Augmented reality-guided pedicle screw fixation: an experimental study

Sang-Min Park; Dongjoon Kim; Jiwon Park; Ho-Joong Kim; Jin S. Yeom

doi:10.31616/asj.2025.0163

Asian Spine J > Online first

Park, Kim, Park, Kim, and Yeom: Augmented reality-guided pedicle screw fixation: an experimental study

Basic Study

Asian Spine Journal 2025;asj.2025.0163.

Online first: August 25, 2025

DOI: https://doi.org/10.31616/asj.2025.0163

Augmented reality-guided pedicle screw fixation: an experimental study

Sang-Min Park¹

, Dongjoon Kim²

, Jiwon Park³

, Ho-Joong Kim¹

, Jin S. Yeom¹

¹Spine Center, Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea

²School of Information Convergence, College of Software and Convergence, Kwangwoon University, Seoul, Korea

³Department of Orthopaedics, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea

Corresponding author: Sang-Min Park, Spine Center, Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82 Gumi-ro 173beon-gil, Bundang-gu, Seongnam 13620, Korea,
Tel: +82-31-787-7208, Fax: +82-31-787-4056, E-mail: psmini@naver.com

Received March 18, 2025 Revised April 9, 2025 Accepted May 12, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

See commentary "Letter to editor: Augmented reality-guided pedicle screw fixation" in Volume 19 on page 873.

Abstract

Study Design

Cadaveric experimental study.

Purpose

To evaluate the feasibility and accuracy of pedicle screw placement using a custom-developed augmented reality-assisted pedicle screw fixation (ARPSF) system in a porcine spine model.

Overview of Literature

Conventional pedicle screw placement techniques face limitations including potential inaccuracy, radiation exposure, and workflow disruption. Augmented reality technology can overlay virtual surgical planning directly onto the operative field while maintaining the surgeon’s focus on the patient.

Methods

Five porcine cadaveric lumbar spines were used in this study. A custom-developed head-mounted display system with optical tracking projected three-dimensional reconstructed spine models and planned screw trajectories into the surgeon’s field of view. A single experienced spine surgeon placed 50 pedicle screws (4.5 mm diameter). Registration was performed using a point-pair matching technique with fifteen anatomical landmarks. Accuracy was assessed via postoperative computed tomography scan, measuring entry point deviation, trajectory deviation, and angular difference, and evaluated using the Gertzbein-Robbins classification.

Results

Of the 50 pedicle screws placed, 47 (94%) achieved grade A accuracy with complete containment within the pedicle. The remaining three screws (6%) were classified as grade B, with minor breaches less than 2 mm. No unsafe placements (grades C–E) occurred. The mean entry point deviation was 0.55 mm (standard deviation [SD]=0.33 mm), and the mean deviation at the screw tip was 0.71 mm (SD=0.32 mm). The mean axial angular deviation was 2.04° (SD=0.58°). The average placement time was 2.2 minutes per screw.

Conclusions

The custom-developed ARPSF system demonstrated high accuracy for pedicle screw placement in a porcine model, achieving submillimeter precision and minimal angular deviation. This experimental study shows the potential of augmented reality technology to enhance spine instrumentation precision.

Keywords: Augmented reality; Pedicle screw fixation; Porcine cadaver spine; Head-mounted display

Introduction

Pedicle screw fixation has become the gold standard for spinal stabilization across a wide range of pathologies, including degenerative conditions, trauma, deformity, and tumors [1]. The technique provides superior biomechanical stability compared to other fixation methods due to its three-column control of spinal elements [2]. However, accurate screw placement remains challenging, with potential serious complications such as neurological injury, vascular damage, and biomechanical instability resulting from malpositioned screws [3].

The traditional freehand technique relies heavily on the surgeon’s knowledge of anatomical landmarks and tactile feedback, with accuracy rates varying widely from 69% to 94% depending on the spinal region and the surgeon’s experience [4,5]. Various navigation technologies have been developed to improve placement accuracy. Fluoroscopy-guided techniques reduce screw malposition risk compared to the freehand approach but involve significant radiation exposure for both patients and surgical teams and still report breach rates of 5%–15% [6]. Computer-assisted navigation systems, using pre- or intraoperative imaging, have further improved accuracy rates to approximately 90%–95% [7]. Robotic-assisted pedicle screw placement has recently emerged, with studies reporting accuracy rates of 90%–98% [8,9]. However, current navigation systems and robotic platforms have limitations, including line-of-sight issues, workflow disruptions, and the need for surgeons to divide their attention between the surgical field and external navigation monitors [10].

Augmented reality (AR) advances surgical navigation by overlaying digital information directly onto the surgeon’s real-world view [11–13]. This allows visualization of critical anatomical structures and planned trajectories while maintaining focus on the surgical field, potentially overcoming the limitations of conventional navigation systems [14,15]. AR applications in spine surgery have evolved rapidly from prototypes to Food and Drug Administration-approved devices [16]. Head-mounted displays (HMDs) integrated with surgical navigation enable intuitive visualization of complex three-dimensional (3D) relationships while maintaining hand-eye coordination [17,18]. Several research groups have developed AR systems specifically for spine surgery, with initial studies showing promising results in both cadaveric and clinical settings [19–21].

We hypothesized that an AR-based navigation system would provide high accuracy for pedicle screw placement while maintaining efficient workflow. The purpose of this experimental study was to evaluate the feasibility and accuracy of pedicle screw placement using our custom-developed AR-assisted pedicle screw fixation (ARPSF) system in a porcine spine model. The ARPSF system integrates a custom HMD with real-time instrument tracking and multiplanar visualization capabilities to guide pedicle screw insertion.

Materials and Methods

Study design and equipment

This cadaveric experimental study evaluated the feasibility and accuracy of pedicle screw placement using an ARPSF system with real-time instrument tracking. Five porcine cadaveric lumbar spines were used. Porcine lumbar vertebrae were selected based on their anatomical similarities to human vertebrae despite differences in pedicle morphology and orientation. The cadavers measured approximately 80 to 100 cm in length (from ears to tail) and weighed 50 to 60 kg. The thoracolumbar spine was excised, with muscles and ligamentous tissue removed while preserving bones, discs, and joints. The specimens were secured on a standard surgical table using pins.

The AR system comprised a custom-developed HMD, an in-house optical tracking system using OptiTrack cameras (NaturalPoint Inc., Corvallis, OR, USA), and a high-performance workstation for image processing and navigation. A standard spine instrument set was used, including pedicle awls, probes, tappers, and 4.5 mm diameter polyaxial pedicle screws.

Registration and navigation protocol

Preoperative computed tomography (CT) scans with 1 mm slice thickness were obtained for all specimens. The Digital Imaging and Communications in Medicine (DICOM) data were transferred to the navigation workstation, and 3D models were generated using previously developed screw simulation software for trajectory planning [22]. Registration involved a point-pair matching technique, identifying nine anatomical landmarks on exposed posterior elements (spinous and transverse processes) on both the virtual model and the physical specimen using a tracked pointer. A transformation matrix was computed to align the coordinate systems with a target registration error of less than 1.5 mm.

A dynamic reference frame consisting of five reflective optical markers was securely attached to a central vertebra’s spinous process using a custom-designed clamp, serving as the primary spatial reference. All surgical instruments (awl, probe, tapper, screwdriver) were calibrated using the optical tracking system to determine their precise tip and axis locations relative to their marker arrays. The HMD was calibrated for the surgeon using a standardized interpupillary distance adjustment protocol with a 15-minute training session for system familiarization (Fig. 1).

The AR system projected the 3D reconstructed spine model and planned screw trajectories directly onto the surgeon’s field of view. The display showed the 3D virtual model and planned trajectories overlaid directly on the cadaver with real-time tracking of instruments and screws. The system also displayed the real-time distance and angle between the actual and planned trajectories, along with multiplanar reconstruction (MPR) CT images (sagittal and axial) that were updated in real-time during navigation. Four visualization modes were available: 3D overlay, trajectory, instrument tracking, and combined modes. The surgeon could switch between modes using hand gestures, with the system updating at 24 frames per second.

Pedicle screw placement and accuracy assessment

All procedures were performed by a single experienced spine surgeon (S.M.P., with more than 10 years of experience). A total of 50 pedicle screws (10 per cadaver) were placed in the lumbar spine using a standardized technique. The process involved identifying the entry point, creating an initial hole with an awl, advancing a pedicle probe through the pedicle into the vertebral body following the virtual trajectory, verifying cortical integrity through tract palpation, and inserting 4.5 mm diameter pedicle screws with a tracked screwdriver. Throughout the procedure, real-time feedback was provided through the HMD, enabling the surgeon to correct the trajectory as needed. For each pedicle screw placement, the total procedure time (from entry point identification to final screw placement), the number of trajectory adjustments, and any technical issues encountered with the AR system were recorded (Fig. 2).

After screw placement, postoperative CT scans were obtained for each specimen using identical parameters to the preoperative scans. Technical accuracy was assessed by measuring entry point deviation (linear distance between planned and actual entry points), tip point deviation (linear distance between planned and actual screw tip points), and trajectory deviation (angular difference between planned and actual trajectories in axial planes). A blinded evaluator used specialized software (Infinitt PACS; Infinitt Co., Seoul, Korea) to perform these measurements (Fig. 3).

Clinical accuracy was assessed using the Gertzbein-Robbins classification system, with grade A indicating screws completely within the pedicle, grade B indicating breach <2 mm, grade C indicating breach ≥2 mm to <4 mm, grade D indicating breach ≥4 mm to <6 mm, and grade E indicating breach ≥6 mm [23]. All postoperative images were evaluated by an independent spine surgeon who did not participate in screw placement. Screws classified as grade A were considered accurately placed.

Statistical analysis was performed using Stata/MP 17.1 (StataCorp LLC, College Station, TX, USA). Descriptive statistics, including means (standard deviations [SD]), were calculated for entry point deviation, trajectory deviation, and trajectory angle difference. The accuracy rate was calculated as the percentage of screws classified as grade A.

Results

In this experimental study using porcine cadaveric spines, 50 pedicle screws were placed with the ARPSF system. Registration was successful in all specimens, achieving a mean target registration error of 0.92 mm (range, 0.67–1.21 mm), calculated as the root mean square distance between corresponding points in the virtual model and the physical specimen post-registration. Postoperative CT scans showed high accuracy rates for successful screw placement.

Clinical accuracy

According to the Gertzbein-Robbins classification, 94% of screws (47 out of 50) were classified as grade A, indicating that these screws were completely contained within the pedicle without any cortical breach. The remaining 6% (three screws) were grade B, with minor cortical breaches under 2 mm. Importantly, none of the screws were classified as grade C, D, or E, demonstrating no unsafe pedicle screw placement.

Technical accuracy

The technical accuracy of the ARPSF system was evaluated by measuring deviations from planned trajectories. The mean entry point deviation was 0.55 mm (SD=0.33 mm), demonstrating high precision at the critical initial entry phase (Fig. 4A). At the screw tip, the mean deviation between the navigated pedicle device and the planned path was 0.71 mm (SD=0.32 mm), indicating accuracy was maintained throughout the trajectory of screw insertion (Fig. 4B). The mean axial angular deviation between the placed pedicle screws and the pre-planned paths was 2.04° (SD=0.58°). This minimal angular deviation further demonstrated the system’s ability to accurately guide screw placement along the intended trajectory (Fig. 4C).

Navigation time

Pedicle screw placement averaged 2.2 minutes per screw (SD=1.1 minutes), from identifying the entry point to final screw insertion, demonstrating an efficient workflow with the AR guidance system.

Discussion

In this study, ARPSF in a porcine spine model demonstrated high accuracy, with 94% of screws placed completely within the pedicle (Gertzbein grade A). The technical precision was evidenced by small deviations from planned trajectories, with a mean entry point deviation of 0.55 mm, a mean tip deviation of 0.71 mm, and a mean axial angular deviation of 2.04°. These results suggest that AR guidance can enhance the precision of pedicle screw placement while maintaining efficiency, with an average placement time of 2.2 minutes per screw.

AR navigation systems have shown promise in spine surgery, offering improved accuracy over conventional navigation methods. A cadaveric study by Elmi-Terander et al. [24] evaluated the feasibility and accuracy of AR surgical navigation with integrated 3D intraoperative imaging, reporting an accuracy of 85% for thoracic pedicle screw placement, significantly better than freehand technique. In a subsequent study using the same technology for minimally invasive pedicle screw placement, they achieved an accuracy of 89% with a mean navigation time of 90 seconds per screw [19]. More recent clinical applications of this technology have achieved even higher accuracy rates, with Liu et al. [20] reporting 98% accuracy in a study of 205 thoracic, lumbar, and sacral pedicle screws placed using an AR HMD.

Various AR systems have shown promising results in both cadaveric and clinical settings. A cadaveric study by Felix et al. [25] reported 96% accuracy for thoracolumbar pedicle screws placed under AR guidance. Similarly, Dennler et al. [26] found that AR navigation improved the precision of drilling pilot holes for pedicle screws and reduced the impact of surgeon experience in a sawbone model. Farshad et al. [27] demonstrated that AR guidance can enable novice users to achieve placement accuracy comparable to that of experienced surgeons. The matched-control clinical study by Elmi-Terander et al. [28] comparing AR-guided pedicle screw placement with the freehand technique found significantly higher accuracy with AR navigation (94% vs. 90%, p<0.05).

Our results compare favorably with previous studies, achieving 94% perfect placement (grade A) and 100% safe placement (grades A and B) with submillimeter deviations from planned trajectories. Our technical accuracy metrics of entry point deviation (0.55 mm) and angular deviation (2.04°) are also comparable to or superior to those reported in other AR navigation studies. Burström et al. [29] reported angular deviations of 1.7° and 1.6° in the axial and sagittal planes, respectively, while Molina et al. [30] found a mean screw tip linear deviation of 1.98 mm and a mean angular error of 1.29°.

The AR system developed for this study offers several advantages, including real-time tracking capabilities that allow surgeons to maintain visual focus on the surgical field. This reduces the need for attention shifts to external monitors, a limitation of conventional navigation systems that can increase cognitive load and lead to performance errors, as noted by Léger et al. [10].

However, our AR system also presented certain limitations. Despite the ability to overlay 3D models and screw trajectories directly on the actual spine, the relatively small field of view of the AR glasses limits the resolution of the 3D models. Additionally, while the trajectory overlay is theoretically advantageous, precisely following this trajectory during actual screw insertion proved challenging. Surgeons often referred to the MPR CT images simultaneously displayed within the AR view to verify accurate screw placement. To enhance visualization of screw insertion depth, shadow effects were implemented, rendering the bone transparent at the insertion site. Nevertheless, surgeons still relied heavily on MPR images for final depth verification, somewhat diminishing the theoretical advantage of the 3D overlay.

This study had several limitations, including the use of porcine cadaveric specimens instead of human cadavers, which may limit the direct clinical applicability of our findings. Although porcine spine anatomy shares similarities with human anatomy, there are notable differences in pedicle morphology and orientation. Second, the study involved only one surgeon, potentially limiting the generalizability. Third, the absence of soft tissue and blood in the cadaveric model eliminates challenges encountered in clinical settings. Fourth, we only evaluated screw placement in the lumbar spine, and results may differ in thoracic regions with smaller pedicles. Fifth, the study lacked a direct comparison with traditional techniques within the same experimental setup. Future studies should include control groups using conventional methods to enable more robust conclusions regarding the relative benefits of AR navigation. Sixth, we did not record the frequency or magnitude of intraoperative trajectory adjustments made during screw placement, which would have provided valuable information about the system’s real-time guidance capabilities. Seventh, the sample size (50 screws across five specimens) was based on comparable experimental studies [21,24] rather than a formal power analysis, potentially limiting the statistical robustness of the findings. Finally, despite the high accuracy of our custom-developed AR system, it remains an experimental platform requiring further refinement before potential clinical application. Despite the promising results, further research, including human cadaveric studies and carefully designed clinical trials, is necessary before this technology can be considered for widespread clinical adoption.

Conclusions

Our study demonstrated the high accuracy and precision of ARPSF in a porcine cadaveric model. Our custom-developed system, encompassing a custom HMD, navigation system, software, and screw simulator, represents a significant advancement in AR-guided spine surgery. Future development should focus on improving the AR display’s field of view, seamlessly integrating 3D overlays with MPR imaging, and refining the user interface to optimize surgical workflow and efficiency.

Key Points

A custom-developed augmented reality system for pedicle screw fixation achieved 94% perfect placement (grade A) in a porcine spine model with no unsafe breaches.
The system demonstrated high technical accuracy with small mean deviations from planned trajectories: 0.55 mm at entry point, 0.71 mm at screw tip, and 2.04° angular deviation).
The augmented reality system enables real-time navigation guidance while maintaining visual focus on the surgical field.
Multiplanar computed tomography reconstructions in the augmented reality view helped verify screw placement accuracy.
This study lays the groundwork for future development of augmented reality applications in spine surgery.

Notes

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Funding

This work was supported by an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korean government (MSIT) (No. 2017-0-01815, Development of AR-based Surgery Toolkit and Applications).

Author Contributions

Conceptualization: SMP, DK. Data curation: JP. Formal analysis: JP. Methodology: SMP, HJK, JSY. Software: JP. Validation: HJK. Writing–original draft: SMP. Writing–review & editing: HJK, JSY. Final approval of the manuscript: all authors.

Fig. 1

The augmented reality assisted pedicle screw fixation system setup and workflow. (A–D) Infrared (IR) camera shows the optical tracking system utilizing OptiTrack cameras. The custom-developed head-mounted display (HMD) with attached reflective markers. Spine model shows the prepared porcine cadaveric lumbar spine with muscle and ligamentous tissue removed while preserving the bones, discs, and joints. The surgical tools with attached reflective markers for real-time tracking. (E, F) Preoperative planning illustrates the computed tomography-based virtual planning for pedicle screw trajectories, with axial and three-dimensional views showing the planned screw paths. (G) Operation demonstrates the actual pedicle screw insertion guided by the augmented reality system with virtual planned trajectory (yellow arrow) and actual screw insertion path (blue arrow) displayed in real-time.

Fig. 2

Real-time augmented reality navigation during pedicle screw placement. (A) The upper image shows the surgeon’s view through the head-mounted display with real-time tracking of instruments and pedicle screw placement. The dynamic reference frame is attached to the porcine spine, and tracked instruments are visible. The virtual trajectory (green line) guides the screw insertion with real-time distance feedback. (B, C) The lower images show the navigation software interface with the virtual three-dimensional (3D) spine model (left) displaying the angle between actual and planned trajectory, and the registration points (right) marked on the 3D spine model for point-pair matching.

Fig. 3

Technical accuracy assessment of pedicle screw placement. (A) Three-dimensional reconstruction showing the porcine lumbar spine with inserted pedicle screws and planned trajectories (red rod). The blue plane illustrates the cross-sectional view for accuracy assessment. (B) Postoperative computed tomography axial view showing the measurement method for technical accuracy. Entry point deviation (green), tip point deviation (blue), and angular deviation (yellow dashed lines) between the planned trajectory (orange solid line) and actual screw placement were measured.

Fig. 4

Technical accuracy measurements of augmented reality assisted pedicle screw placement. Violin plots showing the distribution of (A) entry point deviation with a mean of 0.55 mm (standard deviation [SD]=0.33 mm), (B) tip deviation with a mean of 0.71 mm (SD=0.32 mm), and (C) angular deviation with a mean of 2.04° (SD=0.58°).

References

1. Gaines RW Jr. The use of pedicle-screw internal fixation for the operative treatment of spinal disorders. J Bone Joint Surg Am 2000;82:1458–76.

2. Hirano T, Hasegawa K, Takahashi HE, et al. Structural characteristics of the pedicle and its role in screw stability. Spine (Phila Pa 1976) 1997;22:2504–10.

3. Gautschi OP, Schatlo B, Schaller K, Tessitore E. Clinically relevant complications related to pedicle screw placement in thoracolumbar surgery and their management: a literature review of 35,630 pedicle screws. Neurosurg Focus 2011;31:E8.

4. Parker SL, McGirt MJ, Farber SH, et al. Accuracy of free-hand pedicle screws in the thoracic and lumbar spine: analysis of 6816 consecutive screws. Neurosurgery 2011;68:170–8.

5. Park SM, Shen F, Kim HJ, et al. How many screws are necessary to be considered an experienced surgeon for freehand placement of thoracolumbar pedicle screws?: analysis using the cumulative summation test for learning curve. World Neurosurg 2018;118:e550–6.

6. Tian NF, Xu HZ. Image-guided pedicle screw insertion accuracy: a meta-analysis. Int Orthop 2009;33:895–903.

7. Tian W, Zeng C, An Y, Wang C, Liu Y, Li J. Accuracy and postoperative assessment of pedicle screw placement during scoliosis surgery with computer-assisted navigation: a meta-analysis. Int J Med Robot 2017;13:e1732.

8. Park SM, Kim HJ, Lee SY, Chang BS, Lee CK, Yeom JS. Radiographic and clinical outcomes of robot-assisted posterior pedicle screw fixation: two-year results from a randomized controlled trial. Yonsei Med J 2018;59:438–44.

9. Kanhangad MP, Srinivasa V, Thirugnanam B, et al. Robotic spine systems: overcoming surgeon experience in pedicle screw accuracy: a prospective study. Asian Spine J 2024;18:663–72.

10. Leger E, Drouin S, Collins DL, Popa T, Kersten-Oertel M. Quantifying attention shifts in augmented reality image-guided neurosurgery. Healthc Technol Lett 2017;4:188–92.

11. Olexa J, Shear B, Han N, et al. Feasibility of a novel augmented reality overlay for cervical screw placement in phantom spine models. Asian Spine J 2024;18:372–9.

12. Shuhaiber JH. Augmented reality in surgery. Arch Surg 2004;139:170–4.

13. Park SM, Kim HJ, Yeom JS. Is minimally invasive surgery a game changer in spinal surgery? Asian Spine J 2024;18:743–52.

14. Burstrom G, Persson O, Edstrom E, Elmi-Terander A. Augmented reality navigation in spine surgery: a systematic review. Acta Neurochir (Wien) 2021;163:843–52.

15. Park SM, Kim HJ, Yeom JS, Shin YG. Spine surgery using augmented reality. J Korean Soc Spine Surg 2019;26:26–32.

16. Azad TD, Warman A, Tracz JA, Hughes LP, Judy BF, Witham TF. Augmented reality in spine surgery: past, present, and future. Spine J 2024;24:1–13.

17. Yoon JW, Chen RE, Kim EJ, et al. Augmented reality for the surgeon: systematic review. Int J Med Robot 2018;14:e1914.

18. Ma L, Zhao Z, Chen F, Zhang B, Fu L, Liao H. Augmented reality surgical navigation with ultrasound-assisted registration for pedicle screw placement: a pilot study. Int J Comput Assist Radiol Surg 2017;12:2205–15.

19. Elmi-Terander A, Nachabe R, Skulason H, et al. Feasibility and accuracy of thoracolumbar minimally invasive pedicle screw placement with augmented reality navigation technology. Spine (Phila Pa 1976) 2018;43:1018–23.

20. Liu A, Jin Y, Cottrill E, et al. Clinical accuracy and initial experience with augmented reality-assisted pedicle screw placement: the first 205 screws. J Neurosurg Spine 2021;36:351–7.

21. Spirig JM, Roner S, Liebmann F, Furnstahl P, Farshad M. Augmented reality-navigated pedicle screw placement: a cadaveric pilot study. Eur Spine J 2021;30:3731–7.

22. Wi W, Park SM, Shin BS. Computed tomography-based preoperative simulation system for pedicle screw fixation in spinal surgery. J Korean Med Sci 2020;35:e125.

23. Gertzbein SD, Robbins SE. Accuracy of pedicular screw placement in vivo. Spine (Phila Pa 1976) 1990;15:11–4.

24. Elmi-Terander A, Skulason H, Soderman M, et al. Surgical navigation technology based on augmented reality and integrated 3D intraoperative imaging: a spine cadaveric feasibility and accuracy study. Spine (Phila Pa 1976) 2016;41:E1303–11.

25. Felix B, Kalatar SB, Moatz B, et al. Augmented reality spine surgery navigation: increasing pedicle screw insertion accuracy for both open and minimally invasive spine surgeries. Spine (Phila Pa 1976) 2022;47:865–72.

26. Dennler C, Jaberg L, Spirig J, et al. Augmented reality-based navigation increases precision of pedicle screw insertion. J Orthop Surg Res 2020;15:174.

27. Farshad M, Spirig JM, Suter D, et al. Operator independent reliability of direct augmented reality navigated pedicle screw placement and rod bending. N Am Spine Soc J 2021;8:100084.

28. Elmi-Terander A, Burstrom G, Nachabe R, et al. Augmented reality navigation with intraoperative 3D imaging vs fluoroscopy-assisted free-hand surgery for spine fixation surgery: a matched-control study comparing accuracy. Sci Rep 2020;10:707.

29. Burstrom G, Nachabe R, Persson O, Edstrom E, Elmi Terander A. Augmented and virtual reality instrument tracking for minimally invasive spine surgery: a feasibility and accuracy study. Spine (Phila Pa 1976) 2019;44:1097–104.

30. Molina CA, Phillips FM, Colman MW, et al. A cadaveric precision and accuracy analysis of augmented reality-mediated percutaneous pedicle implant insertion. J Neurosurg Spine 2020;34:316–24.