Robotic Spinal Surgery: Current Evidence, Clinical Applications, and Future Perspectives

Background: Robotic-assisted spine surgery has evolved from mechanically guided pedicle screw placement into increasingly integrated platforms combining preoperative planning, intraoperative three-dimensional imaging, navigation, and robotic trajectory guidance. Although pedicle screw insertion remains the most extensively studied application, robotic technology is progressively being incorporated into minimally invasive fusion procedures, deformity surgery, trauma, revision surgery, and oncological reconstruction. The principal proposed benefits include improved instrumentation accuracy, reduced dependence on intraoperative fluoroscopy, reproducible execution of preplanned trajectories, and facilitation of minimally invasive workflows. However, uncertainty remains regarding its effect on patient-centered clinical outcomes, cost-effectiveness, radiation exposure, and superiority over contemporary navigation systems. Methods: A structured literature review was conducted to evaluate contemporary evidence concerning robotic-assisted thoracic and lumbar spinal instrumentation, as well as to assess potential future developments in this field. Comparative studies and systematic reviews/meta-analysis evaluating robotic-assisted techniques against free hand, fluoroscopy-guided, or comput-er-assisted navigation techniques were considered. Outcomes of interest included pedicle screw accuracy, intraoperative and postoperative screw revision, radiation exposure, operative time, blood loss, hospital length of stay, complications, patient-reported outcomes, learning curve, and economic considerations. Robotic platforms were additionally considered separately because differences between imaging, registration, mechanical guidance, and workflow may limit generalization of pulled results across systems. Results: The most consistent advantage of robotic-assisted spinal instrumentation concerns pedicle screw accuracy. Contemporary systematic reviews and meta-analysis generally demonstrate higher rates of optimal od clinically acceptable screw placement compared with conventional freehand or fluoroscopy-guided techniques, although the magnitude of benefit varies among robotic platforms, indications, and comparator techniques. Recent evidence also suggests that robotic assistance may provide an accuracy advantage over image-based navigation, however, differences in revision rates, operative time, blood loss, and complications are substantially less consistent. Radiation outcomes depend strongly on how exposure is defined. Robotic workflows can reduce occupational exposure to the surgical team by shifting imaging toward preoperative or intraoperative three-dimensional acquisition, but total patient radiation dose vary according to imaging modality, registration strategy, and institutional protocol. Evidence regarding operative duration is similarly heterogeneous and influenced by the learning curve and workflow maturity. Some studies report reductions in blood loss and length of stay, particularly when robotic assistance facilitates minimally invasive surgery, although these advantages cannot always be attributed to robotics independently of the operative approach. Evidence demonstrating superior long-term patient-reported outcomes, lower neurological complication rates, or reduced reoperation remains limited. High acquisition and maintenance cost, platform-specific workflows, registration errors, technical failure, and the need for dedicated team training remain important barriers to widespread implementation. Conclusions: Robotic assistance has become an established precision technology for spinal instrumentation, with the strongest evidence supporting improved pedicle screw placement accuracy. Its clinical value extends beyond accuracy through integration with navigation, advanced imaging, and minimally invasive surgical workflows, however, improved technical precision should not be equated automatically with superior patient outcomes. Future research should increasingly compare robotic systems with contemporary three-dimensional navigation rather than fluoroscopy alone and should prioritize standardized patient-centered outcomes, radiation dosimetry, workflow efficiency, long-term revision rates, and cost-effectiveness. Advances in artificial intelligence, automated surgical planning, augmented reality, and increasingly autonomous robotic functions my further expand the role of robotics from trajectory guidance toward comprehensive digital surgical platforms.