A Comparative Evaluation of 3 Different Free-Form Deformable Image Registration and Contour Propagation Methods for Head and Neck MRI: The Case of Parotid Changes During Radiotherapy

Abstract

Purpose:To validate and compare the deformable image registration and parotid contour propagation process for head and neck magnetic resonance imaging in patients treated with radiotherapy using 3 different approaches—the commercial MIM, the open-source Elastix software, and an optimized version of it.Materials and Methods:Twelve patients with head and neck cancer previously treated with radiotherapy were considered. Deformable image registration and parotid contour propagation were evaluated by considering the magnetic resonance images acquired before and after the end of the treatment. Deformable image registration, based on free-form deformation method, and contour propagation available on MIM were compared to Elastix. Two different contour propagation approaches were implemented for Elastix software, a conventional one (DIR_Trx) and an optimized homemade version, based on mesh deformation (DIR_Mesh). The accuracy of these 3 approaches was estimated by comparing propagated to manual contours in terms of average symmetric distance, maximum symmetric distance, Dice similarity coefficient, sensitivity, and inclusiveness.Results:A good agreement was generally found between the manual contours and the propagated ones, without differences among the 3 methods; in few critical cases with complex deformations, DIR_Mesh proved to be more accurate, having the lowest values of average symmetric distance and maximum symmetric distance and the highest value of Dice similarity coefficient, although nonsignificant. The average propagation errors with respect to the reference contours are lower than the voxel diagonal (2 mm), and Dice similarity coefficient is around 0.8 for all 3 methods.Conclusion:The 3 free-form deformation approaches were not significantly different in terms of deformable image registration accuracy and can be safely adopted for the registration and parotid contour propagation during radiotherapy on magnetic resonance imaging. More optimized approaches (as DIR_Mesh) could be preferable for critical deformations.

T2w‐MRI signal normalization affects radiomics features reproducibility

“…A more detailed description of the image registration and contour propagation procedure can be found in previous works. 23,28…”

A multiparametric method to assess the MIM deformable image registration algorithm

“…During the optimization process, the image similarity has a higher weight compared to the physical likelihood, with the risk of producing unrealistic transformations . If the DIR results are not satisfactory, the user can refine the alignment using the Reg Refine tool . In this case, boxes of adjustable dimensions are manually positioned in those regions where the alignment is not adequate and inside these boxes local rigid registrations are performed.…”

“…This approach is interesting even if realistic deformations are quite difficult to be implemented in large regions. Finally, when patient data are used, DIR performances are usually assessed comparing anatomical marker positions in deformed and original images. Even if these tests offer useful clinical information, they are inadequate to fully describe algorithm behavior and to point out its limits.…”

“…A lot of different deformable algorithms have been developed in the last years and several studies have been proposed to highlight their strengths and weaknesses or to compare the performances of different algorithms. Several papers have been published on MIM DIR algorithm performances, mostly comparing MIM results with those obtained using other algorithms . The impact of image characteristics (as contrast levels, noise, deformation etc.)…”

“Patient‐specific validation of deformable image registration in radiation therapy: Overview and caveats”

“…[51], and their values need to be in the order of 0.80-0.90 and 2-3 mm (voxel dimension) for overlap and distance measures, respectively. Contour propagation and its validation with respect to ground truth contours have been largely adopted in both mono-modal and multi-modal imaging of different anatomical sites, with prevalence in head & neck, 22,32,[59][60][61][62][63][64] thoraco-abdominal regions 14,[17][18][19]31,34,[65][66][67][68][69] and pelvis. 21,66,67,70,71 Specifically for multi-modal imaging, contour-based metrics are the most used methods for DIR evaluation, since they can provide an easy solution for the definition of corresponding anatomical (and functional) information.…”