Advancements in robotics and navigation have the potential to transform spine surgery

The modern era of instrumented spine surgery began with surgical pioneers and innovators such as Paul Harrington, Raymond Roy-Camille, Yves Cotrel, and Jean Dubousset. With more advanced spinal instrumentation came the need for improved accuracy in placing spinal hardware. This is especially critical for pedicle screw fixation in both the thoracic and lumbar spine. Initially, plain radiographs and fluoroscopic imaging, along with intraoperative anatomic landmarks, were used to help guide pedicle screw placement. However, even in well-trained hands, the accuracy of screw placement was not 100%. As the techniques and indications for pedicle screw fixation evolved over time, so did the need for improved accuracy of screw placement, which catalyzed the development of intraoperative surgical navigation and surgical robotics.

Types of robotic and navigation systems
Robotic and navigation systems for use in spine surgery fall into one of three groups, according to Young-Seok et al:

• In supervisory controlled systems, the machine is programmed with predetermined actions that are eventually carried out with some autonomy from the robot, as well as close supervision from the operating surgeon.
• Telesurgical systems allow the surgeon complete control of the motions of the operating system from a remote command station (e.g., da Vinci Robotic Surgical Systems from Intuitive Surgical).
• Shared control systems, currently the most popular, allow both the robot and the surgeon to simultaneously control intraoperative maneuvers and surgical instruments during the procedure.

Computer-assisted navigation has also gained popularity. Two of the most widely used navigation platforms are the StealthStation with O-arm from Medtronic and Ziehm Vision with NaviPort from Ziehm Imaging.

Surgical navigation offers several advantages over traditional freehand pedicle screw fixation. Multiple studies have shown that the use of surgical navigation platforms increases the accuracy of pedicle screw placement. Additionally, the accumulated dose of radiation for a fluoroscopically assisted instrumented spine case is nearly 10 times higher than that of a navigated case. This factor is especially important when considering a spine surgeon’s lifetime exposure to radiation. Similarly, the patient in a surgically navigated case is also delivered a lower dose of radiation.

For example, the first widely used robotic surgical platform that received FDA clearance was Spine Assist from Mazor Robotics. This surgical platform has undergone several evolutions, including a robotic arm that attaches to the operating table and the addition of a 3D camera to help improve the accuracy of intraoperative instrument placement and eventually improve accuracy of pedicle screw fixation. One of the initial problems with robotic platforms was skiving of the surgical cannulas, which has been subsequently resolved with advances in technology.

Potential drawbacks
One of the major disadvantages associated with robotics and navigation is the capital cost associated with the technology. For example, the Mazor X Robotic Guidance System currently lists for approximately $1.5 million, which does not include surgical disposables, routine service, as well as scheduled maintenance. Navigation equipment costs can be in excess of $1 million. Although reimbursement for the use of navigation is not always possible, it is noteworthy that shorter intraoperative times and fewer complications associated with misplaced pedicle screws can eventually lead to a cost savings. As a result, this can lead to overall reduced costs for patient care.

The learning curve associated with robotic surgical platforms is another potential drawback. As with any new technology, surgeons utilizing robotic platforms need time to become familiar with the workflow and use of the equipment. Hu and Lieberman concluded that the learning curve for a surgeon using the spine assist robot is approximately 150 cases. Once a surgeon becomes adept at using the robot, they can increase the rate of successfully placed pedicle screws, decrease radiation exposure, and eventually have a lower rate of intraoperative conversion to manual screw placement.

On the other hand, the learning curve for intraoperative navigation is not extraordinarily difficult. Most of the time is spent obtaining intraoperative imaging. It can be helpful to have an experienced radiology technician available to assist with image acquisition. Typically, the intraoperative time for image acquisition is approximately 10 to 15 minutes. Naturally, there are some time requirements needed to familiarize oneself with the workflow of navigation platforms.

There is no doubt that emerging technology is changing the practice of spine surgery. Robotics and navigation are becoming increasingly popular as surgeons look for ways to improve the accuracy of pedicle screw placement, reduce complications, potentially increase reliability and reproducibility, and, by extension, improve surgical outcomes. Adoption of robotics and navigation must be weighed against the high costs and steep learning curve associated with the acquisition and use of this technology.

Cassim M. Igram, MD, FAAOS, is a clinical professor in the departments of orthopaedic surgery and neurosurgery at the University of Iowa. He is a member of the AAOS Now Editorial Board, treasurer of the Political Action Committee of the American Association of Orthopaedic Surgeons, and a member of the AAOS Committee on Professionalism.

References

1. Lee YS, Cho DC, Kim KT. Navigation-guided/robot-assisted spinal surgery: a review article. Neurospine. 2024;21(1):8-17. doi: 10.14245/ns.2347184.592
2. Elswick CM, Strong MJ, Joseph JR, Saadeh Y, Oppenlander M, Park P. Robotic-assisted spinal surgery: current generation instrumentation and new applications. Neurosurg Clin N Am. 2020;31(1):103-110. doi: 10.1016/j.nec.2019.08.012
3. Perfetti DC, Kisinde S, Rogers-LaVanne MP, Satin AM, Lieberman IH. Robotic spine surgery: past, present, and future. Spine (Phila Pa 1976). 2022;47(13):909-921. doi: 10.1097/BRS.0000000000004357
4. Hu X, Ohnmeiss DD, Lieberman IH. Robotic-assisted pedicle screw placement: lessons learned from the first 102 patients. Eur Spine J. 2013;22(3):661-666. doi: 10.1007/s00586-012-2499-1