Robot-assisted Spine Surgery Research Articles

Artificial Intelligence and Robotics in Spine Surgery.

Study Design:Narrative review.Objectives:Artificial intelligence (AI) and machine learning (ML) have emerged as disruptive technologies with the potential to drastically affect clinical decision making in spine surgery. AI can enhance the delivery of spine care in several arenas: (1) preoperative patient workup, patient selection, and outcome prediction; (2) quality and reproducibility of spine research; (3) perioperative surgical assistance and data tracking optimization; and (4) intraoperative surgical performance. The purpose of this narrative review is to concisely assemble, analyze, and discuss current trends and applications of AI and ML in conventional and robotic-assisted spine surgery.Methods:We conducted a comprehensive PubMed search of peer-reviewed articles that were published between 2006 and 2019 examining AI, ML, and robotics in spine surgery. Key findings were then compiled and summarized in this review.Results:The majority of the published AI literature in spine surgery has focused on predictive analytics and supervised image recognition for radiographic diagnosis. Several investigators have studied the use of AI/ML in the perioperative setting in small patient cohorts; pivotal trials are still pending.Conclusions:Artificial intelligence has tremendous potential in revolutionizing comprehensive spine care. Evidence-based, predictive analytics can help surgeons improve preoperative patient selection, surgical indications, and individualized postoperative care. Robotic-assisted surgery, while still in early stages of development, has the potential to reduce surgeon fatigue and improve technical precision.

Telerobotic Spinal Surgery Based on 5G Network: The First 12 Cases.

ObjectiveThe purpose of this study was to determine the efficacy and feasibility of 5th generation wireless systems (5G) telerobotic spinal surgery in our first 12 cases. MethodsA total of 12 patients (5 males, 7 females; age, 23–71 years) with spinal disorders (4 thoracolumbar fractures, 6 lumbar spondylolisthesis, 2 lumbar stenosis) were treated with 5G telerobotic spinal surgery. Sixty-two pedicle screws were implanted.ResultsAll patients had substantial relief from their symptoms. Screw placements were classified using Gertzbein-Robbins criteria. There were 59 grade A, 3 grade B. Mean operation time was 142.5 ± 46.7 minutes. Mean guiding wire insertion time was 41.3 ± 9.8 minutes. The deviation between the planned and actual positions was 0.76 ± 0.49 mm. No intraoperative adverse event was found. Conclusion5G remote robot-assisted spinal surgery is accurate and reliable. We conclude that 5G telerobotic spinal surgery is both efficacious and feasible for the management of spinal diseases with safety.

Robotic-assisted spine surgery: Application of preoperative and intraoperative imaging

Technological advancements in spine surgery have paved the way for improved patient outcomes, and robotic-assistance has become a frontrunner in spine research and development. However, its use and understanding is yet to be fully determined. The purpose of this chapter is to highlight the applications of current robotic systems in spine surgery. The chapter focuses on current imaging modalities and their uses, as well as future imaging techniques that may broaden the indications for robotic use, while maintaining optimal outcomes.

Research on the accuracy of three-dimensional localization and navigation in robot-assisted spine surgery.

Compared with traditional surgical methods, which only rely on doctors' experience, three-dimensional robot-assisted navigation technology could locate the lesion more accurately. The transformation principle of three-dimensional navigation system was analyzed. The surgical path was planned on the reconstructed three-dimensional model. The experimental data of positioning position and posture were used as two important parameters to evaluate the accuracy of the robot-assisted spine surgery navigation system. The final experimental results show that the accuracy of the positioning and navigation position of the robot-assisted surgical navigation system was 2.54 ± 0.15mm (range 2.25-2.76 mm). The accuracy of positioning and navigation posture was 2.55 ° ± 0.49°(range 1.92°-3.21°). It could be seen the three-dimensional positioning and navigation system proposed in this study had a high accuracy and could basically meet the basic accuracy requirements of spine surgery.

Robotic-assisted Spine Surgery: A Review of its Development, Outcomes, and Economics on Practice

Purpose: Improper pedicle screw placement can lead to increased complications and the need for revision surgery. The purpose of this article is to review the history of robotic assistance in spine surgery, along with the current data on its clinical outcomes, potential advantages, and economics on practice. Methods: Review of the literature. Results: A review of the current literature demonstrated that intrapedicular accuracy has shown to be either superior or equivalent to a free-hand technique. Radiation exposure with robotic assistance is generally similar to free-hand, with a trend toward a lesser exposure following increased experience. Operative times, outcomes, and complication rates have been variable between prospective and retrospective studies, with mostly equivalent results when compared with free-hand screw placement. Conclusions: Higher-level studies (level I and II) have demonstrated similar clinical outcomes and pedicle screw accuracy when compared with the free-hand technique. As with most new technology, a learning curve is apparent, with the potential for a decrease in radiation exposure and economic benefit over time.

A Robot-Assisted Spine Surgery System Based on Intraoperative 2D Fluoroscopy Navigation

In this paper, a robotic system based on intraoperative 2D fluoroscopy navigation in which fluoroscopy images are obtained by C-arm popularized in the clinic, for spine surgery is proposed. The procedure of robot-assisted spine surgery is designed and described. An improved special 6-dof hybrid robot considering both the stiffness and workspace is proposed. And the kinematic model and jacobian matrix of robot are established. To realize fluroscopy images acquisition and avoid interfering with the patient during the process of positioning, human-robot cooperation based on fuzzy variable admittance control considering arm stiffness which would influence the stability of robot, is applied in robotic system. In addition, navigation techniques containing a novel bi-planar design, a robust circular control point detector and closed-loop positioning of tool, based on fluoroscopy images are proposed. In experiments, kinematic model of hybrid robot is test based on laser tracker and the distance error is 0.17 mm which is much smaller than the motion range. The effect of tool weight compensation is measured and the max mean force and torque errors are 0.7477N and 0.0617 N.M. The experimental results could meet requirements in human-robot cooperation. Furthermore, we test the the robotic system proposed in this paper on spine model bone and cadaver with the help of surgeons. The experimental results are validated by 2D image c-arm-based and 3D image CT-based and considered clinically acceptable.

Navigated robotic assistance improves pedicle screw accuracy in minimally invasive surgery of the lumbosacral spine: 600 pedicle screws in a single institution.

In the emerging field of robot-assisted spine surgery, radiographic evaluation of pedicle screw accuracy in the surgical setting is of high interest. Advances in medical imaging have improved the accuracy of pedicle screw placement, from fluoroscopy-guided to computer-aided navigation. A retrospective, institutional review board-exempt review of the first 106 navigated robot-assisted spine surgery cases was performed. Radiographic evaluation of preoperative and postoperative computerized tomography (CT) scans were collected. In the first 106 cases, 630 lumbosacral pedicle screws were placed. Thirty screws were placed in five patients without the robot because of surgeon discretion. Of the 600 pedicle screws inserted by navigated robotic guidance, only 1.5% (9/600) were repositioned intraoperatively. This study demonstrated a high level of accuracy (98.2%) in terms of grade A or B pedicle screw breach scores in the clinical use of navigated, robot-assisted surgery in its first 101 cases.

Robotic-Assisted Spine Surgery: History, Efficacy, Cost, And Future Trends.

Robot-assisted spine surgery has recently emerged as a viable tool to enable less invasive and higher precision surgery. The first-ever spine robot, the SpineAssist (Mazor Robotics Ltd., Caesarea, Israel), gained FDA approval in 2004. With its ability to provide real-time intraoperative navigation and rigid stereotaxy, robotic-assisted surgery has the potential to increase accuracy while decreasing radiation exposure, complication rates, operative time, and recovery time. Currently, robotic assistance is mainly restricted to spinal fusion and instrumentation procedures, but recent studies have demonstrated its use in increasingly complex procedures such as spinal tumor resections and ablations, vertebroplasties, and deformity correction. However, robots do require high initial costs and training, and thus, require justification for their incorporation into common practice. In this review, we discuss the history of spinal robots along as well as currently available systems. We then examine the literature to evaluate accuracy, operative time, complications, radiation exposure, and costs – comparing robotic-assisted to traditional fluoroscopy-assisted freehand approaches. Finally, we consider future applications for robots in spine surgery.

New spinal robotic technologies.

Robotic systems in surgery have developed rapidly. Installations of the da Vinci Surgical System® (Intuitive Surgical, Sunnyvale, CA, USA), widely used in urological and gynecological procedures, have nearly doubled in the United States from 2010 to 2017. Robotics systems in spine surgery have been adopted more slowly; however, users are enthusiastic about their applications in this subspecialty. Spinal surgery often requires fine manipulation of vital structures that must be accessed via limited surgical corridors and can require repetitive tasks over lengthy periods of time - issues for which robotic assistance is well-positioned to complement human ability. To date, the United States Food and Drug Administration (FDA) has approved 7 robotic systems across 4 companies for use in spinal surgery. The available clinical data evaluating their efficacy have generally demonstrated these systems to be accurate and safe. A critical next step in the broader adoption of surgical robotics in spine surgery is the design and implementation of rigorous comparative studies to interrogate the utility of robotic assistance. Here we discuss current applications of robotics in spine surgery, review robotic systems FDA-approved for use in spine surgery, summarize randomized controlled trials involving robotics in spine surgery, and comment on prospects of robotic-assisted spine surgery.

Navigated robot-guided pedicle screws placed successfully in single-position lateral lumbar interbody fusion

Minimally invasive lateral interbody fusion has distinct advantages over traditional posterior approaches. When posterior stabilization is needed, percutaneous placement of pedicle screws from the lateral decubitus position may potentially increase safety and improve operative efficiency by precluding the need for repositioning. However, safe placement of pedicle screws in the lateral position remains technically challenging. This study describes the pedicle screw placement of single-position lateral lumbar interbody fusion (SP-LLIF) cases in which navigated robotic assistance was used. A single-surgeon, single-site, retrospective Institutional Review Board-exempt review of the first 55 SP-LLIF navigated robot-assisted spine surgery cases performed by the lead author was conducted. An orthopaedic surgeon evaluated screw placement using plain film radiographs. In addition, pedicle screw malposition, reposition, and return to operating room (OR) rates were collected. In the first 55 SP-LLIF cases, 342 pedicle screws were placed. The average patient age and body mass index were 67 years and 29.5 kg/m2, respectively. Of the 342 screws placed, 4% (14/342) were placed manually without the robot, due to surgeon discretion. Of the 328 screws placed with the robot, 2% (7/328) were repositioned based on the surgeon’s discretion, resulting in a 98% navigated robot-assisted pedicle screw placement success rate. In this cohort there were no revisions due to malpositioned screws. No complications due to screw placement were reported. This study demonstrates a high level (98%) of successful surgeon-assessed pedicle screw placement in minimally invasive navigated robot-assisted SP-LLIF, with no malpositions requiring a return to the OR.

Does the accuracy of pedicle screw placement differ between the attending surgeon and resident in navigated robotic-assisted minimally invasive spine surgery?

Robotic assistance with integrated navigation is an area of high interest for improving the accuracy of minimally invasive pedicle screw placement. This study analyzes the accuracy of pedicle screw placement between an attending spine surgeon and a resident by comparing the left and right sides of the first 101 consecutive cases using navigated robotic assistance in a private practice clinical setting. A retrospective, Institutional Review Board-exempt review of the first 106 navigated robot-assisted spine surgery cases was performed. One attending spine surgeon and one resident performed pedicle screw placement consistently on either the left or right side (researchers were blinded). A CT-based Gertzbein and Robbins system (GRS) was used to classify pedicle screw accuracy, with grade A or B considered accurate. There were 630 consecutive lumbosacral pedicle screws placed. Thirty screws (5 patients) were placed without the robot due to surgeon discretion. Of the 600 pedicle screws inserted by navigated robotic guidance (101 patients), only 1.5% (9/600) were repositioned intraoperatively. Based on the GRS CT-based grading of pedicle breach, 98.67% (296/300) of left-side screws were graded A or B, 1.3% (4/300) were graded C, and 0% (0/300) were graded D. For the right-side screws, 97.67% (293/300) were graded A or B, 1.67% (5/300) were graded C, and 0.66% (2/300) were graded D. This study demonstrated a high level of accuracy (based on GRS) with no significant differences between the left- and right-side pedicle screw placements (98.67% vs. 97.67%, respectively) in the clinical use of navigated, robot-assisted surgery.

Four Year Experience of Robot-Assisted Pedicle Screw Placement: An Australian Prospective Analysis

Abstract INTRODUCTION Robot-assisted surgery has emerged as an innovative and minimally-invasive technique, touted as superior to the traditional free-hand technique of pedicle screw fixation in spinal fusion surgery. Complications of misplaced pedicle screws include inadequate fixation and surgical failure requiring revision, neural injury, cerebrospinal fluid (CSF) leak, vascular injury, and facet joint trauma with sequela of adjacent segment disease. Literature reports an incidence of pedicle screw misplacement in up to 10% with free-hand technique. Robot-assisted surgery has reported superiority with increased accuracy of pedicle screw placement and reduced complication rates. This prospective multi-institutional single cohort analysis reports the outcomes in robot-assisted spinal fusion surgery in Melbourne, Australia over 4 yr. METHODS Data was prospectively collected from 2015 to 2019 from robot-assisted spinal surgeries performed by 2 surgeons across 2 institutions. Postoperative spinal computed tomography (CT) scan was compared to preoperative CT based planning to determine the accuracy of pedicle screw placement to 0.1 mm. Accurate pedicle screw placement was defined as within 2.0 mm from the target. Intraoperative radiation exposure time, operative time and length of hospital stay were also collected. RESULTS The total number of cases was 164 and the total number of screws placed was 744. Accurate pedicle screw placement was 98.65%. Average intraoperative radiation exposure time was 9.9 s. Average operative time for single-level surgery was 74 min. The average length of hospital stay was 2.4 d. CONCLUSION The authors conclude that robot-assisted pedicle screw placement is a safe and highly accurate adjunct to spinal surgery. While robot-assisted spinal surgery significantly improves patient outcomes with reduced patient morbidity and revision rates, it has limitations in primary capital expenditure, consumable costs and, in training and accreditation. It is the authors’ opinion that the robot-assisted spinal surgery technique requires nuanced patient selection and expertise in the traditional free-hand method is still essential in the event of technological failure.

Complications of Robotic Spine Surgery

Abstract INTRODUCTION Robotic assisted spine surgery is becoming increasingly widespread during spinal instrumentation cases. We report our early experience utilizing robotic assisted spinal instrumentation. The aim of the study is to review complications experienced during robotic assisted spinal instrumentation including analysis of pedicle screw accuracy, medical, and surgical complications. METHODS This study was performed as a descriptive, retrospective study. We reviewed cases over the course of 12 mo and examined all operative and postoperative data including pedicle screw accuracy, medical, and surgical complications related to the surgery and hospital stay. Pedicle screw accuracy was assessed utilizing the Gertzbein–Robbins scale. RESULTS The study included 67 consecutive patients undergoing 68 robotic-assisted procedures. Patient ages ranged from 20 to 90 yr. There were 37 males and 30 females. Indications for surgery included degenerative disease 33, trauma 24, tumor 5, and infection 1. There were a total of 592 pedicle screws placed. A total of 26 (4.3%) screws were revised intraoperatively using the robot. An additional 32 (5.4%) screws were aborted from robotic assistance. Pedicle screw accuracy was noted to be excellent with 97% of screws rated as clinically acceptable. There were 4 deaths (5.8%), 18 patients (26%) experienced a medical complication, 26 patients (38%) experienced a surgical complication and 6 patients (9%) experienced both a medical and surgical complication. A total of 38 patients (55%) experienced any morbidity or mortality related to surgery. Mean operative time was 277 min. CONCLUSION We report our initial experience with robotic-assisted spine surgery. Pedicle screw accuracy was noted to be high. We experienced a broad array of medical and surgical complications. The high complication rate may be due to long operative times and presence of a learning curve utilizing the robot. Further study is warranted to note if more experience decreases complication rates. It is unclear if the complication rate is significantly different compared to traditional methods of spinal instrumentation.

Automatic pedicle screw planning using atlas-based registration of anatomy and reference trajectories

An algorithm for automatic spinal pedicle screw planning is reported and evaluated in simulation and first clinical studies. A statistical atlas of the lumbar spine (N = 40 members) was constructed for active shape model (ASM) registration of target vertebrae to an unsegmented patient CT. The atlas was augmented to include ‘reference’ trajectories through the pedicles as defined by a spinal neurosurgeon. Following ASM registration, the trajectories are transformed to the patient CT and accumulated to define a patient-specific screw trajectory, diameter, and length. The algorithm was evaluated in leave-one-out analysis (N = 40 members) and for the first time in a clinical study (N = 5 patients undergoing cone-beam CT (CBCT) guided spine surgery), and in simulated low-dose CBCT images. ASM registration achieved (2.0 ± 0.5) mm root-mean-square-error (RMSE) in surface registration in 96% of cases, with outliers owing to limitations in CT image quality (high noise/slice thickness). Trajectory centerlines were conformant to the pedicle in 95% of cases. For all non-breaching trajectories, automatically defined screw diameter and length were similarly conformant to the pedicle and vertebral body (98.7%, Grade A/B). The algorithm performed similarly in CBCT clinical studies (93% centerline and screw conformance) and was consistent at the lowest dose levels tested. Average runtime in planning five-level (lumbar) bilateral screws (ten trajectories) was (312.1 ± 104.0) s. The runtime per level for ASM registration was (41.2 ± 39.9) s, and the runtime per trajectory was (4.1 ± 0.8) s, suggesting a runtime of ~(45.3 ± 39.9) s with a more fully parallelized implementation. The algorithm demonstrated accurate, automatic definition of pedicle screw trajectories, diameter, and length in CT images of the spine without segmentation. The studies support translation to clinical studies in free-hand or robot-assisted spine surgery, quality assurance, and data analytics in which fast trajectory definition is a benefit to workflow.

Pedicle screw accuracy in clinical utilization of minimally invasive navigated robot-assisted spine surgery

In the emerging field of robot-assisted spine surgery, the radiographic evaluation of pedicle screw accuracy in clinical application is an area of high interest. This study describes the pedicle screw accuracy of the first 56 consecutive cases in which navigated robotic assistance was used in a private practice clinical setting. A retrospective, Institutional Review Board-exempt review of the first 56 navigated robot-assisted spine surgery cases was performed. Pedicle screw malposition, reposition, and return to operating room (OR) rates were collected. A CT-based Gertzbein and Robbins system (GRS) was used to classify pedicle screw accuracy. In the first 56 robotic cases, 356 total pedicle screws were placed. Eight screws were placed without the robot due to surgeon discretion. Of the 348 pedicle screws inserted by navigated robotic guidance, only 2.6% (9/348) were repositioned, resulting in a 97.4% (339/348) successful screw placement rate. The average age was 64, and 48% were female. Average body mass index was 31 kg/m2. Based on the GRS CT-based grading, 97.7% (340/348) were graded A or B, 1.7% (6/348) screws were graded C, and only 0.6% (2/348) of screws were graded D. Two complications, explantation of interbody and vacuum-assisted wound closure, were reported as requiring a return to the OR, but these were not related to robotic guidance or pedicle screws. This study demonstrated a high level of accuracy (97.7%) in the first 56 cases using navigated, robot-assisted surgery based on the GRS. There were two non-screw-related complications requiring return to the operating room.

Learning Curve for Robot-Assisted Percutaneous Pedicle Screw Placement in Thoracolumbar Surgery.

Study DesignRetrospective review of an initial cohort of consecutive patients undergoing robot-assisted pedicle screw placement.PurposeWe aimed to evaluate the learning curve, if any, of this new technology over the course of our experience.Overview of LiteraturePercutaneous pedicle screws have specific advantages over open freehand screws. However, they require intraoperative imaging for their placement (e.g., fluoroscopy and navigation) and require increased surgeon training and skill with the learning curve estimated at approximately 20–30 cases. To our knowledge, this is the first study that measures the learning curve of robot-guided purely percutaneous pedicle screw placement with comprehensive objective postoperative computed tomography (CT) scoring, time per screw placement, and fluoroscopy time.MethodsWe included the first 80 consecutive patients undergoing robot-assisted spinal surgery at Melbourne Private Hospital. Data were collected for pedicle screw placement accuracy, placement time, fluoroscopy time, and revision rate. Patient demographic and relevant perioperative and procedural data were also collected. The patients were divided equally into four sub-groups as per their chronological date of surgery to evaluate how the learning curve affected screw placement outcomes.ResultsTotal 80 patients were included; 73 (91%) had complete data and postoperative CT imaging that could help assess that placement of 352 thoracolumbar pedicle screws. The rate of clinically acceptable screw placement was high (96.6%, 95.4%, 95.6%, and 90.7%, in groups 1 to 4, respectively, p=0.314) over time. The median time per screw was 7.0 minutes (6.5, 7.0, 6.0, and 6.0 minutes in groups 1 to 4, respectively, p=0.605). Intraoperative revision occurred in only 1 of the 352 screws (0.3%).Conclusions We found that robot-assisted screw placement had high accuracy, low placement time, low fluoroscopy time, and a low complication rate. However, there were no significant differences in these parameters at the initial experience and the practiced, experience placement (after approximately 1 year), indicating that robot-assisted pedicle screw placement has a very short (almost no) learning curve.

Robot-Assisted Pedicle Screw Placement: Learning Curve Experience

To describe the learning curve of pedicle screw placement using robot-assisted spine surgery of an experienced neurosurgeon and 2 supervised neurosurgical fellows. The first 120 cases of robot-assisted spine surgery at our institution were assessed. Patient variables included age, body mass index, and indication for surgery. Intraoperative variables included the vertebral level of screw placement, number of screws placed by each operator, intraoperative blood loss, and operative time. Postoperative variables included length of stay, discharge disposition, 30-day readmissions, wound complications, and hardware revisions. Screw accuracy was determined with image overlay analysis comparing planned screw trajectory on the navigation software with the intraoperative computed tomography scan with final screw placement. Two-dimensional accuracy was determined for the tip of the screw, tail of the screw, and angle at the screw was placed. The supervising physician and first fellow began utilizing the robot concurrently upon its arrival, and the second fellow began using the robot after the system had been in place for 7 months. Both experienced surgeon and first fellow displayed a learning curve and achieved statistically significant improvement of accuracy after 30 screws. The second fellow had significantly better accuracy than the experienced surgeon in his first 30 screws. There were no complications from hardware placement in either group. There were no returns to the operating room for hardware issues. Robot-assisted spine surgery is a safe, accurate method of pedicle screw instrumentation. Our data show similar learning adaptation rates for the first fellow and the experienced surgeon. Techniques learned by the attending surgeon were immediately transferable to a new learner, who was able to achieve a faster learning curve than both the first fellow and the experienced surgeon.

The use of robotics in minimally invasive spine surgery.

The field of spine surgery has changed significantly over the past few decades as once technological fantasy has become reality. The advent of stereotaxis, intra-operative navigation, endoscopy, and percutaneous instrumentation have altered the landscape of spine surgery. The concept of minimally invasive spine (MIS) surgery has blossomed over the past ten years and now robot-assisted spine surgery is being championed by some as another potential paradigm altering technological advancement. The application of robotics in other surgical specialties has been shown to be a safe and feasible alternative to the traditional, open approach. In 2004 the Mazor Spine Assist robot was approved by FDA to assist with placement of pedicle screws and since then, more advanced robots with promising clinical outcomes have been introduced. Currently, robotic platforms are limited to pedicle screw placement. However, there are centers investigating the role of robotics in decompression, dural closure, and pre-planned osteotomies. Robot-assisted spine surgery has been shown to increase the accuracy of pedicle screw placement and decrease radiation exposure to surgeons. However, modern robotic technology also has certain disadvantages including a high introductory cost, steep learning curve, and inherent technological glitches. Currently, robotic spine surgery is in its infancy and most of the objective evidence available regarding its benefits draws from the use of robots in a shared-control model to assist with the placement of pedicle screws. As artificial intelligence software and feedback sensor design become more sophisticated, robots could facilitate other, more complex surgical tasks such as bony decompression or dural closure. The accuracy and precision afforded by the current robots available for use in spinal surgery potentially allow for even less tissue destructive and more meticulous MIS surgery. This article aims to provide a contemporary review of the use of robotics in MIS surgery.

Robotic-assisted navigated minimally invasive pedicle screw placement in the first 100 cases at a single institution

Proper pedicle screw placement is an integral part of spine fusion requiring expertly trained spine surgeons. Advances in medical imaging guidance have improved accuracy. There is high interest in the emerging field of robot-assisted spine surgery; however, safety and accuracy studies are needed. This study describes the pedicle screw placement of the first 100 cases in which navigated robotic assistance was used in a private practice clinical setting. A single-surgeon, single-site retrospective Institutional Review Board-exempt review of the first 100 navigated robot-assisted spine surgery cases was performed. An orthopaedic surgeon evaluated screw placement using plain film radiographs. In addition, pedicle screw malposition, reposition, and return to operating room (OR) rates were collected. Results demonstrated a high level (99%) of successful surgeon assessed pedicle screw placement in minimally invasive navigated robot-assisted spine surgery, with no malpositions requiring return to the OR.

Guideline for Posterior Atlantoaxial Internal Fixation Assisted by Orthopaedic Surgical Robot.

Atlantoaxial transarticular facet screw fixation (Magerl technique) and C1 lateral mass screws combined with C2 pedicle screws fixation (Harms technique) are the most commonly used techniques for posterior internal fixation in the upper cervical spine. Upper cervical spinal surgery is a technically demanding and challenging procedure because of complicated anatomical structures and frequent occurrence of anomalies. Accurate insertion of screws allows for stable and secure internal fixation, which is necessary for both techniques. Traditional methods under fluoroscopic assistance in this region cannot meet the requirements of high levels of accuracy and security during the procedure. Robot‐assisted spinal surgery can provide accurate and reliable guidance during the screw insertion, which is evidenced in the literature. As a recently developed technique, robot‐assisted surgery is supposed to be performed by skilled surgeons who have received standard training for robotic surgery. The standardized upper cervical spinal surgery assisted by the robot system needs to be introduced to these surgeons. Based on the consensus of consultant specialists, the literature review, and our local experience, this guideline included the introduction of the robotic system, the workflow of robot‐assisted procedures, and the precautions to take during procedures. This guideline aims to provide a standardization of the robotic surgery for posterior atlantoaxial internal fixation.