Virtual segmentectomy based on high-quality three-dimensional lung modelling from computed tomography images.

Objectives: The aim of this study was to demonstrate the feasibility and efficacy of a novel simulation software called, virtual segmentectomy.
Methods: We developed the segmentectomy simulation system, which was programmed to analyse the detailed 3D bronchovascular structure and to predict the appropriate segmental surface and surgical margin, based on lung modelling from CT images.
Results: We have attempted this novel technique for 3 cases of pulmonary metastases and 1 case of multiple lung cancer. For validation, the predicted resection margin was compared with the actual resected specimen. The surgical surface, as estimated by the simulation, was compared with the surface of the specimen and a surgical video. To test its feasibility, the operation time, blood loss, durations of chest tube placement and hospitalization as well as pathological findings were assessed.
Conclusions: Preoperative simulation and intraoperative guidance by virtual segmentectomy could contribute significantly to determining the most appropriate anatomical segmentectomy and curative resection.