AI-Assisted Volumetric Comparison of Parenchyma-Sparing Effect in Robotic Segmentectomy vs Lobectomy.

Abstract

Background and objective: In recent years, pulmonary segmentectomy has become a preferred treatment option for early-stage lung cancer. The primary factor encouraging clinicians to choose segmentectomy is the assumption of greater parenchymal preservation. In this study, we investigated the parenchyma-sparing effect of robotic pulmonary segmentectomy compared with robotic lobectomy using artificial intelligence (AI)-assisted 3-dimensional (3D) volumetric analysis.

Methods: Preoperative and postoperative thoracic computed tomography scans of patients diagnosed with lung cancer between January 2022 and December 2025 who underwent robotic lobectomy or segmentectomy were analyzed using Synapse 3D software. Resected, remaining, expected, and measured lung volumes were calculated. Differences between predicted and measured values were analyzed using the independent-samples t test or the Mann-Whitney U test, depending on the data distribution.

Results: A total of 39 patients were included in the study. Lobectomy was performed in 21 patients, and segmentectomy in 18. The median resected lung volume was 360.5 mL (interquartile range [IQR]: 198-550) in the segmentectomy group and 896 mL (IQR: 599-1194) in the lobectomy group (P < .001). The difference in expected remaining lung volume percentages between the lobectomy and segmentectomy groups was statistically significant (P < .001), whereas the difference in measured postoperative remaining lung volumes was not statistically significant (P = .1).

Conclusion: This pilot study demonstrated that robotic segmentectomy may not provide the expected parenchymal preservation advantage compared with lobectomy. Further prospective multicenter studies with larger cohorts are required.