Reduction of dental metallic artefacts in CT: Value of a newly developed algorithm for metal artefact reduction (O-MAR)

Kidoh, Masafumi; Nakaura, Takeshi; Nakamura, Shinichi; Tokuyasu, Shinichi; Osakabe, Hirokazu; Harada, Kazunori; Yamashita, Yasuyuki

doi:10.1016/j.crad.2013.08.008

Cited by 88 publications

(76 citation statements)

References 20 publications

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“…[5][6][7][8][9] In addition to monoenergetic reconstructions in DECT, dedicated MAR algorithms have become available for clinical practice in the past couple of years. MAR algorithms in both single-energy CT imaging [10][11][12][13][14] and DECT imaging 8,9 have been shown to reduce metal artefacts.…”

mentioning

confidence: 99%

Metal artefact reduction in CT imaging of hip prostheses—an evaluation of commercial techniques provided by four vendors

Andersson¹,

Nowik²,

Persliden³

et al. 2015

BJR

108

106

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Objective: The aim of this study was to evaluate commercial metal artefact reduction (MAR) techniques in X-ray CT imaging of hip prostheses. Methods: Monoenergetic reconstructions of dual-energy CT (DECT) data and several different MAR algorithms, combined with single-energy CT or DECT, were evaluated by imaging a bilateral hip prosthesis phantom. The MAR images were compared with uncorrected images based on CT number accuracy and noise in different regions of interest. Results: The three MAR algorithms studied implied a general noise reduction (up to 67%, 74% and 77%) and an improvement in CT number accuracy, both in regions close to the prostheses and between the two prostheses. The application of monoenergetic reconstruction, without any MAR algorithm, did not decrease the noise in the regions close to the prostheses to the same extent as did the MAR algorithms and even increased the noise in the region between the prostheses. Conclusion: The MAR algorithms evaluated generally improved CT number accuracy and substantially reduced the noise in the hip prostheses phantom images, both close to the prostheses and between the two prostheses. The study showed that the monoenergetic reconstructions evaluated did not sufficiently reduce the severe metal artefact caused by large orthopaedic implants. Advances in knowledge: This study evaluates several commercially available MAR techniques in CT imaging of large orthopaedic implants.Images degraded by metal artefacts are a common problem in X-ray CT imaging. Artefacts caused by the presence of metallic implants in the CT scanned volume, such as hip prostheses or dental fillings, appear as dark and bright streaks across the reconstructed image. Metal artefacts can severely degrade the image quality and hence limit the diagnostic value of a CT scan. 1 Hip prostheses cause severe artefacts when present in a CT scanned volume, and the resulting degradation of image quality leads to difficulties in diagnosing fractures, implant loosening or pathology in organs or soft tissue in the pelvic area. If CT images containing hip prostheses are used in radiotherapy treatment planning for tissue heterogeneity correction, the metal artefacts may introduce inaccuracies in dose calculations.Metal artefacts in CT imaging are mainly caused by beam hardening and photon starvation. Photon starvation artefacts are created when X-rays traverse materials with high attenuation coefficients, which leads to an insufficient amount of photons reaching the detectors and results in very noisy projections. The noise is magnified in the reconstruction process and the resulting streaks can be seen in the reconstructed image. Beam hardening refers to the fact that low-energy photons are attenuated to a greater degree than high-energy photons when passing through the scanned volume. This effect is more pronounced when the X-ray beam passes through high-density materials such as metals.

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mentioning

confidence: 99%

Metal artefact reduction in CT imaging of hip prostheses—an evaluation of commercial techniques provided by four vendors

Andersson¹,

Nowik²,

Persliden³

et al. 2015

BJR

108

106

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“…2 Examples are high-density dental implants, fiducial markers or hip prostheses. These generate metal artefact, which alters Hounsfield unit (HU) values, 3 resulting in an inaccurate dose distribution estimate. Compared with photon beam therapy, range of particle beam would be more sensitive to variation of water-equivalent path length (WEPL).…”

Section: Introductionmentioning

confidence: 99%

Single-energy metal artefact reduction with CT for carbon-ion radiation therapy treatment planning

Miki¹,

Mori²,

Hasegawa³

et al. 2016

BJR

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Objective: One approach to improving image quality of CT is to use metal artefact reduction image processing, such as single-energy metal artefact reduction (SEMAR). To quantify the impact of image correction on the quality of carbon-ion dose distribution, treatment planning using SEMAR was evaluated. Methods: Using a head phantom into which metal screws could be inserted, we acquired standard planning CT images. We calculated dose distributions using phantom images with and without metal added, and with and without SEMAR. Hounsfield unit (HU) and dose distribution variation of these images with and without SEMAR were measured using metal-free image subtraction. We similarly analysed the image data sets of two patients with head and neck cancer who had dental implants. Results: HU difference between metal-containing images and metal-free images without and with SEMAR were 279.5 6 97.2 HU and 21.4 6 19.5 HU on severe artefact area, respectively. The range of dose distribution difference from the prescribed dose between uncorrected and SEMAR-corrected images varied from 219.5% to 23.4% within planning target volume (PTV). PTV-D 95 (%) for uncorrected and SEMAR-corrected image data were 82.4% and 95.4%, respectively. For data in patients with metal dental work, PTV-D 95 (%) for uncorrected and SEMAR-corrected data were 92.2% and 92.5% (Patient 1), and 90.9% and 95.7% (Patient 2), respectively. Conclusion: SEMAR algorithm shows promise in improving CT image quality and in ensuring an accurate representation of dose distribution.

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“…30,31 In this study, we found comparable visual improvement to oMAR with our kerMAR algorithm in terms of artifact reduction, with the following potential improvement as pointed to by the blue arrows on fig. 1: Our MR based kerMAR appears to better suppress high intensity streaks close to the implants than oMAR.…”

Section: Comparison Of Kermar To Omarmentioning

confidence: 49%

“…Clinical feasibility The oMAR algorithm runs on the order of minutes per patient, 31 which is suitable for clinical use. On our system (Dell Precision M3100 Laptop, CPU: Intel Core i7-4712HQ @ 2.3GHz, RAM: 16Gb) and our largely unoptimised Python implementation, kerMAR takes around 10-30min.…”

Section: Kidoh Et Al Found Inmentioning

confidence: 99%

CT metal artifact reduction using MR image patches

Nielsen

Edmund

Leemput

2018

Medical Imaging 2018: Physics of Medical Imaging

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Metal implants give rise to metal artifacts in computed tomography (CT) images, which may lead to diagnostic errors and erroneous CT number estimates when the CT is used for radiation therapy planning. Methods for reducing metal artifacts by exploiting the anatomical information provided by coregistered magnetic resonance (MR) images are of great potential value, but remain technically challenging due to the poor contrast between bone and air on the MR image. In this paper, we present a novel MR-based algorithm for automatic CT metal artifact reduction (MAR), referred to as kerMAR. It combines kernel regression on known CT value/MR patch pairs in the uncorrupted patient volume with a forward model of the artifact corrupted values to estimate CT replacement values. In contrast to pseudo-CT generation that builds on multi-patient modelling, the algorithm requires no MR intensity normalisation or atlas registration. Image results for 7 head-and-neck radiation therapy patients with T1-weighted images acquired in the same fixation as the RT planning CT suggest a potential for more complete MAR close to the metal implants than the oMAR algorithm (Philips) used clinically. Our results further show improved performance in air and bone regions as compared to other MR-based MAR algorithms. In addition, we experimented with using kerMAR to define a prior for iterative reconstruction with the maximum likelihood transmission reconstruction algorithm, however with no apparent improvements

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Reduction of dental metallic artefacts in CT: Value of a newly developed algorithm for metal artefact reduction (O-MAR)

Cited by 88 publications

References 20 publications

Metal artefact reduction in CT imaging of hip prostheses—an evaluation of commercial techniques provided by four vendors

Metal artefact reduction in CT imaging of hip prostheses—an evaluation of commercial techniques provided by four vendors

Single-energy metal artefact reduction with CT for carbon-ion radiation therapy treatment planning

CT metal artifact reduction using MR image patches

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