Next-Generation Robotic Spine Surgery: First Report on Feasibility, Safety, and Learning Curve

Khan, Asham; Meyers, J.; Siasios, Ioannis; Pollina, John

doi:10.1093/ons/opy280

Cited by 124 publications

(121 citation statements)

References 29 publications

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“…The learning curve, safety, and feasibility was investigated by Khan et al 18 The authors reported no screw misplacement and no complications within the first 20 patients using the robotic spine surgery system. The mean time for screw insertion was 3.6 minutes, and the authors 18 concluded that only a minimal learning curve exists.…”

Section: Discussionmentioning

confidence: 99%

“…Urakov et al 17 described improved efficiency with increased case load, but they also noted that the learning curve was largely dependent on the experience and the dedication of the operator. Khan et al, 18 however, described a minimal learning curve involved with robotic spine surgery and stated the efficacy of the technique. Most of the literature describing the learning curve using robotic surgery focused on pedicle screw insertion time but failed to report on the overall operative time, including cases in which the robotic system malfunctioned.…”

Section: Introductionmentioning

confidence: 99%

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Surgeons' Learning Curve of Renaissance Robotic Surgical System

et al. 2020

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Introduction: A few articles on robot-assisted pedicle screw placement described the learning curve but failed to report on the overall operative time, including cases in which the robotic system malfunctioned. The purpose of this study was to identify a single surgeon's learning curve including estimated blood loss, surgery time, anesthesia time, robot time, and complications. Methods: A retrospective study was performed between January 2016 and August 2018 for patients who underwent posterior spinal fusion using the Mazor robot. Based on the charts, the robot time, time of anesthesia, and surgery time were recorded, as were the complications, misplacement of screws, and blood loss. Results: Of 62 robot-assisted surgeries scheduled, only 46 were performed (74.2%) upon patients with a mean age of 63.3 6 13.0 years. The mean follow-up time was 13.2 6 8.0 months and most commonly a fusion from L4 to S1 was performed (20/46, 43.5%). A high improvement in estimated intraoperative blood loss was observed of 755.7 6 344.7 mL (slope ¼ À9.89). A decrease in time in anesthesia, surgery, and robotic usage was identified with a slope factor of

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Surgeons' Learning Curve of Renaissance Robotic Surgical System

et al. 2020

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“…Similarly, a recent study examining the feasibility of another robotic-navigation guided system, Mazor X (Mazor Robotics Ltd) reported an accuracy rate of 98.7% examining 75 screws. 13 In addition to improving accuracy, while not directly examined in this study, importantly the robotic-navigation system has the added advantage of likely reducing radiation exposure intraoperatively to the both the patient and the surgeon. The only fluoroscopy required intraoperatively are the few images required for registration, including a good AP and lateral at each instrumented level.…”

Section: Discussionmentioning

confidence: 99%

Initial Single-Institution Experience With a Novel Robotic-Navigation System for Thoracolumbar Pedicle Screw and Pelvic Screw Placement With 643 Screws

et al. 2019

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Background: Robotic-guided navigation systems for pedicle screw placement has gained recent interest to ensure accuracy and safety and diminish radiation exposure. There have been no published studies using a new combined robotics and navigation system (Globus ExcelsiusGPS system). The purpose of this study was to demonstrate safety with this system. Methods: This is a case series of consecutive patients at a single institution from February 1, 2018, to August 31, 2018. All patients who had planned placement of thoracic and lumbar pedicle screws using the combined roboticsnavigation system were included. Chart review was performed for operative details. A subgroup analysis was performed on patients with postoperative computed tomography (CT) scans to assess screw placement accuracy using the Gertzbein and Robbins system. Acceptable pedicle screw position was defined as grade A or B. Results: One hundred six patients were included, with 636 pedicle screws, 6 iliac screws, and 1 S2AI screw. Five cases were aborted for technical issues. In the remaining 101 patients, 88 patients had screws placed using preoperative CT planning and 13 patients using intraoperative fluoroscopy planning. All screws except for 5 pedicle screws in 2 patients were placed successfully using the robot (99%). These 5 pedicle screws were placed by converting to a fluoroguided technique without robotic assistance. Eighty-six patients had screws placed using a percutaneous technique, and 15 patients had screws placed using an open technique. Ninety-eight patients underwent interbody placement: 28 anterior lumbar interbody fusions (ALIFs), 12 lateral lumbar interbody fusions (LLIFs), and 58 transforaminal lumbar interbody fusions (TLIFs). All ALIFs and LLIFs were performed prior to placement of the screws. Four LIF patients had screws placed in the lateral position. No patients had screw-related complications intraoperatively or postoperatively, and no patients returned to the operating room for screw revision. Thirteen patients underwent postoperative CT for various reasons. Of the 66 pedicle screws that were examined with postoperative CT, all screws (100%) had acceptable position. Conclusion: This study demonstrates that the combined robotics and navigation system is a novel technology that can be utilized to place pedicle screws and pelvic screws safely and has the potential to reduce screw-related complications. Level of Evidence: 4 (case series).

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“…In addition, authors reported a favorable learning curve compared to older versions of the system. 32…”

Section: Mazor Xmentioning

confidence: 99%

Robotic Spine Surgery and Augmented Reality Systems: A State of the Art

et al. 2020

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Instrumented spine procedures have been performed for decades to treat a wide variety of spinal disorders. New technologies have been employed to obtain a high degree of precision, to minimize risks of damage to neurovascular structures and to diminish harmful exposure of patients and the operative team to ionizing radiations. Robotic spine surgery comprehends 3 major categories: telesurgical robotic systems, robotic-assisted navigation (RAN) and virtual augmented reality (AR) systems, including AR and virtual reality. Telesurgical systems encompass devices that can be operated from a remote command station, allowing to perform surgery via instruments being manipulated by the robot. On the other hand, RAN technologies are characterized by the robotic guidance of surgeon-operated instruments based on real-time imaging. Virtual AR systems are able to show images directly on special visors and screens allowing the surgeon to visualize information about the patient and the procedure (i.e., anatomical landmarks, screw direction and inclination, distance from neurological and vascular structures etc.). The aim of this review is to focus on the current state of the art of robotics and AR in spine surgery and perspectives of these emerging technologies that hold promises for future applications.

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Next-Generation Robotic Spine Surgery: First Report on Feasibility, Safety, and Learning Curve

Cited by 124 publications

References 29 publications

Surgeons' Learning Curve of Renaissance Robotic Surgical System

Surgeons' Learning Curve of Renaissance Robotic Surgical System

Initial Single-Institution Experience With a Novel Robotic-Navigation System for Thoracolumbar Pedicle Screw and Pelvic Screw Placement With 643 Screws

Robotic Spine Surgery and Augmented Reality Systems: A State of the Art

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