WCLC 2025 - Posters & ePosters-P1.07.09 Real-World Efficacy of an AI-Driven 3D Reconstruction System on Pulmonary Surgery

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This study retrospectively evaluated the real-world clinical efficacy of an AI-driven 3D reconstruction system in pulmonary surgery, specifically focusing on lobectomy and segmentectomy procedures. Conducted at Peking University People’s Hospital, the research included consecutive patients initially scheduled for lobectomy or segmentectomy and assessed intraoperative procedural modifications, perioperative outcomes, and surgical costs.<br /><br />Key findings indicated that the AI-driven 3D reconstruction system was used in 17.9% of lobectomies (186/1038) and 58.6% of segmentectomies (342/584). Among patients planned for segmentectomy, those in the AI group had significantly fewer intraoperative procedural modifications (6.1% vs. 20.7% in the control group; P=0.001). For patients initially scheduled for lobectomy, conversion to segmentectomy occurred more frequently with AI-assisted planning (3.8% vs. 0.9%; P=0.01). Importantly, when surgeries were performed as initially planned without modifications, perioperative outcomes were comparable between AI and control groups. Moreover, the AI group demonstrated significantly reduced overall surgical costs.<br /><br />The study underscores that AI-driven 3D reconstruction enhances surgical precision and planning, reducing the need for intraoperative procedural changes, particularly in segmentectomies, without compromising perioperative outcomes. Additionally, it may lower the overall cost burden associated with pulmonary surgeries.<br /><br />Future research directions include validating these findings across diverse clinical settings and conducting prospective studies to further confirm the benefits of AI-driven 3D reconstruction in thoracic surgery. Previous studies have highlighted the technology’s accuracy in anatomical variant identification, and this work supports its practical advantages in routine clinical use.<br /><br />In conclusion, implementing the AI-driven 3D reconstruction system in pulmonary surgery appears to improve procedural planning and efficiency, reduce costs, and maintain patient outcomes, marking a significant advancement in thoracic surgical practice.

Asset Subtitle

Jiayi Geng

Meta Tag

Speaker Jiayi Geng

Topic Early-Stage Non-small Cell Lung Cancer

Keywords

AI-driven 3D reconstruction

pulmonary surgery

lobectomy

segmentectomy

intraoperative procedural modifications

perioperative outcomes

surgical costs

thoracic surgery

clinical efficacy

surgical planning