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, Rp = 0.62). The correlation between DDMmean and the volume ratios post-DIR was stronger (Rp = 0.51; 0.68) than the correlation with the TE (bladder: Rp = 0.46; rectum: Rp = 0.47), or the ICE (bladder: Rp = 0.34; rectum: Rp = 0.37). There was a negative correlation between DSC and DDMmean of both the bladder (Rp = −0.23) and the rectum (Rp = −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.
Highlights
Deformable image registration (DIR) is essential to ensure accurate delivery of radiotherapy (RT) for tumor sites subject to considerable motion, changes in tumor volume and normal anatomy due to patient’s weight loss [1,2]
The most commonly used metrics to evaluate the performance of DIR involve the Dice Similarity Coefficient (DSC), the Hausdorff distance, and the mean surface distance, or by identification of landmarks [17,18,19,22]
In our previous study we introduced the multiple-image-based distance discordance metric (DDM), and showed that the DDM was more strongly correlated with the absolute registration error than inverse consistency error (ICE) and transitivity error (TE) when DIR was performed on a digital phantom [28]
Summary
Deformable image registration (DIR) is essential to ensure accurate delivery of radiotherapy (RT) for tumor sites subject to considerable motion, changes in tumor volume and normal anatomy due to patient’s weight loss [1,2]. The most commonly used metrics to evaluate the performance of DIR involve the Dice Similarity Coefficient (DSC), the Hausdorff distance, and the mean surface distance, or by identification of landmarks [17,18,19,22]. The former three metrics typically rely on the availability of manually delineated structures [14,17], and the landmark technique is limited in regions of soft tissue where robust identification of landmarks is challenging [19,20,21]. On the other hand, can only provide information about tissue expansion and shrinkage without conveying any information about DIR uncertainties
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