Ventilation imaging can be performed using thoracic four dimensional computed tomography (4D-CT) images (max inhale phase and max exhale phase) and deformable image registration (DIR). If this method was administered in multi institution, some institution would use commercially available automatic DIR software. But, there are not many reports about commercially available automatic DIR. In this study, we evaluated the accuracy of a commercially available automatic deformable image registration (DIR) algorithm using 4D-CT images. For evaluating the accuracy of DIR, registration error was calculated by difference between manual displacement and automatic calculated displacement (DIR outputs). A B-spline DIR algorithm implemented in a Velocity AI ver. 2.7.0 software (Velocity Medial, GA, USA) was evaluated. 4D-CT images including 300 landmarks /case, throughout the lung, provided by DIR-lab (www.dir-lab.com). In this study, five patients were studied. The goal of DIR was to find a point to point correspondence between inhale image and exhale image. First, manual displacement was calculated by land mark points between max inhale phase and max exhale phase. Next, DIR outputs were calculated by a Velocity AI. After that, registration error was calculated by difference between manual displacement and DIR outputs. The mean 3D registration error (standard deviation) for the five cases was 2.70 (2.24) mm. Fewer large errors were seen, but the frequent histogram had a peak at 1.5mm of 3D error, and the frequencies decline as one moves away from the peak. The average 3D registration errors for case1 were 0.94 mm for 1.5 mm motion distance magnitude, 1.96 mm for 6.0 mm and 3.70 mm for 9.0 mm, respectively. Our result clearly shows that the accuracy of DIR in Velocity AI was within 3.0 mm. Therefore commercially available automatic DIR may be useful for image-guided radiation therapy, adaptive radiation therapy and ventilation imaging.