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Background: Sacroiliac (SI) screw fixation is a demanding technique, with a high rate of screw malposition due to the complex pelvic anatomy. TiRobot™ is an orthopedic surgery robot which can be used for SI screw fixation. This study aimed to evaluate the accuracy of robot-assisted placement of SI screws compared with a freehand technique. Methods: Thirty patients requiring posterior pelvic ring stabilization were randomized to receive freehand or robot-assisted SI screw fixation, between January 2016 and June 2016 at Beijing Jishuitan Hospital. Forty-five screws were placed at levels S1 and S2. In both methods, the primary end point screw position was assessed and classified using postoperative computed tomography. Fisher's exact probability test was used to analyze the screws' positions. Secondary end points, such as duration of trajectory planning, surgical time after reduction of the pelvis, insertion time for guide wire, number of guide wire attempts, and radiation exposure without pelvic reduction, were also assessed. Results: Twenty-three screws were placed in the robot-assisted group and 22 screws in the freehand group; no postoperative complications or revisions were reported. The excellent and good rate of screw placement was 100% in the robot-assisted group and 95% in the freehand group. The P value (0.009) showed the same superiority in screw distribution. The fluoroscopy time after pelvic reduction in the robot-assisted group was significantly shorter than that in the freehand group (median [Q1, Q3]: 6.0 [6.0, 9.0] s vs. median [Q1, Q3]: 36.0 [21.5, 48.0] s; χ2 = 13.590, respectively, P < 0.001); no difference in operation time after reduction of the pelvis was noted (χ2 = 1.990, P = 0.158). Time for guide wire insertion was significantly shorter for the robot-assisted group than that for the freehand group (median [Q1, Q3]: 2.0 [2.0, 2.7] min vs. median [Q1, Q3]: 19.0 [15.5, 45.0] min; χ2 = 20.952, respectively, P < 0.001). The number of guide wire attempts in the robot-assisted group was significantly less than that in the freehand group (median [Q1, Q3]: 1.0 [1.0,1.0] time vs. median [Q1, Q3]: 7.0 [1.0, 9.0] times; χ2 = 15.771, respectively, P < 0.001). The instrumented SI levels did not differ between both groups (from S1 to S2, χ2 = 4.760, P = 0.093). Conclusions: Accuracy of the robot-assisted technique was superior to that of the freehand technique. Robot-assisted navigation is safe for unstable posterior pelvic ring stabilization, especially in S1, but also in S2. SI screw insertion with robot-assisted navigation is clinically feasible.

Background: Old pelvis fractures are among the most challenging fractures to treat because of their complex anatomy, difficult-to-access surgical sites, and the relatively low incidence of such cases. Proper evaluation and surgical planning are necessary to achieve the pelvic ring symmetry and stable fixation of the fracture. The goal of this study was to assess the use of three-dimensional (3D) printing techniques for surgical management of old pelvic fractures. Methods: First, 16 dried human cadaveric pelvises were used to confirm the anatomical accuracy of the 3D models printed based on radiographic data. Next, nine clinical cases between January 2009 and April 2013 were used to evaluate the surgical reconstruction based on the 3D printed models. The pelvic injuries were all type C, and the average time from injury to reconstruction was 11 weeks (range: 8-17 weeks). The workflow consisted of: (1) Printing patient-specific bone models based on preoperative computed tomography (CT) scans, (2) virtual fracture reduction using the printed 3D anatomic template, (3) virtual fracture fixation using Kirschner wires, and (4) preoperatively measuring the osteotomy and implant position relative to landmarks using the virtually defined deformation. These models aided communication between surgical team members during the procedure. This technique was validated by comparing the preoperative planning to the intraoperative procedure. Results: The accuracy of the 3D printed models was within specification. Production of a model from standard CT DICOM data took 7 hours (range: 6-9 hours). Preoperative planning using the 3D printed models was feasible in all cases. Good correlation was found between the preoperative planning and postoperative follow-up X-ray in all nine cases. The patients were followed for 3-29 months (median: 5 months). The fracture healing time was 9-17 weeks (mean: 10 weeks). No delayed incision healing, wound infection, or nonunions occurred. The results were excellent in two cases, good in five, and poor in two based on the Majeed score. Conclusions: The 3D printing planning technique for pelvic surgery was successfully integrated into a clinical workflow to improve patient-specific preoperative planning by providing a visual and haptic model of the injury and allowing patient-specific adaptation of each osteosynthesis implant to the virtually reduced pelvis.