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Purpose-To investigate the utility of consistency metrics, such as inverse consistency, in contour based deformable registration error analysis.Methods-Four images were acquired of the same phantom that has experienced varying levels of deformation. The deformations were simulated with deformable image registration. Using calculated deformation maps the inconsistencies within the algorithm were investigated. This can be done for example by calculating deformation maps both in forward and reverse directions and applying them subsequently to an image. If the algorithm is not inverse-consistent then this final image will not be the same as the original, as it should be. Other consistency tests were done for example by comparing different algorithms or by applying the deformation maps to a circular set of multiple deformations whereby the original and final images are in fact the same. The resulting composite deformation map in this case contains a combination of the errors within in those maps, because if error-free the resulting deformation map should be zero everywhere. We have termed this the generalized inverse consistency error map (Σ ⃗ (x⃗ )).Results and Conclusions-The correlation between the consistency metrics and registration error varied considerably depending on the registration algorithm and type of consistency metric. There was also a trend for the actual registration error to be larger than the consistency metrics. A disadvantage of these techniques is that good performance in these consistency checks is a necessary but not sufficient condition for an accurate deformation method.

. (2012). On the dosimetric effect and reduction of inverse consistency and transitivity errors in deformable image registration for dose accumulation. Medical Physics, 39 (1), 272-280. On the dosimetric effect and reduction of inverse consistency and transitivity errors in deformable image registration for dose accumulation AbstractPurpose: Deformable image registration (DIR) is necessary for accurate dose accumulation between multiple radiotherapy image sets. DIR algorithms can suffer from inverse and transitivity inconsistencies. When using deformation vector fields (DVFs) that exhibit inverse-inconsistency and are nontransitive, dose accumulation on a given image set via different image pathways will lead to different accumulated doses. The purpose of this study was to investigate the dosimetric effect of and propose a postprocessing solution to reduce inverse consistency and transitivity errors. Methods: Four MVCT images and four phases of a lung 4DCT, each with an associated calculated dose, were selected for analysis. DVFs between all four images in each data set were created using the Fast Symmetric Demons algorithm. Dose was accumulated on the fourth image in each set using DIR via two different image pathways. The two accumulated doses on the fourth image were compared. The inverse consistency and transitivity errors in the DVFs were then reduced. The dose accumulation was repeated using the processed DVFs, the results of which were compared with the accumulated dose from the original DVFs. To evaluate the influence of the postprocessing technique on DVF accuracy, the original and processed DVF accuracy was evaluated on the lung 4DCT data on which anatomical landmarks had been identified by an expert. Results: Dose accumulation to the same image via different image pathways resulted in two different accumulated dose results. After the inverse consistency errors were reduced, the difference between the accumulated doses diminished. The difference was further reduced after reducing the transitivity errors. The postprocessing technique had minimal effect on the accuracy of the DVF for the lung 4DCT images. Conclusions: This study shows that inverse consistency and transitivity errors in DIR have a significant dosimetric effect in dose accumulation; Depending on the image pathway taken to accumulate the dose, different results may be obtained. A postprocessing technique that reduces inverse consistency and transitivity error is presented, which allows for consistent dose accumulation regardless of the image pathway followed. Purpose: Deformable image registration (DIR) is necessary for accurate dose accumulation between multiple radiotherapy image sets. DIR algorithms can suffer from inverse and transitivity inconsistencies. When using deformation vector fields (DVFs) that exhibit inverse-inconsistency and are nontransitive, dose accumulation on a given image set via different image pathways will lead to different accumulated doses. The purpose of this study was to investigate the dosimetric effect of a...

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Radiobiological models suggest that if there is a non-uniform distribution of microscopic brain metastases in patients with small cell lung cancer, higher population-based metastasis-free rates might be achievable with non-uniform irradiation compared with the same integral whole-brain dose delivered as a uniform prescription.