TU-H-CAMPUS-JeP1-03: Results From a Multi Institution Study On Image Quality Impact in Deformable Image Registration

Purpose: Various commercial algorithms for deformable image registration (DIR) were tested to investigate their accuracy and robustness, against image noise and artifacts. Methods: Ten institutions with five available commercial solutions provided data to assess the agreement of DIR-propagated ROIs with automatically drawn ROIs considered as ground-truth for the comparison. The DIR algorithms were tested on real patient data (pelvis). A Deformation was applied to the reference data set (CTref) using the ImSimQA software, a (CTeval) and seven CBCT images with increasing level of noise and capping artifacts were simulated. Every center performed DIR between CTref, and the deformed datasets. The noise was defined as standard deviation normalized to signal in an homogeneous medium, artefacts as the difference of mean HU values between the central and peripheral region of an homogeneous medium. To investigate the relationship between image quality parameters and the DIR results a three way ANOVA was performed on logit function of DICE index. Results: Based on 480 DIR-mapped ROIs the ANOVA test states that centers, ROIs and Image Quality are significant predictors of DIR performances. DIR conducted on CBCT simulated images is significant worst of the ones obtained on the original images. Increasing noise and artefacts didn't affect significantly DIR performances. Considering a limit for Dice Index of 0.75 one center underperform this level. DIR resulted significantly more accurate in rectal contours propagation. Conclusion: This work illustrates the effect of image noise to DIR performances in a ground truth provided scenario. Clinical issues like ART or Dose Accumulation need accurate and robust DIR software using CBCT images. For the range of artefacts and noise explored in this experiment the commercial software appeared to be robust. One centre didn't satisfy the minimum accuracy requirement showing that QA is mandatory to implement clinically DIR for ROI propagation.