Image Guidance Sub-lobar Pulmonary Resection Using Machine Learning 3-Dimensional Reconstruction

B. Son¹, H. Kim², J. Son^1
1Pusan National University Yangsan Hospital, Yangsan, Kyongsang-namdo ²Pusan National University, Yangsan, Kyongsang-namdo

Please explain the educational or technical point that this video addresses.: This video is about robotic right upper lobe S3 segmentectomy using 3D reconstruction images. The 3D reconstruction program was not a commercial software but a program developed by the presenter's research team, carefully designed to be applied from the surgeon's perspective in the surgical field. We believe that the program we have developed provides an easier and safer approach to complex segmentectomy.

Please provide a 250 word summary of the surgical video being submitted.: After presenting LCSG 0821 and JCOG 0820, the frequency of sublobar pulmonary resection increased in early lung cancer. Segmentectomy poses challenges compared to lobectomy due to the need for securing resection margins and the complexity of sublobar anatomy. Understanding segmental veins is crucial but difficult due to their high variation.
To address these challenges, we developed a model that automatically generates 3D reconstruction images using machine learning and integrated it with the Da Vinci robot system's Tilepro function for sublobar resection. The model distinguishes the lung area, including the BRONCHUS, ARTERY, VEIN, and Nodule region, and simulates sublobar resection areas. It features a web-based interface for interactive manipulation and displays 3D images simultaneously with surgical images via TilePro, enabling intraoperative image verification.
We successfully performed surgery on a 68-year-old female patient using our 3D images with the TilePro function. Image-guided robotic sublobar resection allows intraoperative verification of sublobar structures, particularly segmental veins, reducing the learning curve for beginners. Immediate confirmation of resection margins and structures during surgery can reduce operation time and postoperative complications such as congestion in the remaining segments.