Overcoming CT Registration Failures in Robotic Spine Surgery: A Lateral Fiducial Positioning Technique for Obese Patients

Purpose CT registration failure represents a critical barrier excluding severely obese patients from robotic-assisted spine surgery (RASS) benefits. This study validates a novel lateral fiducial positioning technique to overcome field-of-view limitations that cause registration failures in patients with BMI > 40 kg/m², addressing the geometric incompatibility between obese patient size and current imaging constraints. Methods Retrospective analysis of 54 consecutive patients (BMI > 40 kg/m²) undergoing RASS using MazorX Stealth Edition with intraoperative O-arm imaging between October 2023 and November 2024. Lateral fiducial positioning repositioned markers along the patient's flank when standard central positioning demonstrated inadequate visualization on scout images, utilizing O-arm's asymmetric field-of-view (40 cm lateral vs. 15 cm sagittal coverage). Primary outcome was first-attempt registration success rate. Results Mean BMI was 43.6 ± 2.7 kg/m² (range 40.3–51.0). First-attempt registration success was achieved in 45/54 cases (83.3%, 95% CI: 72.1%-91.4%). Lateral positioning was used in 16 cases (29.6%) with significantly higher success rates versus standard positioning (93.8% vs 78.9%, P = 0.043). Ultimate registration success was 100%. Patients requiring reattempts had longer O-arm acquisition times (32.6 vs 19.2 minutes, P < 0.001) and higher radiation exposure (66.6 vs 38.0 units, P < 0.001). Optimal pedicle screw placement (Gertzbein-Robbins Grade A + B) was achieved in 97.6% of 288 screws. Conclusion Lateral fiducial positioning eliminates CT registration failures in severely obese patients undergoing robotic spine surgery, achieving 100% ultimate registration success while maintaining surgical accuracy. This immediately implementable technique expands robotic surgery access to high-BMI patients without requiring additional equipment, ensuring obesity alone does not preclude patients from precision robotic assistance benefits.