Advancing robot-guided techniques in lumbar spine surgery: a systematic review and meta-analysis

ABSTRACT

Background

Lumbar spine surgery is a crucial intervention for addressing spinal injuries or conditions affecting the spine, often involving lumbar fusion through pedicle screw (PS) insertion. The precision of PS placement is pivotal in orthopedic surgery. This systematic review compares the accuracy of robot-guided (RG) surgery with free-hand fluoroscopy-guided (FFG), free-hand without fluoroscopy-guided (FHG), and computed tomography image-guided (CTG) techniques for PS insertion.

Methods

A systematic search of various databases from 1 January 2013 to 30 December 2023 was conducted following PRISMA guidelines. Primary outcomes, including PS insertion accuracy and breach rate, were analyzed using a random-effects model. Risk of bias was assessed using the Newcastle-Ottawa Scale.

Results

The overall accuracy of PS insertion using RG, based on 37 studies involving 3,837 patients and 22,117 PS, is 97.9%, with a breach rate of 0.021. RG demonstrated superior accuracy compared to FHG and CTG, with breach rates of 3.4 and 0.015 respectively for RG versus FHG, and 3.8 and 0.026 for RG versus CTG. Additionally, RG was associated with reduced mean estimated blood loss compared to CTG, indicating improved safety.

Conclusions

The RG is associated with enhanced accuracy of PS insertion and reduced breach rates over other methods. However, additional randomized controlled trials comparing these modalities are needed for further validation.

Prospero Registration

CRD42023483997

KEYWORDS:

• Accuracy assessment
• computed tomography-guided
• fluoroscopy-guided surgery
• free-hand surgery
• lumbar spine surgery
• meta-analysis
• pedicle screw insertion
• robot-guided surgery

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewers disclosure

One reviewer is a Consultant for Globus and eCential Robotics. All other peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.

Author contributions

Temitope Emmanuel Komolafe, Liang Zhou, and Wenlong Zhao primarily contributed to data acquisition and analysis, manuscript drafting and reviewing, project administration, and supervision. Jiachen Guo and Zongdao Li provided expertise in the interpretation of data, manuscript drafting and reviewing. Zhiping Fan and Blessing Funmi Komolafe contributed to drafting and reviewing the manuscript. Wei Wang provided expert opinion on surgical robots and contributed to drafting the manuscript. Oluwarotimi Williams Samuel contributed to drafting of manuscript, provided expert opinion, and critically revised the manuscript. All authors read and approved the final manuscript.

Acknowledgments

The authors gratefully acknowledge the support of the National Key Research and Development Program of the National Natural Science Foundation of China (Grant number 92048205), the National Natural Science Foundation of China (Grant number 82072228), and the National Natural Science Foundation of China (Grant number 62376152). The authors acknowledge the sacrifices made by anonymous reviewers for their meritorious service.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/17434440.2024.2378080

Additional information

Funding

This paper was not funded.