A multiparametric method to assess the MIM deformable image registration algorithm

Abstract

A quantitative evaluation of the performances of the deformable image registration (DIR) algorithm implemented in MIM‐Maestro was performed using multiple similarity indices. Two phantoms, capable of mimicking different anatomical bending and tumor shrinking were built and computed tomography (CT) studies were acquired after applying different deformations. Three different contrast levels between internal structures were artificially created modifying the original CT values of one dataset. DIR algorithm was applied between datasets with increasing deformations and different contrast levels and manually refined with the Reg Refine tool. DIR algorithm ability in reproducing positions, volumes, and shapes of deformed structures was evaluated using similarity indices such as: landmark distances, Dice coefficients, Hausdorff distances, and maximum diameter differences between segmented structures. Similarity indices values worsen with increasing bending and volume difference between reference and target image sets. Registrations between images with low contrast (40 HU) obtain scores lower than those between images with high contrast (970 HU). The use of Reg Refine tool leads generally to an improvement of similarity parameters values, but the advantage is generally less evident for images with low contrast or when structures with large volume differences are involved. The dependence of DIR algorithm on image deformation extent and different contrast levels is well characterized through the combined use of multiple similarity indices.

Evaluation of Intensity- and Contour-Based Deformable Image Registration Accuracy in Pancreatic Cancer Patients

“…In this study, we applied cDIR and hDIR to several contours (CTV, GTV, stomach, and duodenum) simultaneously; however, it is possible that accuracy would increase if each contour were used individually. Manual user configurations, such as Reg refine [18,19], or other new methods, are necessary to increase the accuracy of DIR, because the accuracy appears to be limited, even when cDIR and hDIR methods are used.…”

Development of an automated radiotherapy dose accumulation workflow for locally advanced high‐risk prostate cancer – A technical report

“…MIM v.6.9 (MIMVista Corp., Cleveland OH) was used to develop the workflow. MIM DIR is an intensity‐based free‐form deformable algorithm that utilises the sum of squared difference between voxel HU values (per voxel), which seeks to minimise intensity differences between two images for image registration 46 . This was a sequential treatment regimen whereby a dose of 46–54 Gy in 23‐27 fractions was prescribed to the prostate, seminal vesicles (SVs) and pelvic lymph nodes (PLNs) in Phase 1 (P1).…”

Application of an automated dose accumulation workflow in high-risk prostate cancer - validation and dose-volume analysis between planned and delivered dose

“…14 , 15 A customized dose accumulation and contour propagation workflow was developed using MIM and was operated in MIM Assistant's interface for automation of data transfer and workflow management. 16 Details of the workflow construction and CBCT contour preparation have been reported 8 , and can be referred to in the supplementary material A.…”