016;41(9):E548-555.\u003c/li\u003e\n\u003cli\u003eMerloz P, Tonetti J, Pittet L, Coulomb M, Lavallee S, Sautot P. Pedicle screw placement using image guided techniques. \u003cem\u003eClin Orthop Relat Res. \u003c/em\u003e1998(354):39-48.\u003c/li\u003e\n\u003cli\u003eKreinest M, Rillig J, Kuffer M, Grutzner PA, Tinelli M, Matschke S. Comparison of pedicle screw misplacement following open vs. percutaneous dorsal instrumentation after traumatic spinal fracture. \u003cem\u003eEur J Trauma Emerg Surg. \u003c/em\u003e2021;47(3):727-732.\u003c/li\u003e\n\u003cli\u003eNeubauer J KK, Knipe H. Gertzbein and Robbins classification. Reference article, Radiopaedia.org. 2020; https://radiopaedia.org/articles/82155.\u003c/li\u003e\n\u003cli\u003eSchwendner M, Meyer B, Krieg SM. [Robot-assisted pedicle screw placement]. \u003cem\u003eOper Orthop Traumatol. \u003c/em\u003e2023;35(1):37-42.\u003c/li\u003e\n\u003cli\u003eZhang Q, Han XG, Xu YF, et al. Robotic navigation during spine surgery. \u003cem\u003eExpert Rev Med Devices. \u003c/em\u003e2020;17(1):27-32.\u003c/li\u003e\n\u003cli\u003ePojskic M, Bopp M, Nimsky C, Carl B, Sabeta B. Initial Intraoperative Experience with Robotic-Assisted Pedicle Screw Placement with Cirq((R)) Robotic Alignment: An Evaluation of the First 70 Screws. \u003cem\u003eJ Clin Med. \u003c/em\u003e2021;10(24).\u003c/li\u003e\n\u003cli\u003eGabrovsky N, Ilkov P, Laleva M. Cirq(R) robotic assistance for thoracolumbar pedicle screw placement - feasibility, accuracy, and safety. \u003cem\u003eBrain Spine. \u003c/em\u003e2023;3:101717.\u003c/li\u003e\n\u003cli\u003eChesney K, Triano M, Dowlati E, Zhang I, Felbaum DR, Aulisi EF. Cirq robotic arm-assisted transpedicular instrumentation with intraoperative navigation: technical note and case series with 714 thoracolumbar screws. \u003cem\u003eJ Robot Surg. \u003c/em\u003e2022;16(4):893-898.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"patient-safety-in-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psis","sideBox":"Learn more about [Patient Safety in Surgery](http://pssjournal.biomedcentral.com/)","snPcode":"13037","submissionUrl":"https://submission.nature.com/new-submission/13037/3","title":"Patient Safety in Surgery","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4274972/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4274972/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Aim was to compare image-guided navigation with a robot-assisted solution for performing MISS regardarding precision, required time and subjective aspects.\u003c/p\u003e\n\u003cp\u003eMethods: 90 pedicles were instrumented on two torsos, half with navigation, half robot-assisted.\u003c/p\u003e\n\u003cp\u003eResults: Precision analysis between both solutions didn’t show a significant difference.\u003c/p\u003e\n\u003cp\u003eTime measurement showed a significantly longer duration per wire for the robot-arm on the first torso and a not significant longer duration on the second torso, where a significant reduction in the mean duration was shown.\u003c/p\u003e\n\u003cp\u003eThere was no significant difference in the subjective impressions comparing navigation and robot except the possibility to change the procedure.\u003c/p\u003e\n\u003cp\u003eConclusion: Precision of both methods is suitable for clinical use. A time advantage using the robot-arm couldn`t be demonstrated in the present study. A significant learning curve was shown, so a reduction in the longer duration on the robot can be expected. 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