First experience with a novel image guidance technology for posterior pedicle screw fixation: A cadaveric study on 2D/3D registration-based spine surgery
Year: 2025
Type: article
Abstract: PURPOSE: Minimally invasive pedicle screw insertion relies on imaging techniques due to limited anatomical visualization. A potential solution for intraoperative 3D guidance is using 2D/3D registration algorithms, which align intraoperative 2D X-rays with preoperatively acquired 3D datasets. This study aimed to evaluate the application of a novel 2D/3D image guidance software in posterior fixation with pedicle screws regarding accuracy, speed, and radiation exposure in a realistic clinical setting. METHODS: Four human cadavers were instrumented with a total of 80 pedicle screws (from T8 to L5) by eight surgeons using 2D/3D image guidance. The surgeons, with varying levels of experience in spine surgery and navigation, utilized the software for the first time. Before the procedures, they underwent a structured one-hour training session. Accuracy, time parameters, and radiation exposure during pedicle screw insertion were assessed. RESULTS: All K-wires were inserted correctly, demonstrating precise wire placement, regardless of the surgeons' experience. For pedicle screw placement, the 2D/3D image guidance achieved high accuracy of 95.0%, with no superior or inferior perforations. The mean time for each pedicle screw placement was 7.62 ± 2.83 min, with an average radiation exposure of 1.24 µSv per pedicle screw for the surgeon. CONCLUSION: The use of 2D/3D image guidance in this study demonstrated high precision in the placement of K-wires and pedicle screws. Consequently, 2D/3D image guidance presents a promising tool for both experienced and inexperienced users, facilitating precise 3D guidance of pedicle screws with a standard 2D C-arm.
Source: European Spine Journal
Institution: Klinikum Ludwigshafen
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,790
OpenAlex ID: W4415106483
