A multiparametric method to assess the MIM deformable image registration algorithm.

Silvia Calusi,Livia Marrazzo,Pierluigi Bonomo,Stefania Pallotta,Lorenzo Livi,Marta Casati,Isacco Desideri,Linhsia Noferini,Franco Fusi,Margherita Zani,Giusy Labanca,Cinzia Talamonti

doi:10.1002/acm2.12564

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.

Highlights

In the last few years deformable image registration (DIR) algorithms have become necessary tools in adaptive radiation therapy (ART)treatments
We propose a multiparametric validation of the MIM‐Maestro DIR algorithm and Reg Refine tool (MIM Software, Cleveland, OH) considering some typical deformations that might appear in computed tomography (CT) studies during the course of head and neck radiotherapy treatments
For the variable contrast test dice similarity coefficient (DSC) values for the three spheres of Phantom 1 between CT(0°) and R3 are reported in the same table

Summary

Introduction

In the last few years deformable image registration (DIR) algorithms have become necessary tools in adaptive radiation therapy (ART)treatments. Different approaches have been followed to perform such validation, involving the use of deformable phantoms, digital phantoms, and clinical patient data. When patient data are used, DIR performances are usually assessed comparing anatomical marker positions[14,15,16,17,18] 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

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Conclusion