Computer-Assisted Navigation in Shoulder Arthroplasty: A Narrative Review

Abstract

Shoulder arthroplasty, including total shoulder arthroplasty (TSA) and reverse shoulder arthroplasty (RSA), is a well-established procedure for treating degenerative, post-traumatic, and inflammatory conditions of the shoulder joint. The success of these surgeries depends largely on the precise placement of implants, which helps restore proper joint mechanics, reduce complications, and extend the lifespan of the prosthesis. However, achieving accurate implant positioning can be challenging, especially in cases involving severe bone loss, anatomical deformities, or prior surgeries. Poor alignment can lead to instability, implant loosening, and the need for revision surgery. Computer-assisted navigation has become an important tool in shoulder arthroplasty, providing real-time intraoperative guidance to improve surgical accuracy and consistency. By integrating preoperative 3D imaging with intraoperative tracking, navigation technology allows surgeons to optimize glenoid component placement, reducing the risk of malalignment and mechanical failure. Research suggests that navigation-assisted techniques improve precision, enhance functional outcomes, and may even reduce complication rates by optimizing fixation strategies, such as using fewer but longer screws in RSA. Despite its benefits, navigation in shoulder arthroplasty is not without challenges. It requires additional surgical time, increases costs, and demands a learning curve for surgeons. However, with advancements in artificial intelligence, augmented reality, and robotic-assisted surgery, navigation is expected to become even more effective and accessible. This review explores the current impact of navigation on clinical outcomes, its role in complex cases, and the future potential of this technology. While early results are promising, further long-term studies are needed to fully assess its value and establish best practices for its routine use in shoulder arthroplasty.