PubMed1995
PURPOSE: Portal imaging is the most important quality assurance procedure for monitoring the reproducibility of setup geometry in radiation therapy. The role of portal imaging has become even more critical in recent years due to the migration of three-dimensional (3D) treatment planning technology, including high-precision conformal therapy, from the research setting to routine clinical practice. Unfortunately, traditional methods for acquiring and interpreting portal images suffer from a number of deficiencies that contribute to the well-documented observation that many setup errors go undetected, and some persist for a clinically significant portion of the prescribed dose. Significant improvements in both accuracy and efficiency of detecting setup errors can, in principle, be achieved by using automatic image registration for on-line screening of images obtained from electronic portal imaging devices (EPIDs). METHODS AND MATERIALS: This article presents recent developments in a method called core-based image analysis that shows great promise for achieving the desired improvements in error detection. Core-based image analysis is a fundamental computer vision method that is capable of exploiting the full power of EPIDs by providing for on-line detection of setup errors via automatic registration of user-selected anatomical structures. We describe a robust method for automatic portal image registration based on core analysis and demonstrate an approach for assessing both accuracy and precision of registration methods using realistic, digitally reconstructed portal radiographs (DRPRs) where truth is known. RESULTS: Automatic core-based analysis of a set of 20 DRPRs containing known, random field positioning errors was performed for a patient undergoing treatment for prostate cancer. In all cases, the reported translation was within 1 mm of the actual translation with mean absolute errors of 0.3 mm and standard deviations of 0.3 mm. In all cases, the reported rotation was within 0.6 degree of the actual rotation with a mean absolute error of 0.18 degree and a standard deviation of 0.23 degree. CONCLUSION: Our results, using digitally reconstructed portal radiographs that closely resemble clinical portal images, suggest that automatic core-based registration is suitable as an on-line screening tool for detecting and quantifying patient setup errors.