Robotic-Assisted Arthroscopy Promises Enhanced Procedural Efficiency, Visualization, and Control but Must Overcome Barriers to Adoption

Abstract

Robotic-assisted surgery is now well-established in spine surgery and total joint arthroplasty, but its application to arthroscopy has only recently emerged in the context of advances in artificial intelligence (AI) and robotic technology. This new application addresses limitations of conventional arthroscopy, including constrained depth perception, variation in technique or anatomy leading to inaccuracies, manual fluid management adjustments, and limitations in dexterity due to the requirement that one hand is occupied by the arthroscope. Early preclinical and cadaveric studies demonstrate submillimeter precision and improved anatomic accuracy in procedures such as anterior cruciate ligament reconstruction, but widespread clinical adoption remains limited by regulatory, economic, and training hurdles. This review article synthesizes the capabilities and applications of current robotic-assisted arthroscopy platforms, surveys the landscape of available technologies, and examines barriers to adoption, thereby looking ahead to the potential use of this technology in redefining arthroscopic surgery.