Tag: robotic spine surgery

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Disruptive technologies in spine surgery: current trends, outcomes, and ethical implications

J Neurosurg Spine 44:756–768, 2026

Disruptive technologies in spine surgery—AR/VR, robotics, neuronavigation, endoscopy, and patient-specific implants—are examined for their roles in enhancing precision, training, and patient outcomes. The review summarizes evidence for preoperative simulation, AR-assisted planning, and 3D segmentation, highlighting improvements in accuracy, reduced fluoroscopy, and trainee confidence.

Intraoperative advances such as robot-assisted techniques, computer-assisted navigation, and endoscopic approaches offer minimally invasive alternatives with favorable recovery profiles but face challenges of cost, learning curves, and equitable access. The authors emphasize ethical considerations, need for standardized outcomes, and strategies to expand accessibility and training.

Scope Disruptive spine-surgery technologies emphasized include AR/VR (XR), advanced navigation, robotics, patient-specific implants/3D printing, and endoscopic spine surgery.

XR definitions VR provides a fully immersive digital environment, AR overlays digital content onto the real world, and MR blends both; all fall under XR.

Training impact VR simulation in spine training improved trainee comfort and autonomy and reduced fluoroscopy use in lateral lumbar interbody fusion simulations; VR-trained learners also made fewer pedicle-screw placement errors than traditional instruction.

Preop planning VR-based planning can reduce fluoroscopy/localization time and improve puncture accuracy in endoscopic lumbar discectomy; segmented 3D models support rehearsal, trajectory planning, and risk assessment around critical structures.

AR navigation outcomes Wearable AR navigation (e.g., FDA-cleared xvision) has shown high pedicle-screw placement accuracy (reported ~96.7% thoracic and ~99.1% lumbosacral) and may reduce operative time and radiation exposure.

Patient-specific surgery Segmentation + 3D printing/predictive modeling enable personalized approaches and implants (e.g., patient-specific rods, templates, custom cages), with early reports of high accuracy for template-guided instrumentation and promising feasibility for custom interbody devices.

Endoscopic techniques ESS supports minimally invasive treatment across multiple pathologies and can match conventional outcomes for lumbar disc herniation while improving recovery (e.g., shorter stays/earlier return to work), but broader adoption is constrained by learning curve and reimbursement challenges.

Implementation ethics/costs High acquisition/maintenance costs and limited reimbursement risk widening access disparities; recommended mitigations include subsidized training, shared equipment models, and reimbursement policies to support equitable implementation alongside standardized outcomes and training.

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A cadaveric precision and accuracy analysis of augmented reality–mediated percutaneous pedicle implant insertion

J Neurosurg Spine 34:316–324, 2021

Augmented reality–mediated spine surgery (ARMSS) is a minimally invasive novel technology that has the potential to increase the efficiency, accuracy, and safety of conventional percutaneous pedicle screw insertion methods. Visual 3D spinal anatomical and 2D navigation images are directly projected onto the operator’s retina and superimposed over the surgical field, eliminating field of vision and attention shift to a remote display. The objective of this cadaveric study was to assess the accuracy and precision of percutaneous ARMSS pedicle implant insertion.

METHODS Instrumentation was placed in 5 cadaveric torsos via ARMSS with the xvision augmented reality headmounted display (AR-HMD) platform at levels ranging from T5 to S1 for a total of 113 total implants (93 pedicle screws and 20 Jamshidi needles). Postprocedural CT scans were graded by two independent neuroradiologists using the Gertzbein- Robbins scale (grades A–E) for clinical accuracy. Technical precision was calculated using superimposition analysis employing the Medical Image Interaction Toolkit to yield angular trajectory (°) and linear screw tip (mm) deviation from the virtual pedicle screw position compared with the actual pedicle screw position on postprocedural CT imaging.

RESULTS The overall implant insertion clinical accuracy achieved was 99.1%. Lumbosacral and thoracic clinical accuracies were 100% and 98.2%, respectively. Specifically, among all implants inserted, 112 were noted to be Gertzbein- Robbins grade A or B (99.12%), with only 1 medial Gertzbein-Robbins grade C breach (> 2-mm pedicle breach) in a thoracic pedicle at T9. Precision analysis of the inserted pedicle screws yielded a mean screw tip linear deviation of 1.98 mm (99% CI 1.74–2.22 mm) and a mean angular error of 1.29° (99% CI 1.11°–1.46°) from the projected trajectory. These data compare favorably with data from existing navigation platforms and regulatory precision requirements mandating that linear and angular deviation be less than 3 mm (p < 0.01) and 3° (p < 0.01), respectively.

CONCLUSIONS Percutaneous ARMSS pedicle implant insertion is a technically feasible, accurate, and highly precise method.

 

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Augmented reality–assisted pedicle screw insertion

J Neurosurg Spine 31:139–146, 2019

Augmented reality (AR) is a novel technology that has the potential to increase the technical feasibility, accuracy, and safety of conventional manual and robotic computer-navigated pedicle insertion methods. Visual data are directly projected to the operator’s retina and overlaid onto the surgical field, thereby removing the requirement to shift attention to a remote display. The objective of this study was to assess the comparative accuracy of AR-assisted pedicle screw insertion in comparison to conventional pedicle screw insertion methods.

METHODS Five cadaveric male torsos were instrumented bilaterally from T6 to L5 for a total of 120 inserted pedicle screws. Postprocedural CT scans were obtained, and screw insertion accuracy was graded by 2 independent neuroradiologists using both the Gertzbein scale (GS) and a combination of that scale and the Heary classification, referred to in this paper as the Heary-Gertzbein scale (HGS). Non-inferiority analysis was performed, comparing the accuracy to freehand, manual computer-navigated, and robotics-assisted computer-navigated insertion accuracy rates reported in the literature. User experience analysis was conducted via a user experience questionnaire filled out by operators after the procedures.

RESULTS The overall screw placement accuracy achieved with the AR system was 96.7% based on the HGS and 94.6% based on the GS. Insertion accuracy was non-inferior to accuracy reported for manual computer-navigated pedicle insertion based on both the GS and the HGS scores. When compared to accuracy reported for robotics-assisted computer-navigated insertion, accuracy achieved with the AR system was found to be non-inferior when assessed with the GS, but superior when assessed with the HGS. Last, accuracy results achieved with the AR system were found to be superior to results obtained with freehand insertion based on both the HGS and the GS scores. Accuracy results were not found to be inferior in any comparison. User experience analysis yielded “excellent” usability classification.

CONCLUSIONS AR-assisted pedicle screw insertion is a technically feasible and accurate insertion method.

 

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