Image registration accuracy of GammaPlan: a phantom study

Abstract

Object The authors evaluated the accuracy of the automatic image coregistration function implemented in the Leksell GammaPlan treatment planning software (Version 4C with MultiView Extension and Version 8.0). Methods The authors used a phantom with 9 landmarks (tips of thin cylindrical acrylic rods) evenly distributed in the treatment space. Two sets of images of the phantom were taken with both CT and MR imaging systems. The first image was obtained with the phantom aligned with the scanner's axis and the second scan was made by intentionally shifting and rotating the phantom relative to the scanner's axis. The authors attempted image registration of 2 CT image sets, CT and MR image sets, and 2 MR image sets. The accuracy of image registration was evaluated by measuring the x, y, and z coordinate values of the landmarks on each image set after 2 image sets were coregistered. The authors calculated the differences of the x, y, and z values and the distance, d, between corresponding landmarks in 2 image sets. To minimize interobserver dependence of coordinate measurements, 2 physicists did measurements independently. Results The distances, d, averaged over the 9 landmarks, were 2.63 ± 1.64 and 0.95 ± 0.25 mm for CT–CT and MR–MR image registrations, respectively. When the CT images of the air-filled phantom and MR images were coregistered, however, the algorithm performed poorly: d = 13.8 ± 1.23 mm. To remedy this, the authors undertook a 2-step process by first performing landmark-based registration of the 2 image sets and subsequently applying the automatic registration. With this approach, the mean distance drastically improved: d = 0.74 ± 0.31 mm. When the water-filled phantom was used for CT scans, the registration accuracy of CT and MR image sets was acceptable without the 2-step registration process: d = 1.18 ± 0.36 mm. Conclusions The accuracy of automatic registration of image sets from the same modality was within the voxel size of the scanned images. The accuracy of CT–MR image registration strongly depended on whether the phantom for CT scans was filled with air or water. This indicates the significant effect of the amount of common data available for a mutual information-based algorithm on the accuracy.