Clinical trials show robotic-assisted segmentectomy improves outcomes in early-stage NSCLC, highlighting advancements in 3D imaging and precision surgery.
Background: Recent trials, including JCOG0802/WJOG4607L and CALGB140503, con-firmed the oncological adequacy of segmentectomy for early-stage non-small cell lung cancer (NSCLC). This shift emphasizes the preservation of pulmonary function and minimal invasiveness. Robot-assisted thoracic surgery (RATS) offers enhanced anatomi-cal precision and potentially improves segmentectomy outcomes. Methods: We reviewed the current evidence comparing sublobar resection and lobectomy for early-stage NSCLC, focusing on RATS segmentectomy. Clinical trials, perioperative and long-term outcomes, technical innovations, and patient selection criteria were analyzed. Comparative data among RATS, video-assisted thoracoscopic surgery (VATS), and open approaches were synthesized, including the emerging roles of AI and 3D imaging. Results: Segmentectomy yields survival outcomes equivalent or superior to lobectomy for stage IA peripheral NSCLC ≤2 cm, with better pulmonary function despite higher locoregional recurrence. RATS enhances visualization, dexterity, and ergonomics, thereby enabling precise dissec-tion and lymph node assessment. Compared to VATS and open surgery, RATS shows lower conversion rates, reduced pain, and comparable oncological control. Innovations, such as indocyanine green imaging, 3D modeling, and AI-guided navigation, support margin accuracy and personalized care. Conclusions: Segmentectomy has redefined the surgical standards for early-stage NSCLC. RATS maximizes the minimally invasive bene-fits by combining oncological safety and functional preservation. Its technical precision facilitates complex resections and integration with digital planning tools to advance per-sonalized thoracic surgery. RATS represents the next evolution of minimally invasive thoracic surgery, redefining the balance between oncological safety and functional preservation in early-stage NSCLC.
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Nishino et al. (2025) studied this question.
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