Robot-assisted Spine Surgery Research Articles

Predictors of cost of admission for robot-assisted pedicle screw placement.

The authors investigated the predictors of cost of admission (CoA) for robot-assisted pedicle screw placement to assess the value of robotic systems in spine operations. Demographic, operative, and postoperative variables were retrospectively collected from 506 patients undergoing robot-assisted spine surgery utilizing the ExcelsiusGPS robot at two high-volume tertiary care centers from 2017 to 2023. Perioperative parameters were evaluated against total hospital admission cost utilizing the Kruskal-Wallis and Wilcoxon rank-sum tests followed by multivariable linear regression. The majority of patients were female (53.6%), 50-80 years of age (77.7%), and White (73.9%); had at least 1 comorbidity (58.1%); and presented with an average functional preoperative Frankel grade (57.5%). The mean CoA was $69,458 ± $47,910. On univariable analysis, demographic data including sex, age, race, and Frankel grade were not associated with CoA. The presence of a comorbidity, however, was associated with increased CoA (p < 0.001). Intraoperatively, one-third of the operations (31.8%) were revisions from prior operations and were subsequently associated with increased CoA (p = 0.021). Thoracic-level operations constituted roughly one-quarter of the cohort (24.1%) and were also associated with increased CoA (p < 0.001). Intraoperative durotomies occurred in 7.7% of patients, leading to increased CoA (p = 0.003). Extended surgical durations also demonstrated elevated CoA (p < 0.001). Postoperatively, the median length of stay (LOS) was 3 days, and an LOS of greater than 3 days was one of the primary drivers of cost (p < 0.001). Postoperative complications occurred in just 6.3% of the cohort but were also associated with increased CoA (p < 0.001). On multivariable analysis, LOS, number of screws placed, operative duration, and postoperative complications were the primary predictors of increased CoA. Understanding the drivers of cost in robot-assisted pedicle screw placement is crucial to elucidate the value associated with the use of robotic systems in spine surgery. These results indicate that patient and surgical complexity influence cost and that robotic systems may augment management in spine surgery. Further investigation is warranted to determine the long-term benefits and cost-effectiveness of new technologies compared with traditional techniques in spine surgery.

Limitations of current robot-assisted pedicle screw insertion systems

OBJECTIVE As robot systems for spine surgery have been developed, they have demonstrated a high degree of accuracy in screw placement without sacrificing safety or surgical efficiency. These robotic systems offer preoperative planning and real-time feedback to enhance surgical precision and mitigate human error. Nevertheless, limitations to their optimal performance remain. The authors analyzed the initial 100 cases of pedicle screw placements performed using the Mazor X robot at their institution, presenting case examples to illustrate the limitations that were experienced, and reviewed current literature on the limitations of robot-assisted spine surgery, emphasizing their impact on accuracy and safety. METHODS This was a retrospective review of the first 100 cases of robot-assisted pedicle screw placement at the authors’ institution between December 2019 and June 2024. All intraoperative CT scans were reviewed for screw accuracy. Malpositioned screws, near misses (screw deviation without injury to the patient), or abandoned robot-assisted attempts were identified, and the underlying reasons were evaluated to determine the limitations of current robot technology. RESULTS Of the first 100 cases of robot-assisted pedicle screw placement, there were 20 screw-related complications, of which 14 were near misses, 1 involved neurological injury caused by screw malposition, and 5 were cases in which a robot-assisted attempt was abandoned before manual screw placement. The authors identified the following limitations with current robot technology: registration errors, spine movement after registration, patient body habitus, artifact from metallic implants, poor bone differentiation, skiving, soft-tissue interference, and physical constraints. CONCLUSIONS Despite the advancements of spine robot systems, several limitations persist, especially in mobile or unstable spine locations and around critical structures. The authors’ experience, with provided case examples, further illustrates technical nuances important to understanding and navigating around these limitations. The need for standardized reporting metrics to evaluate and classify emerging technologies is highlighted, emphasizing ongoing technological innovation to enhance the efficacy of robot-assisted spine surgery.

Robotic pedicle screw placement with 3D MRI registration: moving towards radiation free robotic spine surgery

BACKGROUND CONTEXTPreoperative imaging for lumbar spine surgery often includes magnetic resonance imaging (MRI) for soft tissues and computer tomography (CT) for bony detail. While CT scans expose patients to ionizing radiation, whereas MRI scans do not. Emerging MRI techniques allow CT-like 3-dimensional (3D) visualization of bony structures, potentially removing the need for ionizing radiation from CT scans. PURPOSEThis study aims to explore the accuracy of robot-assisted lumbar pedicle screw placement based on preoperative CT-like 3D MRI as the data source for robotic registration. STUDY DESIGNHuman cadaveric study. METHODSCT-like 3D MRI scans of the lumbar spine were acquired in ten human cadavers. A robotic navigation platform was used to plan and navigate pedicle screw placement based on the CT-like 3D MRI. Postoperative CT scans assessed the accuracy of screw positioning compared to preoperative planning based on the Gertzbein-Robbins scale (GRS) and by direct measurement (mm). RESULTSA total of 100 lumbar pedicle screws were robotically placed in ten cadavers (L1 through L5 bilaterally) based on CT-like 3D MRI. On postoperative CT evaluation, 99.0% of the positioned screws achieved an acceptable grade on the GRS (Grade A: n=89 or Grade B: n=10), with 89.0% classified as Grade A and 10.0% as Grade B. Meaning that 89.0% of screws were fully contained within the pedicle (GRS A), and 10% had a minor cortical breach <2 mm (GRS B). The median deviation from the planned trajectory was 0.2 mm (axial IQR: 0.1 to 0.5 mm; sagittal: IQR: 0.1 to 0.4 mm), in both axial and sagittal planes. CONCLUSIONThis study showed that image registration of CT-like 3D MRI for robotic-assisted spine surgery is technically feasible and that accurate pedicle screw placement can be achieved without preoperative CT. Each CT-like 3D MRI was successfully registered for robotic navigation. CLINICAL SIGNIFICANCEThe results suggest that CT-like 3D MRI has the potential to be a radiation-free alternative for preoperative planning and navigation in lumbar spine instrumentation procedures.

Robotic-Assisted Decompression, Decortication, and Instrumentation for Minimally Invasive Transforaminal Lumbar Interbody Fusion.

Robotic-assisted spine surgery has been reported to improve the accuracy and safety of pedicle screw placement and to reduce blood loss, hospital length of stay, and early postoperative pain1. Minimally invasive transforaminal lumbar interbody fusion (MI-TLIF) is a procedure that is well suited to be improved by recent innovations in robotic-assisted spine surgery. Heretofore, the capability of robotic navigation and software in spine surgery has been limited to assistance with pedicle screw insertion. Surgical decompression and decortication of osseous anatomy in preparation for biological fusion had historically been outside the scope of robotic-assisted spine surgery. In 2009, early attempts to perform surgical decompressions in a porcine model utilizing the da Vinci Surgical Robot for laminotomy and laminectomy were limited by the available technology2. Recent advances in software and instrumentation allow registration, surgical planning, and robotic-assisted surgery on the posterior elements of the spine. A human cadaveric study assessed the accuracy of robotic-assisted bone laminectomy, revealing precision in the cutting plane3. Robotic-assisted facet decortication, decompression, interbody cage implantation, and pedicle screw fixation add automation and accuracy to MI-TLIF. A surgical robotic system comprises an operating room table-mounted surgical arm with 6 degrees of freedom that is physically connected to the patient's osseous anatomy with either a percutaneous Steinmann pin to the pelvis or a spinous process clamp. The Mazor X Stealth Edition Spine Robotic System (Version 5.1; Medtronic) is utilized, and a preoperative plan is created with use of software for screw placement, facet decortication, and decompression. The workstation is equipped with interface software designed to streamline the surgical process according to preoperative planning, intraoperative image acquisition, registration, and real-time control over robotic motion. The combination of these parameters enables the precise execution of preplanned facet joint decortication, osseous decompression, and screw trajectories. Consequently, this technique grants the surgeon guidance for the drilling and insertion of screws, as well as guidance for robotic resection of bone with a bone-removal drill. The exploration of robotically guided facet joint decortication and decompression in MI-TLIF presents an innovative alternative to the existing surgical approaches, which involve manual bone removal and can be less precise. Other robotic systems commonly utilized in spine surgery include the ROSA (Zimmer Biomet), the ExcelsiusGPS (Globus Medical), and the Cirq (Brainlab)4. The present video article provides a comprehensive guide for executing robotic-assisted MI-TLIF, including robotic facet decortication and osseous decompression. The introduction of advanced robotic technology capable of both decompressing bone and providing implant guidance represents a considerable advancement in robotic-assisted spine surgery. Software planning for robotic-assisted decortication of fused surfaces, surgical decompression, interbody cage placement, and pedicle screw placement allows for a less invasive and more precise MI-TLIF. Anticipated outcomes include reduction in low back and leg pain, improved functional status, and successful spinal fusion. Radiographic outcomes are expected to show restored foraminal height and solid bony fusion. Further, enhanced surgical precision, reduced approach-related morbidity by expanded robotic capabilities in spinal fusion surgery, and a shift from manual bone removal to precise mechanized techniques can be expected. The introduction of robotic-assisted facet joint decortication and decompression represents a notable milestone in spine surgery, enhancing patient care and technological advancement. Although robotic systems were initially predominantly employed for thoracic or lumbar pedicle screw insertion, recent advancements in robotic technology and software have allowed registration of the posterior elements. This advancement has expanded the utility of robotic systems to the initiation of spinal decompression and the decortication of facet joint surfaces, enhancing fusion procedures.Maintaining anatomical precision and preventing the need for re-registration are critical considerations in this surgical procedure. It is recommended to follow a consistent surgical workflow: facet decortication, decompression, modular screw placement, discectomy, insertion of an interbody cage, placement of reduction tabs, rod insertion, and set screw locking.The incorporation of robotic assistance in MI-TLIF is not exempt from a set of challenges. These encompass issues that pertain to dependability of the setup process, occurrences of registration failures, logistical complexities, time constraints, and the unique learning curve associated with the novel capability of robotic decompression of bone and facet joints. MI-TLIF= minimally invasive transforaminal lumbar interbody fusionOR = operating roomPSIS= posterior superior iliac spineCT = computed tomographyAP = anteroposterior.

Overcoming the Learning Curve in Robot-Assisted Spinal Surgery—How Does It Compare to O-Arm Navigation?

Background: Robotic systems have the potential to significantly enhance the accuracy and outcomes of spinal surgery. Adopting this new technology requires an examination of its learning curve and influencing factors. This study analyzes the learning curve associated with using the Mazor X Stealth Edition system for pedicle screw placement and performs a matched-pair analysis to compare operative durations between robot-assisted and navigation-based surgeries, evaluating the efficiency of the robotic system. Methods: We collected retrospective operative data from patients who underwent robot-assisted pedicle screw placements between December 2020 and June 2024 and conducted a cumulative sum (CuSUM) analysis to assess the learning curve, focusing on the robotic system’s setup duration. Additionally, we compared a group of patients who underwent robot-assisted pedicle screw placements with a pair-matched group who underwent O-arm-based navigation-assisted pedicle screw placements. Results: There was a notable decrease in the robotic setup duration, with a significant shift in trend observed after the first 20 cases. While the initial setup time was 24 minutes, it reduced to 17 minutes in later cases, reflecting a marked improvement in efficiency as the surgeon gained more experience with the robot. Conclusion: Our findings indicate there were no added difficulties using the robotic system compared to the navigation system. Moreover, the learning curve for the robotic system can be quickly surmounted, and it offers clear advantages over previous systems, making it a valuable tool for pedicle screw application.

Robot-Assisted Spine Surgery: The Pearls and Pitfalls.

Robot-assisted spine surgery has gained notable popularity among surgeons because of recent advancements in technology. These innovations provide several key benefits, including high screw accuracy rates, reduced radiation exposure, customized preoperative and intraoperative planning options, and improved ergonomics for surgeons. Despite the promising outcomes reported in literature, potential technical challenges remain across various robotic platforms. It is crucial for surgeons to remember that robotic platforms are shared-control systems, requiring the surgeon to maintain primary control throughout the procedure. To ensure patient safety, surgeons should be well versed in common technical pitfalls and strategies to mitigate these limitations.

History and trends of robot-assisted spine surgery

Spanning two decades since the 1st generation spinal robotics inception, the robot-assisted spine surgery (RSS) technology has evolved through generations, culminating in the 4th generation characterized by real-time visual navigation and wire-free screw placement. The fundamental principles of RSS technology include surgical planning, tracking, image registration, and robotic arm control technologies. Currently, RSS technology is maturely employed in thoracolumbar procedures and is progressively being applied in cervical surgeries, spinal tumor resections, and percutaneous operations, offering advantages in reducing tissue trauma and exposure to radiation, thereby improving patient outcomes. Emerging research also focuses on the cost-effectiveness of clinical applications and robot-specific complications. With the integration of artificial intelligence into surgical planning, RSS technology is poised to further incorporate emerging technologies and expand its application across a broader clinical spectrum.

Robotic-assisted spine surgery-a narrative review.

Emerging technologies have increasingly been adopted in spine surgery in the attempt to increase precision and improve outcomes. Robotic assistance is an area of significant interest, with proposed benefits including increased accuracy, decreased complication rates, and decreased radiation exposure. The purpose of this review is to provide an overview of the currently available robotic assistance systems and their associated outcomes and limitations. A review of national databases was performed using key terms "robotic", "spine", and "surgery" for literature from 2014 to 2023. Studies that aimed to describe the utilities of endoscopic surgeries, associated outcomes, limitations, and future directions were included. Studies that were not in English were excluded. This review includes a brief overview of the history of robotic spine surgery as well as its clinical outcomes, limitations, and future directions. Robotic-assisted spine surgery has seen increasing use in the attempt to increase precision and improve outcomes and has been associated with increased accuracy in pedicle screw placement and decreased complication rates. Barriers to its adoption include a significant learning curve, possibly longer operative cases, and significant associated costs. As robotic assistance continues to become increasingly popular in spine surgery, it is critical for surgeons to understand the technology available and the associated outcomes to make informed decisions when considering which system to incorporate into their practice.

Proficiency Development and Learning Curve in Robot-Assisted Spine Surgery Using the ExcelsiusGPS® System: Experience From a Single Institution.

Retrospective Cohort Study Objectives: Robot-assisted spine surgery (RASS) is a rapidly evolving technique with potential benefits for improving surgical outcomes. A number of studies on RASS learning curve have focused on early iterations of the Mazor robot. Limited research exists on the learning curve associated with using the Globus Medical ExcelsiusGPS® system. In this retrospective study, we aimed to evaluate the learning curve of RASS using the ExcelsiusGPS® system at a single institution. A total of 95 patients (541 screws) who underwent RASS between 2021 and 2022 were included. Variables including operative time, robot registration time, screw placement time, fluoroscopy utilization, and complications were analyzed. Statistical analysis was performed using descriptive statistics and two-sample t-tests. The average operative time significantly decreased after the first 14 cases, indicating a learning curve. However, no significant improvement was observed in robot registration time. Notably, screw placement time significantly improved after approximately 13 cases. When controlling for the number of levels fused, the trends remained consistent. Our study confirmed the presence of a learning curve in RASS using the ExcelsiusGPS® system and demonstrated rapid proficiency development. Our findings highlight the relatively quick learning curve of 1 RASS system.

Experience with the utilization of new-generation shared-control robotic system for spinal instrumentation.

Robotic assistance in spine surgery is emerging as an accurate, effective and enabling technology utilized in the treatment of patients with surgical spinal pathology. The safety and reproducibility of robotic assistance in the placement of pedicle screw instrumentation is still being investigated. The objective of this study was to present our experience of instrumented spinal fusion utilizing an intraoperative robotic guidance system. We retrospectively reviewed all cases of spinal instrumentation of the thoracic and lumbo-sacral spine using the Mazor X robotic system (Medtronic Inc, Minneapolis, MN, USA), performed at our institution by one surgeon between July 2017 and June 2020. Wilcoxon Rank test was used to compare time taken to place each screw during the first 20 cases and the cases thereafter. 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 20th case or 120 screws (8.70 vs. 5.42 min, P=0.008). No postoperative 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. 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.

Robotic-Assisted Spine Surgery: Role in Training the Next Generation of Spine Surgeons.

This study aimed to assess the degree of interest in robot-assisted spine surgery (RASS) among residents and to investigate the learning curve for beginners performing robotic surgery. We conducted a survey to assess awareness and interest in RASS among young neurosurgery residents. Subsequently, we offered a hands-on training program using a dummy to educate one resident. After completing the program, the trained resident performed spinal fusion surgery with robotic assistance under the supervision of a mentor. The clinical outcomes and learning curve associated with robotic surgery were then analyzed. Neurosurgical residents had limited opportunities to participate in spinal surgery during their training. Despite this, there was a significant interest in the emerging field of robotic surgery. A trained resident performed RASS under the supervision of a senior surgeon. A total of 166 screw insertions were attempted in 28 patients, with 2 screws failing due to skiving. According to the Gertzbein-Robbins classification, 85.54% of the screws were rated as grade A, 11.58% as grade B, 0.6% as grade C, and 1.2% as grade D. The clinical acceptance rate was approximately 96.99%, which is comparable to the results reported by senior experts and time per screw statistically significantly decreased as experience was gained. RASS can be performed with high accuracy within a relatively short timeframe, if residents receive adequate training.

Current status and prospects for the application of robot-assisted spine surgery

Traditional spine surgery frequently encounters difficulties with inadequate surgical visualization and high risk.Robot-assisted spine surgery is quickly evolving,particularly in screw placement,providing three-dimensional imaging and precise positioning to optimize the surgical process. Robot-assisted systems can increase surgical precision,reduce operating time and radiation exposure,and improve patient prognosis. They also have strong image recognition and analysis capabilities,reducing intraoperative instability and fatigue and allowing remote manipulation.While robot-assisted spine surgery has demonstrated noteworthy advantages in regards to screw placement accuracy and reduced radiation exposure,its effects on operative time remain subject to debate,with cost being a significant hindrance to widespread implementation.Long-term clinical validation and studies of outcomes are necessary for the extensive use of robotic-assisted spine surgery.Future priorities include the enhancement of surgical navigation and imaging,integration of artificial intelligence,improvement of telesurgical capabilities,expansion of robotic functionality,and the development of policy guidance and clinical guidelines to accompany the growth of technology.Robot-assisted spine surgery enhances accuracy and safety,and is anticipated to assume an increasingly crucial role in spine surgery as technology advances and becomes more widely available.

Single-Position Robotic-Assisted Prone Lateral Fusion: Technical Description and Feasibility.

Single-position lateral interbody fusion surgery has gained traction over the years because of reduced surgical time and improved operating theater workflow. With the introduction of robotics in spine surgery, surgeons can place pedicle screws with a high degree of accuracy and efficiency; moreover, the robot allows us to localize the disk space and perform endplate preparation accurately with minimal radiation. In this study, we discuss the potential synergistic benefits of integrating robotic-assisted spine surgery and singleposition prone lateral surgery. We share our technique and provide the operative nuances of using the Mazor X Stealth Edition system (Medtronic, Minneapolis, MN, USA). We highlighted the potential synergistic benefits of integrating both the prone lateral and robotic-assisted surgical techniques, including the challenges encountered. This approach is not meant to replace other techniques or be used in all patients. Instead, it adds to our arsenal for managing spine fusion.

Robot-Assisted Lumbar Pedicle Screw Placement Based on 3D Magnetic Resonance Imaging.

Human Cadaveric Study. This study aims to explore the feasibility of using preoperative magnetic resonance imaging (MRI), zero-time-echo (ZTE) and spoiled gradient echo (SPGR), as source data for robotic-assisted spine surgery and assess the accuracy of pedicle screws. Zero-time-echo and SPGR MRI scans were conducted on a human cadaver. These images were manually post-processed, producing a computed tomography (CT)-like contrast. The Mazor X robot was used for lumbar pedicle screw-place navigating of MRI. The cadaver underwent a postoperative CT scan to determine the actual position of the navigated screws. Ten lumbar pedicle screws were robotically navigated of MRI (4 ZTE; 6 SPGR). All MR-navigated screws were graded A on the Gertzbein-Robbins scale. Comparing preoperative robotic planning to postoperative CT scan trajectories: The screws showed a median deviation of overall 0.25mm (0.0; 1.3), in the axial plane 0.27mm (0.0; 1.3), and in the sagittal plane 0.24mm (0.0; 0.7). This study demonstrates the first successful registration of MRI sequences, ZTE and SPGR, in robotic spine surgery here used for intraoperative navigation of lumbar pedicle screws achieving sufficient accuracy, showcasing potential progress toward radiation-free spine surgery.

Optimizing milling parameters based on full factorial experiment and backpropagation artificial neural network of lamina milling temperature prediction model.

Milling operations of laminae in spinal surgery generate high temperatures, which can lead to thermal injury and osteonecrosis and affect the biomechanical effects of implants, ultimately leading to surgical failure. In this paper, a backpropagation artificial neural network (Bp-ANN) temperature prediction model was developed based on full factorial experimental data of laminae milling to optimize the milling motion parameters and to improve the safety of robot-assisted spine surgery. A full factorial experiment design were used to analyze the parameters affecting the milling temperature of laminae. The experimental matrixes were established by collecting the corresponding cutter temperature Tc and bone surface temperature Tb for the milling depth, feed speed and different bone densities. The Bp-ANN lamina milling temperature prediction model was constructed from experiment data. Increasing milling depth increases bone surface and cutter temperature. Increasing feed speed had little effect on cutter temperature, but decreased bone surface temperature. Increasing bone density of laminae increased cutter temperature. The Bp-ANN temperature prediction model had best training results in the 10th epoch, and there is no overfitting (training set R= 0.99661, validation set R= 0.85003, testing set R= 0.90421, all temperature data set R= 0.93807). The goodness of fit R of Bp-ANN was close to 1, indicating that the predicted temperature was in good agreement with the experiment measurements. This study can help spinal surgery-assisted robot to select appropriate motion parameters at different density bones to improve lamina milling safety.

Mazor X Robot-Assisted Pedicle Screw Placement: A Case Series

Pedicle screw placement is a well-established procedure in spine surgeries, and the utilization of robots in spinal surgery has been on the rise. This study aims to investigate the accuracy and screw placement time associated with the use of Mazor X robots in robotic-assisted pedicle screw placement. A retrospective case study was conducted on 12 patients with lumbar spine disease who underwent Mazor X robot-assisted surgery. Screw placement accuracy was assessed using the Gertzbein-Robinson classification. Additionally, total screw placement time and fluoroscopy time were documented for analysis. A total of 60 screws were placed in the 12 patients who received robotic-assisted pedicle screw placement. Of these screws, 98.3% were found to be within the safe zone. As the cases progressed, there was a noticeable decrease in total screw placement time and fluoroscopy time. Our findings suggest that Mazor X robotic-assisted spine surgery boasts high accuracy rates and demonstrates a decreasing trend in screw placement time and fluoroscopy time. To the best of our knowledge, our institution is the first in China to employ the Mazor X robot for pedicle screw placement surgeries and to document its associated characteristics.

Comparison of Radiographic and Patient-Reported Outcomes After Surgery in Adolescent Idiopathic Scoliosis Between Robotics and Navigation: An Analysis Using Propensity Score Matching.

Purpose This study aimed to compare the radiographic and patient-reported outcomes after surgery in adolescent idiopathic scoliosis (AIS) between robotics and navigation using propensity score matching. Methods This retrospective study involved 50 patients undergoing posterior spinal fusion for AIS between October 2016 and August 2022, utilizing navigation or robotic systems, analyzing them using propensity score matching. The evaluations included assessments using X-ray, Scoliosis Research Society 22-Item (SRS-22) Questionnaire, and CT, considering variables such as age, gender, BMI, and Lenke type. Results Post matching, 13 cases each from robotics and navigation groups were compared. No significant differences were found in the demographic variables, preoperative X-ray parameters, and preoperative SRS-22 scores between the two groups. The robotics group demonstrated a higher perfect accuracy rate (94.0% vs. 84.7%, p=0.005) and a lower deviation rate in pedicle screw placements (1.6% vs. 4.1%, p=0.223). At one year postoperatively, there were no significant differences in the X-ray parameters between both groups. Likewise, no significant differences were found in each domain of SRS-22, but function, self-image, mental health, and satisfaction scores were numerically higher in the robotics group. Conclusion The application of a spinal robotic system in AIS surgery presented enhanced screw accuracy and lower deviation rates, compared to navigation, with no significant differences observed in the X-ray parameters and each domain of SRS-22 at one year postoperatively. This suggests that, to improve patientquality of life (QOL), it is essential for robotic-assisted spine surgery to focus not only on screw accuracy but also on the development of novel robotic-assisted techniques.

Complications Have Not Improved With Newer Generation Robots.

Retrospective cohort study. The purpose of this study was to see whether upgrades in newer generation robots improve safety and clinical outcomes following spine surgery. All patients undergoing robotic-assisted spine surgery with the Mazor X Stealth EditionTM (Medtronic, Minneapolis, MN) from 2019 to 2022 at a combined orthopedic and neurosurgical spine service were retrospectively reviewed. Robot related complications were recorded. 264 consecutive patients (54.1% female; age at time of surgery 63.5 ± 15.3years) operated on by 14 surgeons were analyzed. The average number of instrumented levels with robotics was 4.2 ± 2.7, while the average number of instrumented screws with robotics was 8.3 ± 5.3. There was a nearly 50/50 split between an open and minimally invasive approach. Six patients (2.2%) had robot related complications. Three patients had temporary nerve root injuries from misplaced screws that required reoperation, one patient had a permanent motor deficit from the tap damaging the L1 and L2 nerve roots, one patient had a durotomy from a misplaced screw that required laminectomy and intra-operative repair, and one patient had a temporary sensory L5 nerve root injury from a drill. Half of these complications (3/6) were due to a reference frame error. In total, four patients (1.5%) required reoperation to fix 10 misplaced screws. Despite newer generation robots, robot related complications are not decreasing. As half the robot related complications result from reference frame errors, this is an opportunity for improvement.

A Single-Center Experience of Robotic-Assisted Spine Surgery in Korea : Analysis of Screw Accuracy, Potential Risk Factor of Screw Malposition and Learning Curve.

Recently, robotic-assisted spine surgery (RASS) has been considered a minimally invasive and relatively accurate method. In total, 495 robotic-assisted pedicle screw fixation (RAPSF) procedures were attempted on 100 patients during a 14-month period. The current study aimed to analyze the accuracy, potential risk factors, and learning curve of RAPSF. This retrospective study evaluated the position of RAPSF using the Gertzbein and Robbins scale (GRS). The accuracy was analyzed using the ratio of the clinically acceptable group (GRS grades A and B), the dissatisfying group (GRS grades C, D, and E), and the Surgical Evaluation Assistant program. The RAPSF was divided into the no-breached group (GRS grade A) and breached group (GRS grades B, C, D, and E), and the potential risk factors of RAPSF were evaluated. The learning curve was analyzed by changes in robot-used time per screw and the occurrence tendency of breached and failed screws according to case accumulation. The clinically acceptable group in RAPSF was 98.12%. In the analysis using the Surgical Evaluation Assistant program, the tip offset was 2.37±1.89 mm, the tail offset was 3.09±1.90 mm, and the angular offset was 3.72°±2.72°. In the analysis of potential risk factors, the difference in screw fixation level (p=0.009) and segmental distance between the tracker and the instrumented level (p=0.001) between the no-breached and breached group were statistically significant, but not for the other factors. The mean difference between the no-breach and breach groups was statistically significant in terms of pedicle width (p<0.001) and tail offset (p=0.042). In the learning curve analysis, the occurrence of breached and failed screws and the robot-used time per screw screws showed a significant decreasing trend. In the current study, RAPSF was highly accurate and the specific potential risk factors were not identified. However, pedicle width was presumed to be related to breached screw. Meanwhile, the robot-used time per screw and the incidence of breached and failed screws decreased with the learning curve.

992 Pioneering Robot-Assisted Spine Surgery in the United Kingdom

Abstract Aim The placement of a large interbody implant allows for a larger fusion area. Retroperitoneal approaches, like anterior, antero-lateral, and lateral fusion, facilitate the placement of these implants. At the same time, robot-navigation facilitate complex, minimally invasive spine surgery for posterior screw fixation. This is a single-surgeon, single-centre report on the experience of the first procedures ever performed for navigated robot-assisted spine surgery in the United Kingdom. Method Between October 2019 and May 2021, we identified 34 consecutive patients who underwent robot-assisted spine surgery. The demographic, intra-operative, and peri-operative data were reviewed. Results Of the 34 patients, 65 levels were treated in total (204 screws). 21 patients (60%) underwent single-level fixation, 14 of them (67%) were treated at the L5/S1 level, 3 at L3/L4, 3 at L4/L5 and 1 at L2/L3 level, 13 patients (40%) underwent multi-level fixation, with 4 of them treated for adult scoliosis. Eight patients underwent a supine ALALIF approach and one a lateral decubitus AL-ALIF, 7 had a pure ALIF approach, 8 patients underwent combined XLIF and AL-ALIF approach in a lateral decubitus, 6 underwent pure XLIF approach, 1 patient had previous TLIF surgery, and 3 patients underwent single position lateral surgery (lateral decubitus fusion and posterior screw fixation). Conclusions Minimally invasive spine surgery using robot-assisted navigation yields an improved level of accuracy, decreased radiation exposure, minimal muscle disruption, decreased blood loss, shorter operating theatre time, length of stay, and lower complication rates. Further follow-up of the patients treated will help compare the clinical outcomes with other techniques.