Patient setup error measurement using 3D intensity-based image registration techniques.

Abstract

PURPOSE: Conformal radiotherapy requires accurate patient positioning with reference to the initial three-dimensional (3D) CT image. Patient setup is controlled by comparison with portal images acquired immediately before patient treatment. Several automatic methods have been proposed, generally based on segmentation procedures. However, portal images are of very low contrast, leading to segmentation inaccuracies. In this study, we propose an intensity-based (with no segmentation), fully automatic, 3D method, associating two portal images and a 3D CT scan to estimate patient setup. MATERIALS AND METHODS: Images of an anthropomorphic phantom were used. A CT scan of the pelvic area was first acquired, then the phantom was installed in seven positions. The process is a 3D optimization of a similarity measure in the space of rigid transformations. To avoid time-consuming digitally reconstructed radiograph generation at each iteration, we used two-dimensional transformations and two sets of specific and pregenerated digitally reconstructed radiographs. We also propose a technique for computing intensity-based similarity measures between several couples of images. A correlation coefficient, chi-square, mutual information, and correlation ratio were used. RESULTS: The best results were obtained with the correlation ratio. The median root mean square error was 2.0 mm for the seven positions tested and was, respectively, 3.6, 4.4, and 5.1 for correlation coefficient, chi-square, and mutual information. CONCLUSIONS: Full 3D analysis of setup errors is feasible without any segmentation step. It is fast and accurate and could therefore be used before each treatment session. The method presents three main advantages for clinical implementation-it is fully automatic, applicable to all tumor sites, and requires no additional device.