ArticleJournal of robotic surgery2025
Biomechanical optimization of pedicle screw trajectories in osteoporotic lumbar fusion: finite element analysis and validation of robotic-assisted implementation.
Article in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Osteoporotic degenerative lumbar disease poses substantial challenges to pedicle screw fixation, with high rates of implant loosening and malposition compromising stability and safety. This study integrated finite element analysis (FEA) for preoperative trajectory optimization with robotic-assisted execution to enhance outcomes in short- and long-segment fusions. A three-dimensional FEA model of the L3-S1 osteoporotic spine was developed from CT data, simulating parallel, 15° medially angulated, and trapezoidal trajectories for two-segment (L4-L5) and three-segment (L3-L5) constructs under physiologic loads (350 N follower load + 10 N·m moments). Outcomes included range of motion (ROM), von Mises stress on fixation hardware and facet cartilage. A retrospective cohort of 83 patients with osteoporotic lumbar disease undergoing L3-S1 fusion was divided into robot-assisted (n = 41, 212 screws) and freehand (n = 42, 208 screws) groups. Screw accuracy was graded per Gertzbein-Robbins criteria; facet joint violation (FJV), transverse section angle (TSA), and screw length were assessed via postoperative CT. FEA revealed parallel trajectories minimized ROM and micromotion in two-segment fusions, while trapezoidal configurations provided superior stability in three-segment fusions, with lowest facet cartilage stress (e.g., 1.113 MPa flexion). Robot-assisted placement achieved higher Grade A accuracy (87.3% vs. 75.0%; p = 0.002), reduced overall FJV (9.9% vs. 34.1%; p < 0.001), and enabled longer screws (e.g., L5: 50.8 ± 3.4 mm vs. 47.9 ± 4.2 mm; p < 0.001) with greater TSA (e.g., S1: 25.9° ± 1.3° vs. 23.8° ± 1.6°; p < 0.001), particularly at L5-S1. FEA-guided trajectory selection, executed robotically, optimizes biomechanical stability and clinical precision in osteoporotic fusions, reducing malposition risks and enhancing screw purchase. This “plan-and-execute” paradigm advances personalized spine surgery.
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