ESTRO 2021 Abstract Book

S323

ESTRO 2021

the same-day repeats. However most tests had larger monthly than repeatability SDs. All tests appeared stable over the 6 months, with no trends observed and monthly means agreeing with repeatability means within two SDs (except for two which agreed within 4 SD). Conclusion Tests for a QA programme for radiotherapy planning PET-MR have been developed. The tests appeared repeatable and stable over a six-month period, although monthly variation was larger than test repeatability for most tests. Future work will use this data to derive appropriate tolerance levels, forming a QA programme and so enabling high-quality, robust PET-MR imaging to be used for radiotherapy planning. OC-0424 Robust quality assurance criteria for deformable image registration for adaptive radiotherapy L. Bosma 1 , C. Zachiu 1 , B. Denis de Senneville 2 , B. Raaymakers 1 , M. Ries 3 1 UMC Utrecht, Radiotherapy, Utrecht, The Netherlands; 2 University of Bordeaux, Institut de Mathématiques de Bordeaux, Bordeaux, France; 3 UMC Utrecht, Imaging division, Utrecht, The Netherlands Purpose or Objective Plan adaption and accurate dose accumulation in state-of-the-art radiotherapy, in particular in thorax and abdomen, rely increasingly on deformable image registration (DIR). As a consequence, clinical work-flows encompassing DIR necessitate a reliable and fast quality assurance (QA) that enable on-the-fly go/no-go decisions to proceed. The disadvantage of established QA criteria such as the Dice similarity coefficient (DSC) or Hausdorff distance (HDD) for this purpose is thereby that both do not allow complete “hands-free” operation and also frequently display a limited sensitivity with respect to registration errors in soft tissues. Here, we investigate the structural-similarity index (SSI) as an alternative QA criterion, with respect to robustness, specificity and sensitivity for the decision-making process. As the SSI does not need operator input, it also enables fully automated QA for DIR during adaptive procedures with repeated imaging. Materials and Methods We have investigated the correlations between a set of QA criteria (including the DSC, the HDD, the mean HDD, the Jaccard index, and the SSI) and the endpoint error of known deformations as the gold standard. All criteria are extensively evaluated using (I) synthetic deformations of 3D MRI prostate patient data sets (3D bTFE with fat suppression) of different amplitudes, (II) simulated biomechanical abdominal and thoracic deformations based on finite-element simulations, and (III) annotated 4D patient data. We furthermore evaluated the QA performance for different DIR algorithms on images of multiple resolutions and signal-to- noise-ratios. The quality assurance criteria are scored in terms of the Pearson correlation coefficient, a linear regression analysis, and a receiving operator characteristic (ROC) where the median endpoint error is used as the cutoff value for decision making. Results As shown in table 1, compared to established criteria we find that the SSI has both a higher Pearson correlation coefficient and a higher R 2 for linear regression. As shown in figure 1, this leads in turn to a larger area under the curve for the ROC. The ROC-curve shows that the SSI is both more sensitive as well as more specific to detect misregistrations, which is essential for decision making on DIR in clinical radiotherapy work- flows.