title: A multiple-image-based method to evaluate the performance of deformable image registration in the pelvis.
abstract: Deformable image registration (DIR) is essential for adaptive radiotherapy (RT) for tumor sites subject to motion, changes in tumor volume, as well as changes in patient normal anatomy due to weight loss. Several methods have been published to evaluate DIR-related uncertainties but they are not widely adopted. The aim of this study was, therefore, to evaluate intra-patient DIR for two highly deformable organs-the bladder and the rectum-in prostate cancer RT using a quantitative metric based on multiple image registration, the distance discordance metric (DDM). Voxel-by-voxel DIR uncertainties of the bladder and rectum were evaluated using DDM on weekly CT scans of 38 subjects previously treated with RT for prostate cancer (six scans/subject). The DDM was obtained from group-wise B-spline registration of each patient's collection of repeat CT scans. For each structure, registration uncertainties were derived from DDM-related metrics. In addition, five other quantitative measures, including inverse consistency error (ICE), transitivity error (TE), Dice similarity (DSC) and volume ratios between corresponding structures from pre- and post- registered images were computed and compared with the DDM. The DDM varied across subjects and structures; DDMmean of the bladder ranged from 2 to 13 mm and from 1 to 11 mm for the rectum. There was a high correlation between DDMmean of the bladder and the rectum (Pearson's correlation coefficient, R p  =  0.62). The correlation between DDMmean and the volume ratios post-DIR was stronger (R p  =  0.51; 0.68) than the correlation with the TE (bladder: R p  =  0.46; rectum: R p  =  0.47), or the ICE (bladder: R p  =  0.34; rectum: R p  =  0.37). There was a negative correlation between DSC and DDMmean of both the bladder (R p  =  -0.23) and the rectum (R p  =  -0.63). The DDM uncertainty metric indicated considerable DIR variability across subjects and structures. Our results show a stronger correlation with volume ratios and with the DSC using DDM compared to using ICE and TE. The DDM has the potential to quantitatively identify regions of large DIR uncertainties and consequently identify anatomical/scan outliers. The DDM can, thus, be applied to improve the adaptive RT process for tumor sites subject to motion.
authors.affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave., New York, NY 10065, USA.
authors.forename: Ziad
authors.initials: Z
authors.lastname: Saleh
authors.forename: Maria
authors.initials: M
authors.lastname: Thor
authors.forename: Aditya P
authors.initials: AP
authors.lastname: Apte
authors.forename: Gregory
authors.initials: G
authors.lastname: Sharp
authors.forename: Xiaoli
authors.initials: X
authors.lastname: Tang
authors.forename: Harini
authors.initials: H
authors.lastname: Veeraraghavan
authors.forename: Ludvig
authors.initials: L
authors.lastname: Muren
authors.forename: Joseph
authors.initials: J
authors.lastname: Deasy
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D010388:Pelvis / Q000000981:diagnostic imaging*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D012007:Rectum / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*; D035501:Uncertainty; D001743:Urinary Bladder / Q000000981:diagnostic imaging