Clinical evaluation of the iterative metal artifact reduction algorithm for CT simulation in radiotherapy

Axente, Marian; Paidi, A; Eyben, Rie von; Zeng, Chuan; Bani‐Hashemi, A; Krauß, A.; Hristov, Dimitre

doi:10.1118/1.4906245

Cited by 94 publications

(106 citation statements)

References 28 publications

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“…During the reconstruction, the method smears back the inconsistent projection values into the image by utilizing the back projection operation. This results in streaking artifacts reducing the image quality 3, 4, 5. Anatomical details may be superimposed by metal artifacts and are therefore not distinguishable from each other.…”

Section: Introductionmentioning

confidence: 99%

Improvement of dose calculation in radiation therapy due to metal artifact correction using the augmented likelihood image reconstruction

Ziemann

Stille

Cremers

et al. 2018

J Applied Clin Med Phys

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BackgroundMetal artifacts caused by high‐density implants lead to incorrectly reconstructed Hounsfield units in computed tomography images. This can result in a loss of accuracy in dose calculation in radiation therapy. This study investigates the potential of the metal artifact reduction algorithms, Augmented Likelihood Image Reconstruction and linear interpolation, in improving dose calculation in the presence of metal artifacts.Materials and MethodsIn order to simulate a pelvis with a double‐sided total endoprosthesis, a polymethylmethacrylate phantom was equipped with two steel bars. Artifacts were reduced by applying the Augmented Likelihood Image Reconstruction, a linear interpolation, and a manual correction approach. Using the treatment planning system Eclipse™, identical planning target volumes for an idealized prostate as well as structures for bladder and rectum were defined in corrected and noncorrected images. Volumetric modulated arc therapy plans have been created with double arc rotations with and without avoidance sectors that mask out the prosthesis. The irradiation plans were analyzed for variations in the dose distribution and their homogeneity. Dosimetric measurements were performed using isocentric positioned ionization chambers.ResultsIrradiation plans based on images containing artifacts lead to a dose error in the isocenter of up to 8.4%. Corrections with the Augmented Likelihood Image Reconstruction reduce this dose error to 2.7%, corrections with linear interpolation to 3.2%, and manual artifact correction to 4.1%. When applying artifact correction, the dose homogeneity was slightly improved for all investigated methods. Furthermore, the calculated mean doses are higher for rectum and bladder if avoidance sectors are applied.ConclusionStreaking artifacts cause an imprecise dose calculation within irradiation plans. Using a metal artifact correction algorithm, the planning accuracy can be significantly improved. Best results were accomplished using the Augmented Likelihood Image Reconstruction algorithm.

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Section: Introductionmentioning

confidence: 99%

Improvement of dose calculation in radiation therapy due to metal artifact correction using the augmented likelihood image reconstruction

Ziemann

Stille

Cremers

et al. 2018

J Applied Clin Med Phys

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“…Image quality is potentially being reduced up to a point where a delineation of anatomical structures is no longer possible. This drastically influences the clinical examination 5, 7, 8, 9. Consequently, an accurate contouring of target structures and organs at risk is no longer guaranteed and the dose planning process is inaccurate.…”

Section: Introductionmentioning

confidence: 99%

“…One particular method of interest is the Augmented Likelihood Image Reconstruction (ALIR) that has proven to outperform current methods for clinically relevant data 15. In order to integrate such a method in the daily routine within a clinical environment, the method needs to be evaluated extensively 5, 7, 16, 17. Such evaluation should not only focus on retrieving missing anatomical information and improving image quality, but should also investigate the retrieval of correct HU values.…”

Section: Introductionmentioning

confidence: 99%

“…Such evaluation should not only focus on retrieving missing anatomical information and improving image quality, but should also investigate the retrieval of correct HU values. Studies that evaluate the performance of MAR methods such as iMAR or VME used tissue‐equivalent inserts in phantoms in order to study the HU value retrieval 7, 18. Comparisons of the MAR methods with undisturbed reference images showed that the original HU values could be approximated.…”

Section: Introductionmentioning

confidence: 99%

“…Comparisons of the MAR methods with undisturbed reference images showed that the original HU values could be approximated. In most of the cases, the noise was reduced, while in other cases, the noise was also partly increased 7, 18. Evaluation of the MAR algorithms with respect to their correction capabilities of HU values was slightly limited due to the fact that examined inserts were not alternately positioned on the position with the highest amount of distortion.…”

Section: Introductionmentioning

confidence: 99%

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The effects of metal artifact reduction on the retrieval of attenuation values

Ziemann

Stille

Cremers

et al. 2016

J Applied Clin Med Phys

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BackgroundThe quality of CT slices can be drastically reduced in the presence of high‐density objects such as metal implants within the patients’ body due to the occurrence of streaking artifacts. Consequently, a delineation of anatomical structures might not be possible, which strongly influences clinical examination.PurposeThe aim of the study is to clinically evaluate the retrieval of attenuation values and structures by the recently proposed Augmented Likelihood Image Reconstruction (ALIR) and linear interpolation in the presence of metal artifacts.Material and MethodsA commercially available phantom was equipped with two steel inserts. At a position between the metal rods, which shows severe streaking artifacts, different human tissue‐equivalent inserts are alternately mounted. Using a single‐source computer tomograph, raw data with and without metal rods are acquired for each insert. Images are reconstructed using the ALIR algorithm and a filtered back projection with and without linear interpolation. Mean and standard deviation are compared for a region of interest in the ALIR reconstructions, linear interpolation results, uncorrected images with metal rods, and the images without metal rods, which are used as a reference. Furthermore, the reconstructed shape of the inserts is analyzed by comparing different profiles of the image.ResultsThe measured mean and standard deviation values show that for all tissue classes, the metal artifacts could be reduced using the ALIR algorithm and the linear interpolation. Furthermore, the HU values for the different classes could be retrieved with errors below the standard deviation in the reference image. An evaluation of the shape of the inserts shows that the reconstructed object fits the shape of the insert accurately after metal artifact correction. Moreover, the evaluation shows a drop in the standard deviation for the ALIR reconstructed images compared to the reference images while reducing artifacts and keeping the shape of the inserts, which indicates a noise reduction ability of the ALIR algorithm.ConclusionHU values, which are distorted by metal artifacts, can be retrieved accurately with the ALIR algorithm and the linear interpolation approach. After metal artifact correction, structures, which are not perceptible in the original images due to streaking artifacts, are reconstructed correctly within the image using the ALIR algorithm. Furthermore, the ALIR produced images with a reduced noise level compared to reference images and artifact images. Linear interpolation results in a distortion of the investigated shapes and features remaining streaking artifacts.

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Monte Carlo Approach for Estimating Density and Atomic Number From Dual‐Energy Computed Tomography Images of Carbonate Rocks

2017

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We develop a new Monte Carlo‐based inversion method for estimating electron density and effective atomic number from 3‐D dual‐energy computed tomography (CT) core scans. The method accounts for uncertainties in X‐ray attenuation coefficients resulting from the polychromatic nature of X‐ray beam sources of medical and industrial scanners, in addition to delivering uncertainty estimates of inversion products. Estimation of electron density and effective atomic number from CT core scans enables direct deterministic or statistical correlations with salient rock properties for improved petrophysical evaluation; this condition is specifically important in media such as vuggy carbonates where CT resolution better captures core heterogeneity that dominates fluid flow properties. Verification tests of the inversion method performed on a set of highly heterogeneous carbonate cores yield very good agreement with in situ borehole measurements of density and photoelectric factor.

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Clinical evaluation of the iterative metal artifact reduction algorithm for CT simulation in radiotherapy

Cited by 94 publications

References 28 publications

Improvement of dose calculation in radiation therapy due to metal artifact correction using the augmented likelihood image reconstruction

Improvement of dose calculation in radiation therapy due to metal artifact correction using the augmented likelihood image reconstruction

The effects of metal artifact reduction on the retrieval of attenuation values

Monte Carlo Approach for Estimating Density and Atomic Number From Dual‐Energy Computed Tomography Images of Carbonate Rocks

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