Robotic-Assisted Spine Surgery: Hype or Game-Changer?

The purpose of this study was to clarify the learning curve for robotic-assisted spine surgery. We analyzed the workflow in robotic-assisted spine surgery and investigated how much experience is required to become proficient in robotic-assisted spine surgery. The data were obtained from consecutive 125 patients who underwent robotic-assisted screw placement soon after introducing a spine robotic system at a single center from April 2021 to January 2023. The 125 cases were divided into phases 1-5 of sequential groups of 25 cases each and compared for screw insertion time, robot setting time, registration time, and fluoroscopy time. There were no significant differences in age, body mass index, intraoperative blood loss, number of fused segments, operation time, or operation time per segment between the 5 phases. There were significant differences in screw insertion time, robot setting time, registration time, and fluoroscopy time between the 5 phases. The screw insertion time, robot setting time, registration time, and fluoroscopy time in phase 1 were significantly longer than those in phases 2, 3, 4, and 5. In an analysis of 125 cases after the introduction of the spine robotic system, the screw insertion time, robot setting time, registration time, and fluoroscopy time were significantly longer in the 25 cases in the period initially after introduction. The times were not significantly different in the subsequent 100 cases. Surgeons can be proficient in robotic-assisted spine surgery after their experience with 25 cases.

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.

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.

The use of thoracic pedicle screws for the treatment of adolescent idiopathic scoliosis (AIS) has gained widespread popularity. However, the placement of pedicle screws in the deformed spine poses unique challenges, and surgeons experience a learning curve. The in vivo accuracy as determined by computed tomography (CT) of placement of thoracic pedicle screws in the deformed spine as a function of surgeon experience is unknown. We undertook a retrospective review to determine the effect of surgeon experience on the accuracy of thoracic pedicle screw placement in AIS. In 2005, we started to obtain routine postoperative CT scans on patients undergoing a spinal fusion. From a database of these patients, we selected AIS patients, who underwent a posterior spinal fusion. Fifteen consecutive patients for each of the following three groups stratified by attending surgeon experience were selected (N = 45): A) less than 20 cases of all pedicle screw constructs for AIS (surgeons <2 years of practice), B) 20-50 cases (surgeons 2-5 years of practice), and C) greater than 50 cases (surgeons greater than 5 years of practice). Intraoperative evaluation of all screws included probing of the pedicle screw tract, neurophysiologic monitoring, and fluoroscopic confirmation. A total of 856 thoracic pedicle screws were studied. Postoperative CT scans were evaluated by two spine surgeons and a consensus read established as follows: (1) In: intraosseous placement or <or=2-mm breach, (2) Out: >2-mm breach, either medial or lateral. Of the 856 screws, 104 demonstrated a >2-mm breach, for an overall rate of 12.1% (medial = 55, lateral = 49, P = 0.67). When the breach rates were stratified by surgeon experience, there was a trend toward decreased rate of breach for the most experienced surgeons, although this did not attain statistical significance (Group A: 12.7%, Group B: 12.9%, Group C: 10.8%, P = 0.58). However, the most experienced group (C) had a markedly decreased rate of medial breaches (3.5 vs. 7.4% and 8.4% for groups A and B, respectively, P < 0.01). The breach rate for the concave periapical screws was not statistically different from the overall breach rate (13.0% vs. 12.1%, P = 0.93). In conclusion, the overall accuracy of placement of pedicle screws in the deformed spine was 87.9%, with no neurologic, vascular, or visceral complications. Meticulous technique allows spine surgeons with a range of surgical experience to accurately and safely place thoracic pedicle screws in the deformed spine. The most experienced surgeons demonstrated the lowest rate of medial breaches.

Although a growing amount of literature that suggests robots are safe and can achieve comparable outcomes to conventional techniques, much of this literature is limited by small sample sizes and single-surgeon or single center series. Furthermore, it is unclear what the impact of robotic technology has made on operative and clinical outcomes over time. This is the first and largest multicenter study to examine the trends in outcomes and complications after robot-assisted spine surgery over a 5-year period. Adult (≥18 years old) patients who underwent spine surgery with robot-assistance between 2015 and 2019 at four unique spine centers. The robotic systems used included the Mazor Renaissance, Mazor X, and Mazor Stealth Edition. Patients with incomplete data were excluded from this study. The minimum follow-up was 90 days. A total of 722 adult patients were included (117 Renaissance, 477 X, 128 Stealth). Most patient and operative factors (e.g., sex, tobacco status, total instrumented levels, and pelvic fixation,) were similar across the years. Mean ± standard deviation Charlson comorbidity index (CCI) was 1.5±1.5. The most commonly reported diagnoses included high grade spondylolisthesis (40.6%), degenerative disc disease (18.4%), and degenerative scoliosis (17.6%). Mean (standard deviation) number of instrumented levels was 3.8±3.4. From 2015 to 2019, average robot time per screw improved from 7.2 to 5.5 minutes (P=0.004, R2=0.649). Average fluoroscopy time per screw improved from 15.2 to 9.4 seconds (P=0.002). Rates of both intraoperative screw exchange for misplaced screw (2015-2016: 2.7%, 2019: 0.8%, P=0.0115, R2=0.1316) and robot abandonment (2015-2016: 7.1%, 2019: 1.1%, P=0.011, R2=0.215) improved significantly over time. The incidence of other intraoperative complications (e.g., dural tear, loss of motor/sensory function, blood transfusion) remained consistently low, but similar throughout the years. The length of stay (LOS) decreased by nearly 1 day from 2015 to 2019 (P=0.007, R2=0.779). 90-day reoperation rates did not change significantly. At four institutions among seven surgeons, we demonstrate robot screw accuracy, reliability, operative efficiency, and radiation exposure improved significantly from 2015 to 2019. 90-day complication rates remained low and LOS decreased significantly with time. These findings further validate continued usage of robot-assisted spine surgery and the path toward improved value-based care.

Objective: As technology advances and allows for even more efficiency and precision, it is anticipated that robot-assisted spine surgery will become more and more prevalent in the future. In the realm of spine surgery, we discuss our preliminary experiences with the Excelsius GPS® spine surgical robot and its role in improving patient safety. Methods: At our facility, 150 patients had robot-assisted Transforaminal Lumbar Interbody Fusion (TLIF). The demographic information, radiation exposure, cranial facet joint violation, and pedicle screw accuracy were assessed. Pedicle screw accuracy was evaluated using the Gertzbein-Robbins classification, whereas facet joint violation was evaluated using the Yson classification. Results: 150 patients received robotic help for the placement of 696 screws in all. With robotic aid, we discovered the accuracy to be 98.27% and facet joint violation rates of 17% &amp; 0% for grades 1 &amp; 2 respectively. Radiation exposure for patients was significantly higher than that of healthcare personnel, (10.57±3.605 vs 1.35±0.425 mSv P&lt;0.00001). Conclusion: Robotic spine surgery may reduce human error—such as tremors and fatigue—that may occur during traditional open spine procedures. Robotic surgery offers three-dimensional views and navigation technology and may be used to improve accuracy, lower issues, and raise patient safety.

A single-center randomized controlled study. The objective of this study was to introduce a novel robotic system with an independent arm ("Orthbot Intelligent Orthopedic Minimally Invasive System"; Xin Junte Surgical Technologies) that has been developed and tested as a surgical assistant for autoplacement of the Kirschner wire (K-wire) in lumbar fusion, and to evaluate its accuracy by comparing it with the conventional free-hand instrumentation. Robotic technology has performed excellently in spine surgeries and has demonstrated high clinical value and potential. Robot-assisted spinal surgery is now being promoted as a paradigm for technology-led advancement. A total of 24 patients were recruited and assigned randomly to the robotic arm group (RG) or the free-hand group (FG). Deviation distance and deviation angle (DA) of K-wire placement were measured and compared between the RG and the FG. The average deviation distance was 0.88±0.08 mm in the RG and 5.13±1.68 mm in the FG (P<0.001). In both coronal and sagittal radiographs, the average DA of K-wire placement was smaller in the RG (P<0.05), and in both axial and sagittal computed tomography scans, the average DA of pedicle screw placement was also lower in the RG (P<0.05), which indicated higher accuracy of the robotic system. The novel robotic system in this study has shown certain advantages over the conventional free-hand approach in K-wire placement for lumbar fusion, including being more accurate in K-wire placement, fully automatic, and more adaptive to preoperative plans. Although the robotic arm proves to be promising in our results, the small sample size in this clinical study necessitates further multicenter, large sample follow-up studies to verify its advantages.

ABSTRACTBackground:Cervical pedicle screws provide superior biomechanical fixation with pullout strength four times greater than lateral mass screws, but placement is technically demanding with traditional malposition rates of 6.7%–31.6%. Robotic-assisted spine surgery has demonstrated success in thoracolumbar applications, but cervical translation has been hindered by the lack of cervical-specific instrumentation requiring expensive custom instruments.Methods:We developed a hybrid technique combining robotic guidance with standard cervical instrumentation using minimally invasive surgery dilators as an interface. Sixty-five consecutive patients underwent robot-assisted cervical pedicle screw placement with 565 screws across C2–C7 levels using MazorX Stealth robotic system with O-arm navigation. Accuracy was assessed using Gertzbein-Robbins and Neo classification systems with 3–6-month follow-up for complications.Results:The technique achieved 98.76% clinically acceptable accuracy (Gertzbein-Robbins Grade A + B) with 1.24% breach rate. Perfect placement (Grade A) occurred in 95.22% of screws. Vertebral artery protection was excellent with 99.65% showing no foramen breach. Major complications occurred in 1.5% of patients (single vertebral artery injury), with 7.7% experiencing transient C5 weakness that resolved completely. No patients required revision surgery.Conclusions:This hybrid technique addresses instrument compatibility barriers in robotic cervical spine surgery by eliminating dependence on custom instruments while maintaining robotic accuracy. The technique demonstrates superior outcomes compared to traditional approaches and facilitates broader robotic cervical surgery adoption. Multi-center validation studies are needed to establish the generalizability.

Robotic-assisted bariatric surgery improves accuracy and patient safety

35. How many screws are necessary to be considered an experienced surgeon for freehand placement of thoracolumbar pedicle screws? Analysis of the learning curve using the cumulative summation test for learning curve (LC-CUSUM)

Cervicothoracic deformity correction in patients with dystrophic scoliosis due to neurofibromatosis type 1 (NF1) is technically demanding, owing to the distorted anatomy and poor bone quality. Robotic-assisted spine surgery can enhance accuracy in such complex cases. This report presents the case of a 19-year-old male with NF1 who had progressive cervicothoracic scoliosis and severe back pain. Radiographs revealed severe multi-level curvatures: cervical (53.9°), proximal thoracic (110.8°), and main thoracic (54.7°), with imaging suggestive of a plexiform neurofibroma. The patient underwent robotic-assisted posterior spinal fusion from C3 to T12. The use of the spine robot enabled accurate pedicle screw placement through preoperative planning and intraoperative guidance. Postoperative recovery was smooth, with notable pain relief and functional gains at 3 months. Deformity correction was significant, with postoperative curves reduced to 20° (cervical), 41.1° (proximal thoracic), and 21.7° (main thoracic), and no complications occurred. This case illustrates the value of robotic assistance in complex spinal deformity surgery, particularly in NF1 patients, by improving precision, reducing risks, and enhancing outcomes.

Does intraoperative CT navigation increase the accuracy of pedicle screw placement in pediatric spinal deformity surgery? A systematic review and meta-analysis.

Surgical robots are gaining increasing popularity because of their capability to improve the precision of pedicle screw placement. However, current surgical robots rely on unimodal computed tomography (CT) images as baseline images, limiting their visualization to vertebral bone structures and excluding soft tissue structures such as intervertebral discs and nerves. This inherent limitation significantly restricts the applicability of surgical robots. To address this issue and further enhance the safety and accuracy of robot-assisted pedicle screw placement, this study will develop a software system for surgical robots based on multimodal image fusion. Such a system can extend the application range of surgical robots, such as surgical channel establishment, nerve decompression, and other related operations. Initially, imaging data of the patients included in the study are collected. Professional workstations are employed to establish, train, validate, and optimize algorithms for vertebral bone segmentation in CT and magnetic resonance (MR) images, intervertebral disc segmentation in MR images, nerve segmentation in MR images, and registration fusion of CT and MR images. Subsequently, a spine application model containing independent modules for vertebrae, intervertebral discs, and nerves is constructed, and a software system for surgical robots based on multimodal image fusion is designed. Finally, the software system is clinically validated. We will develop a software system based on multimodal image fusion for surgical robots, which can be applied to surgical access establishment, nerve decompression, and other operations not only for robot-assisted nail placement. The development of this software system is important. First, it can improve the accuracy of pedicle screw placement, percutaneous vertebroplasty, percutaneous kyphoplasty, and other surgeries. Second, it can reduce the number of fluoroscopies, shorten the operation time, and reduce surgical complications. In addition, it would be helpful to expand the application range of surgical robots by providing key imaging data for surgical robots to realize surgical channel establishment, nerve decompression, and other operations.

Spinal disorders represent a substantial global health burden, affecting nearly 5% of the world’s population and contributing significantly to disability and healthcare utilization. Over the past century, spinal neurosurgery has evolved markedly due to advances in neuroanesthesia, antiseptic techniques, and surgical instrumentation. More recently, the integration of minimally invasive techniques, robotic assistance, augmented and virtual reality (AR/VR), machine learning, and three-dimensional (3D) printing has transformed surgical planning, execution, and outcomes. Minimally invasive spinal procedures, including tubular microdiscectomy, endoscopic techniques, and fusion approaches, have reduced tissue trauma, postoperative pain, and recovery time. Robotic-assisted spine surgery has enhanced accuracy in instrumentation placement, reduced radiation exposure, and improved workflow efficiency, albeit with challenges related to cost and operative time. AR and VR technologies have improved intraoperative navigation, surgical precision, and training of residents, while 3D printing has enabled patient-specific preoperative planning, surgical guides, and customized implants. Despite these advancements, widespread adoption remains limited by economic constraints, steep learning curves, and infrastructure requirements. Continued technological refinement, cost reduction, and surgeon training are essential to expand accessibility and maximize the clinical impact of these innovations in spinal neurosurgery.

In recent years, surgical approaches for treating colorectal cancer have shifted from open surgery to laparoscopic surgery and, more recently, to robot-assisted surgery (RAS), yet their relative impact on postoperative inflammation and pain remains unclear. Therefore, this study aimed to compare the postoperative C-reactive protein/albumin ratio (CRA) and Numerical Rating Scale (NRS) scores between RAS and single-incision laparoscopic surgery (SILS) for right-sided colon cancer to assess which surgical modality might be more minimally invasive. We retrospectively analyzed 180 patients who underwent surgical resection for right-sided colon cancer at Saitama Medical University International Medical Center (Hidaka, Saitama, Japan) between March 2021 and October 2024. Among these patients, 80 underwent RAS (RAS group) and 100 underwent SILS (SILS group). Propensity score matching (PSM) was applied, and 67 patients from each group were selected for comparison. Primary outcomes were the CRA and pain intensity on the NRS on postoperative days (POD) 1 and 3. Secondary outcomes included operative time, blood loss, and major complications (Clavien-Dindo > II). After PSM, there were no significant differences in the patient background variables, including the preoperative CRA, between the groups. The operative time was significantly shorter in the SILS group than in the RAS group (SILS vs. RAS: 157 vs. 193min, p < 0.001). Although the CRA did not differ on POD 1 and 3, the SILS group had a significantly higher CRA than the RAS group. The RAS group had a significantly lower NRS score on POD 1. For right-sided colon cancer surgery, SILS involves fewer and smaller incisions and a shorter operative time. However, RAS was associated with a lower early postoperative inflammatory response and pain in this PSM comparison. The refined precision and reduced tissue manipulation offered by robotic systems may explain these differences.