Comparison of different QA methods for deformable image registration to the known errors for prostate and head-and-neck virtual phantoms

Contour comparison, landmark tracking, and image similarity are methods that canbeused to perform a patient-specific evaluation for the accuracy of deformable image registration (DIR), but they are not necessarilyatrue measurement of DIR accuracy. The purpose of this work isto evaluate how the calculated errors from these methods compare tothe known errors for prostate and headand-neck virtual phantoms. These DIR accuracy methods were utilizedto evaluate the performance of two DIR software packages, MIM and Velocity. For Velocity, three different settings of the algorithm were utilized: deformable (DEF),deformable multi-pass (DMP), and extended deformable multi-pass (XMP). For contour comparison, organs were contoured onboth the non-deformed and deformed images. Then, the DIR algorithms were used totransfer contours from the non-deformed tothe deformed image and comparedto that drawn directlyonthe deformed image.In the landmark tracking method, visible landmark motion was measured and compared tothat predicted by the algorithms. For image similarity, the root-mean-square and the mean-absolute differences were calculated between the warped and non-deformed images. In addition, the actual spatial registration error was calculated for each DIR algorithm from the known ground-truth deformationofthe virtual phantoms. The MIM algorithm produced the lowest average errors for the landmark analysis, the closest image similarity, and overall the most accurate contour transfers. When compared to the known deformations, MIM produced the lowest average error, but also the largest errors. Noneofthe QA methods gave any indication of this large maximum error. Beyond this, the sizes of errors from the QA methods were not always the same as the actual errors from the virtual phantom. For this reason, thereis a benefit tosupplementing the QA methods with virtual phantom studies.