Variability in commercially available deformable image registration: A multi‐institution analysis using virtual head and neck phantoms. Issue 5 (30th March 2021)

• Record Type: Journal Article
• Authors: Kubli, Alex; Pukala, Jason; Shah, Amish P.; Kelly, Patrick; Langen, Katja M.; Bova, Frank J.; Mañon, Rafael R.; Meeks, Sanford L.
• Is Part Of: Journal of applied clinical medical physics. Volume 22:Issue 5(2021)
• Page Start: 89
• Page End: 96
• Publication Date: 2021-03-30
• Subjects: deformable -- error -- image -- registration -- virtual phantoms; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.13242
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Purpose: The purpose of this study was to evaluate the performance of three common deformable image registration (DIR) packages across algorithms and institutions. Methods and Materials: The Deformable Image Registration Evaluation Project (DIREP) provides ten virtual phantoms derived from computed tomography (CT) datasets of head‐and‐neck cancer patients over a single treatment course. Using the DIREP phantoms, DIR results from 35 institutions were submitted using either Velocity, MIM, or Eclipse. Submitted deformation vector fields (DVFs) were compared to ground‐truth DVFs to calculate target registration error (TRE) for six regions of interest (ROIs). Statistical analysis was performed to determine the variability between each DIR software package and the variability of users within each algorithm. Results: Overall mean TRE was 2.04 ± 0.35 mm for Velocity, 1.10 ± 0.29 mm for MIM, and 2.35 ± 0.15 mm for Eclipse. The MIM mean TRE was significantly different than both Velocity and Eclipse for all ROIs. Velocity and Eclipse mean TREs were not significantly different except for when evaluating the registration of the cord or mandible. Significant differences between institutions were found for the MIM and Velocity platforms. However, these differences could be explained by variations in Velocity DIR parameters and MIM software versions. Conclusions: Average TRE was shown to be <3 mm for all three software platforms. However, maximum errors could be larger than 2 cm indicating that care should be exercised when using DIR. While MIM performed statistically better than the other packages, all evaluated algorithms had an average TRE better than the largest voxel dimension. For the phantoms studied here, significant differences between algorithm users were minimal suggesting that the algorithm used may have more impact on DIR accuracy than the particular registration technique employed. A significant difference in TRE was discovered between MIM versions showing that DIR QA should be performed after software upgrades as recommended by TG‐132.