Experience with the Utilization of New Generation Shared Control Robotic System for Spinal Instrumentation

doi:10.21203/rs.3.rs-1852165/v1

Purpose

Robotic assistance in spine surgery is emerging as an accurate, effective and enabling technology utilized in the treatment of patients with surgical spinal pathology. Robotic systems have a wide range of applications in spine surgery from the planning and execution of spinal instrumentation to intra-operative navigation. The safety and reproducibility of robotic assistance in the placement of pedicle screw instrumentation is still being investigated, and here we present our experience of instrumented spinal fusion utilizing an intra-operative robotic guidance system.

Patients and methods

We retrospectively reviewed all cases of spinal instrumentation of the thoracic and lumbo-sacral spine using the Mazor X robotic system (Medtronic Inc, USA), performed at our institution by one surgeon between July 2017 and June 2020. Clinical variables in addition to operative details and complications were recorded. To replicate clinical relevance, screw accuracy was assessed on postoperative antero-posterior and lateral x-rays by two independent neurosurgeons. Wilcoxon Rank test was used to compare time taken to place each screw during the first 20 cases and the cases thereafter.

Results

A total of 28 patients were included. A total of 159 screws were placed using the Mazor X robotic system. The overall mean time for screw placement was 7.8 ± 2.3 minutes and there was a significant reduction in the mean time for screw placement after the 20^th case (8.70 min vs. 5.42 minutes, p=0.008). Mean follow-up was 13.0 ± 12.9 months. No post-operative neurologic deficit or new radiculopathy was noted to occur secondary to hardware placement. No revision surgery was required for replacement or removal of a mispositioned screw. No post-operative hardware complications such as hardware migration, or failure were noted within the follow-up period.

Conclusions

From this single-center, single-surgeon series we conclude that robot-assisted spine surgery can be safely and efficiently integrated into the operating room workflow, which improves after a learning curve of approximately 20 operative interventions. We found robot-assisted spinal instrumentation to be reliable, safe, effective and highly precise.

Robotics

Spine

Spinal Instrumentation

Spinal Fusion

Technology

Robotic spine surgery

surgical intelligence

Pedicle screw fixation of the spine is utilized for various purposes including stabilization of the spine and deformity correction. [1–8] Conventionally, pedicle screws were placed “free-hand” utilizing anatomic landmarks with assistance from intraoperative C-arm fluoroscopy, often in the face of anatomic challenges such as small pedicles, fractures or deformity. [6, 8, 9] Complications due to pedicle screw placement led to the creation and use of surgical intelligence tools such as image-based 3-dimensional (3D) navigation, which increased the accuracy of screw placement and reduced complication rates. [1–3, 5, 6, 10, 11] Studies suggest that the use of spinal navigation for pedicle screw placement results in improved clinical outcomes, when compared to conventional free-hand pedicle screw placement with a higher accuracy rate. [1, 6]

The advent of robot-assisted instrumentation placement has improved the reproducibility of spinal instrumentation placement and is steadily gaining popularity. [8, 12] Robotic systems, which are capable of pre-operative planning and intra-operative placement of spinal instrumentation, have shown promising results such as safe and feasible screw placement that is reliable and highly accurate. [1, 3, 5, 6, 9, 12, 13] Furthermore, prior reports indicate that the integration of robots into the operation room (OR) workflow was attainable with a steep learning curve. [3] These results are integral to the advancement of surgical intelligence in spine surgery, but thus far institutional data from early-adopter utilization is sparse. Data specifically assessing the clinical outcome, accuracy of screw placement, and learning curve with novel robotic technology is critical to technology adoption, surgeon confidence, learn curve optimization and patient outcomes. [14]

The goal of this study was to describe our institutional experiences with the Mazor X Robotic System (Medtronic, Minneapolis, Minnesota, USA), focusing on pedicle screw placement and describing the learning curve with the use of this system in our hands.

Patient Data Collection

We conducted a retrospective review of prospectively collected data from 1^st July 2017 to 30^th June 2020, using STROBE guidelines for reporting. All consecutive patients aged 18 or older undergoing spinal instrumentation of the thoracic and lumbo-sacral spine using the Mazor X robotic system were included. This current iteration has several software and hardware improvements compared to its predecessors and made the current product more efficient, accurate and user friendly. It was acquired by our institution in 2017 for the above-mentioned strengths and all cases were performed using this robotic system by the senior author (A.V.) during the specified study period. There were no exclusions. Residents and fellows participated frequently in the surgical procedures, under the senior author’s supervision.

Data was collected from our institution’s electronic health records. Demographic characteristics, clinical variables and operative details were captured.

Robot Assisted Surgery Technique

The Mazor X robotic system is a shared control system that allows the surgeon to plan hardware placement and provides stereotactic navigation-based support during the procedure. It does so by positioning and locking the robotic arm along a predetermined trajectory based on 3D-imaging, reducing the degrees of freedom of movement and thus minimizing error. [3, 11] Descriptions of how the system is used for preoperative planning, intraoperative guidance, and screw placement have been outlined in the literature and we employ a similar workflow. [3, 13, 15]

(Peri-)operative Workflow and Patient Management

Pre-operative standing scoliosis x-rays of the spine including flexion and extension films and a 1mm thin cut CT scan are obtained for patients who are undergoing spinal fusion.

In the operating room, patients are positioned prone on a Jackson table. The robotic system is then fixated securely onto the rail on the caudal end of the operating room table. Standard skin preparation and draping are completed, after which, the robotic system is mounted to the posterior superior iliac spine by inserting a single Schanz pin. We then register the robotic system using intra-operative fluoroscopy and merge it with the pre-operative CT scan to obtain accurate navigation as shown in Figure-1. The screw length, diameter, and positioning are all planned by the surgeon on robotic system using the pre-operative CT scan prior to the surgery, similar to standard practice.

Prior to inserting and utilizing navigation tools, accuracy of the navigated tools is ensured by touching known anatomy. The robot is then sent to the first pedicle that is planned to be instrumented. After making skin incision, a fascial knife is inserted through the robotic system, that terminates on the bony surface entry point as shown in Figure-2. A minimally invasive dilator is placed under navigation to identify the planned pedicle screw entry point. Following this, a drill guide and a skive prevention pin tool are both inserted and tamped into place. The center pin is removed and using a Medtronic drill through the same channel, the pedicle is cannulated to the planned depth. A tap is then placed through the working channel and the pedicle is tapped via navigation. The final step is the placement of the screw through the same working channel as shown in Figure-3. Neuro-monitoring and stimulation of screws with electrode probe is used to confirm that all the screws stimulate above the threshold of 12 mA and there is no concern for breach outside the planned trans-pedicular trajectory. Antero-posterior (AP) and lateral fluoroscopy images were then taken to confirm appropriate placement of the instrumentation followed by insertion of a percutaneous rods, final tightening, and removal of the towers. In open procedures, the robot is brought in after exposure of the bony anatomy and trans-pedicular instrumentation follows the steps described above.

Routine post-operative CT scans to assess instrumentation were not obtained to reduce radiation exposure to the patient. 3D-imaging such as CT and/or MRI scans are obtained in the event of new post-operative neurological deficit, radicular pain or hardware abnormality identified on x-rays. The authors believe that using this method, minor screw breaches which are asymptomatic may not have been detected, but remain clinically irrelevant.

Determining Screw Placement Time and Success

The duration of each screw placement was measured from the time of cutting fascia using the fascial knife to time when the screw was in its final position. The Operating Room nurse recorded the times which were then confirmed using the internal clock of the robotic system. The time required for case preparation, registration and closure was excluded since the timing for those portions can be highly variable. Screw placement was assessed by the primary neurosurgeon with fellowship training in spinal surgery. This was determined by the surgeon’s clinical judgement, triggered EMG, intraoperative fluoroscopy images, and post-operative radiographs, similar to methods described in previous literature. [2, 7] Screw placement was then validated by an independent spinal neurosurgeon using post-operative x-ray images. Each screw was classified as follows: [2]

Grade 1: accurate placement using robot guidance
Grade 2: screw mispositioned/revised using robot guidance
Grade 3: manually placed after robotic guidance aborted
Grade 4: planned screw not placed as deemed non-essential to construct stability

Data Analysis

Frequencies and percentages were reported for nominal data, while mean and standard deviation was calculated for age and BMI of the study participants. To analyze the learning curve, data on the average time of screw placement per case was graphically illustrated. Wilcoxon Rank test was then used to compare time taken to place each screw during the first 20 cases and the cases thereafter. Statistical analysis was performed using IBM SPSS Statistics version 25.0.

Ethical Considerations

This study included analysis of de-identified patient data, and thus approval was obtained from the Institutional Review Board at our institution prior to commencement.

Patient sample

A total of 28 patients (15 male, 13 female) with a mean age of 62.7 ± 9.3 years and a mean BMI of 28.3 ± 4.1 kg/m² were identified, who underwent thoracic and lumbo-sacral spinal fusion with the Mazor X robotic system, including three patients with pelvic fixation - bilateral S2 alar-iliac (S2AI) screws. Basic demographics and surgery-related variables are listed in Table-1.

Twelve patients had a history of prior lumbar decompression, five had prior lumbar fusion operations and one had a history of osteoporosis. In addition to the pedicle screw fixation from a posterior approach, 16 patients (57.1%) underwent concurrent procedure in the form of anterior lumbar interbody fusion (ALIF), on or a few days prior to the posterior instrumentation, to achieve circumferential fusion. The most common indications for the operation were spondylolisthesis and degenerative disc disease. Other indications included trauma, and tumor.

Among our study cohort, 13 patients (46.4%) had an open approach for screw placement while instrumentation was done percutaneously in 15 patients (53.6%). A total of 159 screws were placed using the Mazor X robot with a mean of 5.7 ± 2.8 screws per case. Spinal instrumentation was done primarily in an elective setting and was utilized twice in urgent clinical situations. The mean length of hospital stay after the operation was 5.7 ± 1.5 days (Table-1). The mean follow-up of the total sample was 13.0 ± 12.9 months.

Success of screw placement and revision rate

Success of screw placement and the challenges faced during the cases are summarized in Table-2. During surgery on case number 22, despite satisfactory appearance on fluoroscopy and the absence of bony breach on intra-operative inspection after initial placement according to the plan, there was positive stimulation below the threshold value on electromyographic (EMG) testing, which prompted the revision of two screws, making a total of two “Grade 2” placements. For case number 15, thoracic pedicle screw instrumentation, 3 out of the 4 screws were placed free hand (Grade 3) due to discretion of the surgeon, who felt the entry point chosen by the robot was too medial. Placement of one L5 screw was aborted due to anatomical challenges, (Grade 4) in case number 3. On review of the post-operative imaging by an independent neurosurgeon based on post-operative x-rays, all screws were deemed satisfactory. There were no intra-operative complications or registration failures. No post-operative neurologic or hardware complications were recorded that would prompt three-dimensional imaging. With the above results we were able to achieve an overall Grade 1 placement rate in 96.2% of screws. No revision surgery was required for replacement or removal of a mispositioned screw over the follow-up period.

Time needed for instrumentation and learning curve

The overall mean time to place a screw was 7.8 ± 2.3 minutes. There was a significant reduction in the time for screw placement after the 20th case (8.70 min vs. 5.42 minutes, p = 0.008; Figure-4).

Our experience

The adoption and validation of any new surgical adjunct requires study, prolonged introductory periods, and ascent of a learning curve. Repetitive safe and effective utilization of the Mazor X robotic system has led to fluency in draping, and coordination of instrumentation implantation with all supplemental staff in the OR. [8, 16] The technology is highly accurate and did not lead to any adverse events in the first 28 cases (Table-2). It is important to note that the primary surgeon has extensive navigation experience, and many tenants of maintaining accuracy from navigation directly apply to robotic applications and may have manifested as a reduction in early complication rate.

Over the course of our study period of 3 years, we report a steep learning curve and a trend of increasing efficiency as suggested by the significantly shorter time required to place each screw after the first 20 cases (Figure-4). In our experience, the additional time needed to register and set-up the robot is compensated by making the process of instrumentation itself faster and streamlined, something that can be appreciated more in longer cases with more levels requiring instrumentation.

As reported elsewhere in the published literature, robotic assisted spinal instrumentation is safe with a higher accuracy rate compared to free hand and fluoroscopically guided techniques, something that is reflected in our findings as well. [4, 12, 17] Robotic systems have managed to achieve an accuracy rate of more than 95% which is similar to accuracy of image-guided navigation with reported accuracy rates of 85–95% with the added advantage of reducing surgeon stress and fatigue. [2, 3, 6, 8, 10, 16, 18, 19] The majority of centers across the country which have the capability of robotic spine surgery, utilize different systems such as the SpineAssist (Mazor Robotics Ltd., Caesarea, Israel) Renaissance (Mazor Robotics Ltd., Caesarea, Israel) or the Excelsius GPS (Globus Medical, Inc., Audubon, Pennsylvania). [12] To our knowledge, this is the second reported series of cases being completed with the Mazor X robotic system. [3]

Advantages of utilizing surgical robot for spinal instrumentation

It is likely that overtime, surgical intelligence will make it easier for the operating surgeon to perform complex tasks, decreasing error. [8] Although a surgeon’s expert judgement is required to oversee the system and intervene to ensure patient safety, the robotic system does add safety and supplements the capabilities of the surgeon especially when performing percutaneous minimally invasive surgery, deformity surgery, unusual transpedicular trajectories, or in challenging cases such as revision operations where anatomy is distorted. [8, 10, 20] Robots are reliable for spinal instrumentation but surgeons should be familiar with the advantages and strengths of the equipment as well as have an understanding of its limitations. [21]

Ideally, 3D imaging can help determine accuracy of screw placement, which is commonly used either during or after the placement (post-instrumentation spin). We propose that accuracy of spinal instrumentation placement can be evaluated by the surgeon on intra- and postoperative fluoroscopy images, hereby avoiding higher radiation exposure to the patients. [7, 22] In this series, no patient had any clinical symptoms to prompt 3D imaging or consider re-operation within one year of the initial surgery. Literature suggests that there is no gold standard method to assess screw placement accuracy and each method has its own limitations. [10, 22]

Current challenges of robot-assisted spine surgery and future outlook

We believe that despite our limited use of the robot in some particular settings such as oncology and trauma, it has broad utility. There are certainly some improvements that can be made in the system such as the ease of registration as researchers have reported failure of registration in some cases, although we did not encounter any registration failures in our experience. [2] Several colleagues have described skiving of the drill bit on the steep bony slope as a cause of inaccuracy which is certainly a potential area of improvement. [3, 9, 12] In our experience, we were able to avoid this challenge by using a cutting technique for the initial placement of the drill. The addition of the newer Midas for Mazor X platform, a high-speed drill with over 70000 rotations per minute, placed through the dilator to directly cannulate the pedicle at high speed, is a favorable technique for skive prevention. Of note, there is a significant cost associated with the acquisition of the technology which may limit its initial use to large volume centers. [11]

Strengths and Limitations

This is only the second series on robot-assisted spinal instrumentation with the Mazor X robot, an innovative technology used in our department over the past 3 years. Our article reports many relevant outcomes in a reasonably large patient cohort, including accuracy and complications, and contains a learning-curve analysis, which is novel.

Our study has several limitations that should be mentioned. It is a retrospective single-center and single-surgeon series, which makes generalization of the findings to other centers and settings difficult. Screw accuracy was based on plain x-ray imaging, whereas CT-based imaging might be more powerful to detect minor breaches. We did not include a “control group” of patients treated with either free-hand or 3D navigation-based spinal instrumentation, hence we cannot evaluate superiority of one vs. the other technique. Moreover, our variable list did not include any patient reported or objective outcome measures, which leaves questions about the clinical benefit of robot-assisted spine surgery for the patient well-being currently unanswered. [23] Larger, multi-center studies are on the way to clarify the comparative clinical benefits of robotic vs. navigated vs. free-hand techniques for spinal instrumentation. [24]

From this single-center, single-surgeon series we conclude that screw placement in robot-assisted spine surgery is highly reliable, accurate and precise from, whereas OR workflow and efficiency improve significantly after a learning curve of approximately 20 cases.

ALIF

Anterior Lumbar Interbody Fusion

AP

Antero-posterior

BMI

Body Mass Index

CT

Computed Tomography

EMG

Electromyography

OR

Operating Room

TLIF

Trans-foraminal Lumbar Interbody Fusion

PSIS

Posterior Superior Iliac Spine

SUBMISSION STATEMENT

The authors certify that this is a unique submission and is not being considered for publication, in part or in full, with any other source in any medium. All persons who meet authorship criteria are listed as authors, and all authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing, or revision of the manuscript.

FUNDING SOURCES

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

DECLARATIONS OF INTEREST

Anand Veeravagu: Nuvasive, Medtronic, Surgical Theater, OsteoCentric

All other authors: None

ACKNOWLEDGEMENTS

None

Benech, C.A., et al., Navigated robotic assistance results in improved screw accuracy and positive clinical outcomes: an evaluation of the first 54 cases. J Robot Surg, 2020. 14(3): p. 431–437.
Hu, X., D.D. Ohnmeiss, and I.H. Lieberman, Robotic-assisted pedicle screw placement: lessons learned from the first 102 patients. Eur Spine J, 2013. 22(3): p. 661–6.
Khan, A., et al., Next-Generation Robotic Spine Surgery: First Report on Feasibility, Safety, and Learning Curve. Oper Neurosurg (Hagerstown), 2019. 17(1): p. 61–69.
Molliqaj, G., et al., Accuracy of robot-guided versus freehand fluoroscopy-assisted pedicle screw insertion in thoracolumbar spinal surgery. Neurosurg Focus, 2017. 42(5): p. E14.
Schatlo, B., et al., Safety and accuracy of robot-assisted versus fluoroscopy-guided pedicle screw insertion for degenerative diseases of the lumbar spine: a matched cohort comparison. J Neurosurg Spine, 2014. 20(6): p. 636–43.
Tarawneh, A.M. and K.M. Salem, A Systematic Review and Meta-analysis of Randomized Controlled Trials Comparing the Accuracy and Clinical Outcome of Pedicle Screw Placement Using Robot-Assisted Technology and Conventional Freehand Technique. Global Spine J, 2021. 11(4): p. 575–586.
Hu, X. and I.H. Lieberman, What is the learning curve for robotic-assisted pedicle screw placement in spine surgery? Clin Orthop Relat Res, 2014. 472(6): p. 1839–44.
Campbell, D.H., et al., The Clinical Impact of Image Guidance and Robotics in Spinal Surgery: A Review of Safety, Accuracy, Efficiency, and Complication Reduction. Int J Spine Surg, 2021. 15(s2): p. S10-s20.
Urakov, T.M., et al., Initial academic experience and learning curve with robotic spine instrumentation. Neurosurg Focus, 2017. 42(5): p. E4.
Gautschi, O.P., et al., Clinically relevant complications related to pedicle screw placement in thoracolumbar surgery and their management: a literature review of 35,630 pedicle screws. Neurosurg Focus, 2011. 31(4): p. E8.
D'Souza, M., et al., Robotic-Assisted Spine Surgery: History, Efficacy, Cost, And Future Trends. Robot Surg, 2019. 6: p. 9–23.
McKenzie, D.M., et al., Robotics in spine surgery: A systematic review. J Clin Neurosci, 2021. 89: p. 1–7.
O'Connor, T.E., et al., Mazor X Stealth Robotic Technology: A Technical Note. World Neurosurg, 2021. 145: p. 435–442.
Härtl, R., et al., Worldwide survey on the use of navigation in spine surgery. World Neurosurg, 2013. 79(1): p. 162–72.
Lieberman, I.H., S. Kisinde, and S. Hesselbacher, Robotic-Assisted Pedicle Screw Placement During Spine Surgery. JBJS Essent Surg Tech, 2020. 10(2): p. e0020.
Siddiqui, M.I., et al., Robot-Assisted Pedicle Screw Placement: Learning Curve Experience. World Neurosurg, 2019. 130: p. e417-e422.
Schröder, M.L. and V.E. Staartjes, Revisions for screw malposition and clinical outcomes after robot-guided lumbar fusion for spondylolisthesis. Neurosurg Focus, 2017. 42(5): p. E12.
Vardiman, A.B., et al., Does the accuracy of pedicle screw placement differ between the attending surgeon and resident in navigated robotic-assisted minimally invasive spine surgery? J Robot Surg, 2020. 14(4): p. 567–572.
Vardiman, A.B., et al., Pedicle screw accuracy in clinical utilization of minimally invasive navigated robot-assisted spine surgery. J Robot Surg, 2020. 14(3): p. 409–413.
Wang, M.Y., Steele, W.J., & Urakov, T., Advanced Robotic Spine Surgery: A Case-Based Approach. First ed. 2021, Boca Raton: Taylor & Francis Group, CRC Press.
Stumpo, V., et al., Global adoption of robotic technology into neurosurgical practice and research. Neurosurgical Review, 2021. 44(5): p. 2675–2687.
Aoude, A.A., et al., Methods to determine pedicle screw placement accuracy in spine surgery: a systematic review. Eur Spine J, 2015. 24(5): p. 990–1004.
Stienen, M.N., et al., Objective measures of functional impairment for degenerative diseases of the lumbar spine: a systematic review of the literature. Spine J, 2019. 19(7): p. 1276–1293.
Staartjes, V.E., et al., The European Robotic Spinal Instrumentation (EUROSPIN) study: protocol for a multicentre prospective observational study of pedicle screw revision surgery after robot-guided, navigated and freehand thoracolumbar spinal fusion. BMJ Open, 2019. 9(9): p. e030389.

Table-1: Patient demographics and surgery related characteristics. Results are presented in mean (SD) or count (%)

Age in years	62.7	9.32
Body Mass Index in kg/m²	28.3	4.1
Sex
Male	15	53.6%
Female	13	46.4%
Approach
Percutaneous	15	53.6%
Open	13	46.4%
Indications
Spondylolisthesis	15	53.6%
Degenerative Disc Disease	8	28.6%
Concurrent anterior column surgery (ALIF)	16	57.1%
Average time per screw in minutes	7.6	2.4
Post-operative hospital length of stay in days	5.7	1.5
Follow-up time in months	13.0	12.9
Total	n=28	100%

Table-2: Detailed list of cases, indicating patient age, indication for surgery, levels of instrumentation, number (No.) of screws placed in total / with robotic guidance, screw accuracy (based on postoperative x-ray imaging) and comments. LDDD = lumbar degenerative disc disease; Degen = degenerative; GSW = Gun-Shot Wound

Study ID	Age	Indication	Levels of instrumentation	No. of screws total/ placed with robot	Screw accuracy, based on postoperative imaging	Comments
1	57	Spondylolisthesis (Degen)	L5-S1	4/4	accurate
2	66	LDDD	L4-S1	6/6	accurate
3	58	Spondylolisthesis (Degen)	L4-S1	5/5	accurate	Left L5 screw – grade 4
4	67	LDDD	L3-S1	8/8	accurate
5	77	LDDD	L3-S1	8/8	accurate
6	54	Spondylolisthesis (Degen)	L5-S1	4/4	accurate
7	69	Spondylolisthesis (Degen)	L4-L5	4/4	accurate
8	56	Spondylolisthesis (Degen)	L4-L5	4/4	accurate
9	66	LDDD	L2-S1	4/4	accurate
10	72	LDDD (Degen scoliosis)	L4-L5	4/4	accurate
11	71	LDDD, thoracic myelopathy	T10-S2AI	13	accurate
12	63	Spondylolisthesis, scoliosis (Degen)	L1-S1	6/6	accurate
13	51	Spondylolisthesis (Degen)	L5-S1	4/4	accurate
14	73	Spondylolisthesis (Degen)	L3-L5	6/6	accurate
15	63	Metastatic prostate cancer	T9-T11	4/1	accurate	One T9, two T11 screws – grade 3
16	59	LDDD, stenosis	L3-L4	4/4	accurate
17	72	L1 burst fracture	T10-L4	12/12	accurate
18	68	LDDD, stenosis, scoliosis	T10-S2AI	13	accurate
19	68	Spondylolisthesis (Degen)	L4-S1	6/6	accurate
20	48	GSW T11 fracture	T10-T12	4/4	accurate
21	72	Spondylolisthesis (Degen)	L4-S1	6/6	accurate
22	66	Spondylolisthesis (Degen)	L3-L4 TLIF	4/4	accurate	Both left sided screws revised – grade 2
23	48	Spondylolisthesis (Degen)	L4-S2AI	6/6	accurate
24	75	Spondylolisthesis (Degen)	L4-5	4/4	accurate
25	57	Spondylolisthesis (Degen)	L4-L5	4/4	accurate
26	68	Spondylolisthesis (Degen)	L3-L5	6/6	accurate
27	46	Spondylolisthesis (Degen)	L5-S1	4/4	Possible caudal breach at left S1 screw
28	45	L3 Hemangiopericytoma	L2-L4	5/5	accurate

Competing interest reported. Anand Veeravagu: Consultant – Medtronic, Stryker, Nuvasive, Surgical Theater, Osteocentric. All other authors: None Source of Funding: Kuhlmann Fd for Neurosurgical Fd

Experience with the Utilization of New Generation Shared Control Robotic System for Spinal Instrumentation

Status:

Version 1

Abstract

Figures

Introduction

Materials And Methods

Results

Patient sample

Success of screw placement and revision rate

Time needed for instrumentation and learning curve

Discussion

Our experience

Advantages of utilizing surgical robot for spinal instrumentation

Current challenges of robot-assisted spine surgery and future outlook

Strengths and Limitations

Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Status:

Version 1