Technical Strategies and Learning Curve in Robotic-assisted Peripheral Nerve Surgery

Abstract

Background: Robotic-assisted peripheral nerve surgery (RASPN) has emerged as a promising advancement in microsurgery, offering enhanced precision and tremor reduction for nerve coaptations. This study investigated the largest published patient collective in RASPN and provided specific technical aspects, operative setups, and a learning curve.

Methods: Data collection involved creating a prospective database that recorded surgical details such as surgery type, duration, nerve coaptation time, and number of stitches. The experienced surgeon first underwent a 12-hour training program utilizing the Symani robot system in combination with optical magnification tools before using the system clinically.

Results: The study included 19 patients who underwent robot-assisted peripheral nerve reconstruction. The cohort included six men (31.6%) and 13 women (68.4%), with an average age of 53.8 ± 18.4 years. The procedures included nerve transfers, targeted muscle reinnervation, neurotized free flaps, and autologous nerve grafts. Learning curve analysis revealed no significant reduction in time per stitch over the initial nine coaptations (4.9 ± 0.5 min) compared with the last 10 coaptations (5.5 ± 1.5 min).

Conclusions: The learning curve for RASPN was compared with early experiences with other surgical robots, emphasizing the importance of surgical proficiency and assistant training. Obstacles such as instrument grip strength and blood clot formation were highlighted, and suggestions for future advancements were proposed. RASPN presents an exciting opportunity to enhance precision; however, ongoing research and optimization are necessary to fully harness its benefits.

Fig. 1.

Etiology of the peripheral nerve lesion treated with RASPN with direct nerve repair, nerve transfers or, for example, burn defects with neurotized free flap reconstruction. RASPN was mainly performed for traumatic injuries (A), with a higher frequency in the upper extremity (B). C, Our team primarily focuses on nerve transfers for peripheral nerve reconstruction. PAD, peripheral artery disease; TMR, targeted muscle reinnervation.

Fig. 2.

Learning curve focusing on the needed time and operation. The coaptation of all cases is shown (A), as well as time per stitch in general (B). C, Time per stitch did not differ significantly depending on the applied procedure.

Fig. 3.

Learning curve of RASPN. Nerve coaptations of a single surgeon performing nerve transfers. A, Lower learning curve over the amount of nerve coaptations. No significant differences were shown between the first nine nerve coaptations and the second 10 nerve coaptations (B) and overall cases (C).

Fig. 4.

Surgeon position by robotic peripheral nerve surgery. The surgeon and surgical assistant are sitting towards the 3D screen showing the operative situs. A, The surgical assistant sits between the robotic arms, supporting the surgeon performing the epineural suture. B, The nursing staff sits parallel to the surgical assistant’s visualization of the operative situs.