Mixed reality, artificial intelligence and augmented surgeons
Background: Orthopedic surgery is transitioning from subjective, skill-based outcomes toward standardized digital guidance to mitigate human error and enhance procedural precision. Despite the availability of computer-assisted technologies for over two decades, widespread clinical integration remains limited by high costs, logistical complexities, and technical barriers such as recalibration inaccuracies.
Objective: This review evaluates the current applications, clinical efficacy, and limitations of three-dimensional (3D) printing, computer navigation, and robotics in orthopedics, while assessing the potential of mixed reality (MR) to transform surgical workflows.
Key Points: 3D printing enables the production of patient-specific implants and cutting guides, offering advantages in complex pelvic reconstructions and oncology; however, soft-tissue interference and regulatory hurdles persist. Computer navigation and robotic-assisted systems improve component alignment and ligamentous balancing in arthroplasty, yet current literature lacks definitive evidence of superior long-term implant survivorship or functional outcomes compared to conventional techniques. Adoption is further hindered by increased operative time and radiation exposure. Mixed reality introduces a distinct paradigm, allowing sterile, gesture-controlled interaction with holographic data. Future MR applications may include automated registration via laser-based surface mapping and the integration of artificial intelligence (AI) to enhance intraoperative safety. AI algorithms could potentially provide real-time anatomical warnings and facilitate mass data analysis to refine surgical techniques.
Conclusion: While navigation and robotics face significant economic and technical constraints, mixed reality presents a cost-effective, ergonomic alternative. The integration of MR with artificial intelligence may catalyze the broader adoption of computer-assisted orthopedic surgery by improving interactivity and data-driven decision-making.
