Evaluation of the tool “Reg Refine” for user‐guided deformable image registration

Abstract

“Reg Refine” is a tool available in the MIM Maestro v6.4.5 platform (www.mimsoftware.com) that allows the user to actively participate in the deformable image registration process. The purpose of this work was to evaluate the efficacy of this tool and investigate strategies for how to apply it effectively. This was done by performing DIR on two publicly available ground‐truth models, the Pixel‐based Breathing Thorax Model (POPI) for lung, and the Deformable Image Registration Evaluation Project (DIREP) for head and neck. Image noise matched in both magnitude and texture to clinical CBCT scans was also added to each model to simulate the use case of CBCT–CT alignment. For lung, the results showed Reg Refine effective at improving registration accuracy when controlled by an expert user within the context of large lung deformation. CBCT noise was also shown to have no effect on DIR performance while using the MIM algorithm for this site. For head and neck, the results showed CBCT noise to have a large effect on the accuracy of registration, specifically for low‐contrast structures such as the brainstem and parotid glands. In these cases, the Reg Refine tool was able to improve the registration accuracy when controlled by an expert user. Several strategies for how to achieve these results have been outlined to assist other users and provide feedback for developers of similar tools.PACS number(s): 87.44.Qr, 87.57.nj, 87.57.c

A novel concept to include uncertainties in the evaluation of stereotactic body radiation therapy after 4D dose accumulation using deformable image registration

“…To ensure homogeneity among cases, all the registrations in this work were done by the same person, a radiation oncologist with expertise in lung SBRT. The effectiveness of the RegReveal and RegRefine tools in the lung has been shown by Johnson et al…”

Mitigating differential baseline shifts in locally advanced lung cancer patients using an average anatomy model

“…Johnson et al used a tool called Reg Refine, available with MIM. This allows visual assessment and user guidance of DIR and, improves the registration accuracy when controlled by expert users …”

“…This allows visual assessment and user guidance of DIR and, improves the registration accuracy when controlled by expert users. 37 Elstrom et al and Lawson et al used deformable registration to deform the pCT to certain CBCT scans in order to warp the dose and be able to assess the dosimetric effect. 38,39 In this manuscript, we have used a similar registration technique to obtain an improved model of the patient anatomy during treatment.…”

A multiparametric method to assess the MIM deformable image registration algorithm

“…This approach is convenient but presents some limitations due to phantom unavailability for all the tasks to be tested and from the lack of a ground truth transformation. On the contrary, synthetic or digital phantoms, created by applying displacement vector fields to deform patient images, offer the possibility to perform a quantitative comparison between the ground truth and the algorithm‐created displacement vector fields . This approach is interesting even if realistic deformations are quite difficult to be implemented in large regions.…”

“…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.)…”