Learning curve analysis of robotic-assisted thoracoscopic lung resection performed by a novice thoracic surgeon

Objectives: Robot-assisted thoracoscopic surgery has been increasingly adopted for lung resection, and opportunities for novice surgeons to perform this procedure are expanding. However, evidence regarding the early learning curves among novice thoracic surgeons remains limited. We performed this study to evaluate the learning curve and perioperative outcomes of robot-assisted thoracoscopic surgery for anatomical lung resections performed by novice surgeons. Methods: We reviewed 30 consecutive patients who underwent robot-assisted thoracoscopic anatomical lung resections between April and December 2025. All procedures were performed by a single novice thoracic surgeon with 4 years of experience in thoracic surgery. The primary outcome was console duration. Secondary outcomes included operative time, estimated blood loss, conversion to thoracotomy, postoperative complications, air leaks, chest drain duration, and length of hospital stay. Learning curve analyses were performed using scatter plots, moving averages, and cumulative sum analyses. Results: The median console time was 122 minutes (range, 50-221 minutes), which decreased with increasing experience. The median operative time was 186 minutes (range, 97-306 minutes) and showed a similar downward trend. Cumulative sum analysis identified a clear point indicating procedural proficiency after approximately 20 cases. The median blood loss was 20 mL, which was consistently low. One planned conversion to thoracotomy (3.3%) was performed because of severe hilar adhesions. No major postoperative complications (Clavien-Dindo grade ≥III) were observed. Conclusions: Robot-assisted thoracoscopic anatomical lung resection can be safely performed by novice thoracic surgeons using a structured training framework. Procedural proficiency was achieved in approximately 20 cases, with favorable perioperative outcomes.