Robotic-assisted microsurgery using the MUSA-robot: evaluation of the learning curve in three clinical pilot trials

Aim: Current microsurgical procedures are limited by the physiological tremor and dexterity of the surgeon. The MicroSurgical Assistant (MUSA, Microsure), the world’s first robotic platform for (super)microsurgery can aid in resolving issues encountered during microsurgery. This study presents an overview of the operating times and Structured Assessment of Microsurgery Skills (SAMS) scores to assess the duration and quality of microsurgical anastomoses for three microsurgical procedures currently performed using the MUSA. Methods: This study integrates data from one ongoing randomized controlled trial focusing on robotic-assisted lymphaticovenous anastomosis, along with findings from two separate prospective pilot studies concerning digital nerve repair and free tissue transplantation. SAMS scores and time needed per anastomosis were used to evaluate the quality and learning curve of the MUSA-assisted procedures. Results: Thirty-five robotic-assisted procedures were analyzed, including 18 lymphaticovenous anastomoses, 9 digital nerve repairs, and 8 free tissue transplantations. All procedures showed a trend of a decrease in the time needed to perform the procedure. Moreover, the mean overall SAMS scores for all three procedures were rated above ‘satisfactory’, with all procedures demonstrating a consistent trend of increasing SAMS scores over time. Conclusion: The evaluation of anastomosis’ quality in the initial cohorts of patients undergoing robotic-assisted microsurgery using MUSA indicates satisfying outcomes across all three types of procedures. The reduction in anastomosis time and the improvement in SAMS scores imply an ongoing learning process among the operating surgeons. Subsequent reports are expected to provide information on reaching a plateau phase in procedural efficiency.