Junko Tokuno1, Toyofumi F Chen-Yoshikawa2, Megumi Nakao3, Tetsuya Matsuda3, Hiroshi Date1. 1. Department of Thoracic Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan. 2. Department of Thoracic Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan. Electronic address: fengshic@kuhp.kyoto-u.ac.jp. 3. Graduate School of Informatics, Kyoto University, Kyoto, Japan.
Abstract
OBJECTIVE: Use of 3-dimensional computed tomography for preoperative and intraoperative simulation has been introduced in the field of thoracic surgery. However, 3-dimensional computed tomography provides only static simulation, which is a significant limitation of surgical simulation. Dynamic simulation, reflecting the intraoperative deformation of the lung, has not been developed. The aim of this study was to develop a novel simulation system that generates dynamic images based on patient-specific computed tomography data. METHODS: We developed an original software, the Resection Process Map, for anatomic pulmonary resection. The Resection Process Map semi-automatically generates virtual dynamic images based on patient-specific computed tomography data. We retrospectively evaluated its accuracy in 18 representative cases by comparing the virtual dynamic images with the actual surgical images. RESULTS: In this study, 9 patients who underwent lobectomy and 9 patients who underwent segmentectomy were included. For each case, a virtual dynamic image was successfully generated semi-automatically by the Resection Process Map. The Resection Process Map accurately delineated 98.6% of vessel branches and all the bronchi. The median time required to obtain the images was 121.3 seconds. CONCLUSIONS: We successfully developed a novel dynamic simulation system, the Resection Process Map, for anatomic pulmonary resection.
OBJECTIVE: Use of 3-dimensional computed tomography for preoperative and intraoperative simulation has been introduced in the field of thoracic surgery. However, 3-dimensional computed tomography provides only static simulation, which is a significant limitation of surgical simulation. Dynamic simulation, reflecting the intraoperative deformation of the lung, has not been developed. The aim of this study was to develop a novel simulation system that generates dynamic images based on patient-specific computed tomography data. METHODS: We developed an original software, the Resection Process Map, for anatomic pulmonary resection. The Resection Process Map semi-automatically generates virtual dynamic images based on patient-specific computed tomography data. We retrospectively evaluated its accuracy in 18 representative cases by comparing the virtual dynamic images with the actual surgical images. RESULTS: In this study, 9 patients who underwent lobectomy and 9 patients who underwent segmentectomy were included. For each case, a virtual dynamic image was successfully generated semi-automatically by the Resection Process Map. The Resection Process Map accurately delineated 98.6% of vessel branches and all the bronchi. The median time required to obtain the images was 121.3 seconds. CONCLUSIONS: We successfully developed a novel dynamic simulation system, the Resection Process Map, for anatomic pulmonary resection.