Preoperative Trajectory Planning for Minimally Invasive Removal of Sacroiliac Screws: A Retrospective Cohort Study

Background: Minimally invasive removal of sacroiliac screws is often challenging due to intraoperative uncertainty regarding the screw trajectory, leading to prolonged operative time and increased radiation exposure. Although robot-assisted techniques can improve accuracy, they are associated with high costs. This study aimed to evaluate the feasibility of a "preoperative trajectory planning method" based on preoperative imaging and trigonometric calculation for the removal of sacroiliac screws. Methods: We conducted a retrospective cohort study of 36 patients who underwent sacroiliac screw removal between January 2018 and December 2024. The patients were divided into three groups: a modified group (n=14, using the new method), a traditional group (n=13, relying on intraoperative fluoroscopy for freehand exploration), and a robot-assisted group (n=9, using the TiRobot orthopedic robot). The reasons for screw removal were analyzed, and the operative time, number of intraoperative fluoroscopies, and hospitalization costs were compared among the three groups. Results: All screws were successfully removed. The mean operative time in the modified group (18.6 ± 12.9 minutes) was significantly shorter than that in both the traditional group (25.8 ± 8.8 minutes) and the robot-assisted group (31.1 ± 8.9 minutes) (all P < 0.05). The mean number of fluoroscopies in the modified group (5.9 ± 2.5) showed no significant difference from the robot-assisted group (5.0 ± 2.9), but both were significantly lower than the traditional group (13.2 ± 5.4, P < 0.01). The hospitalization cost in the robot-assisted group (11480.94 ± 472.63 CNY) was significantly higher than that in both the modified and traditional groups (P < 0.01). Conclusion: The "preoperative trajectory planning method" enables precise and efficient removal of sacroiliac screws without reliance on expensive robotic equipment. This method features a short learning curve, reduces operative time and intraoperative radiation exposure, and does not impose an additional financial burden on patients, demonstrating good potential for broad clinical application.