Reducing beam hardening effects and metal artefacts in spectral CT using Medipix3RX

Rajendran, Kishore; Walsh, Michael F.; Ruiter, Niels J A de; Chernoglazov, Alexander I.; Panta, Raj K.; Butler, Anthony; Butler, P. H.; Bell, Stephen T.; Anderson, N.; Woodfield, Tim B. F.; Tredinnick, Seamus; Healy, Joseph L.; Bateman, Christopher; Raja, Aamir; Doesburg, R.; Renaud, Peter; Gieseg, Steven P.; Smithies, Derek J.; Mohr, J L; Mandalika, V. B. H.; Opie, Alex M. T.; Cook, Nick; Ronaldson, J P; Nik, S J; Atharifard, Ali; Clyne, M.N.; Bones, Philip J.; Bartneck, Christoph; Grasset, Raphaël; Schleich, Nanette; Billinghurst, Mark

doi:10.1088/1748-0221/9/03/p03015

Cited by 35 publications

(19 citation statements)

References 27 publications

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“…One advantage of PCD-CT detector technology is the potential to reduce beam-hardening artifacts in comparison to energy-integrating detectors (EID) when using high-energy bins, as has been shown in a small animal scanner 3 . Metal artifacts can diminish image quality, reducing diagnostic accuracy and disguise important findings, and several approaches exist for the reduction of metal artifacts 4 – 7 .…”

Section: Introductionmentioning

confidence: 99%

“…Metal artifacts can diminish image quality, reducing diagnostic accuracy and disguise important findings, and several approaches exist for the reduction of metal artifacts 4 – 7 . Recent studies recommend the use of high-energy thresholds and, if available, a tin filter in PCD-CT 1 – 3 , 8 . Given the potential advantages of PCD-CT technology for metal artifact reduction, the aim of the study was to evaluate the application of PCD-CT for the reduction of metal artifacts and to evaluate the effect of tube potential, energy thresholds and acquisition mode (Macro vs.…”

Section: Introductionmentioning

confidence: 99%

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A semi-automated quantitative comparison of metal artifact reduction in photon-counting computed tomography by energy-selective thresholding

Sawall

Heinze

et al. 2020

Sci Rep

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An evaluation of energy thresholding and acquisition mode for metal artifact reduction in Photon-counting detector CT (PCD-CT) compared to conventional energy-integrating detector CT (EID-CT) was performed. Images of a hip prosthesis phantom placed in a water bath were acquired on a scanner with PCD-CT and EID-CT (tube potentials: 100, 120 and 140 kVp) and energy thresholds (above 55–75 keV) in Macro and Chess mode. Only high-energy threshold images (HTI) were used. Metal artifacts were quantified by a semi-automated segmentation algorithm, calculating artifact volumes, means and standard deviations of CT numbers. Images of a human cadaver with hip prosthesis were acquired on the PCD-CT in Macro mode as proof-of-concept. Images at 140 kVp showed less metal artifacts than 120 kVp or 100 kVp. HTI (70, 75 keV) had fewer artifacts than low energy thresholds (55, 60, 65 keV). Fewer artifacts were observed in the Macro-HTI (8.9–13.3%) for cortical bone compared to Chess-HTI (9.4–19.1%) and EID-CT (10.7–19.0%) whereas in bone marrow Chess-HTI (19.9–45.1%) showed less artifacts compared to Macro-HTI (21.9–38.3%) and EID-CT (36.4–54.9%). Noise for PCD-CT (56–81 HU) was higher than EID-CT (33–36 HU) irrespective of tube potential. High-energy thresholding could be used for metal artifact reduction in PCD-CT, but further investigation of acquisition modes depending on target structure is required.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A semi-automated quantitative comparison of metal artifact reduction in photon-counting computed tomography by energy-selective thresholding

Sawall

Heinze

et al. 2020

Sci Rep

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“…However, the specificity of target material to water cannot be determined by Equation (8) as the water basis is used as a reference material. Therefore, percentage of voxels in the composite materials which are only classified as water are calculated as (9) Finally, the relationship between the known and measured concentrations of gadolinium and hydroxyapatite was analyzed in the material domain images by manually selecting ROIs comprising ~1409 voxels (N) over each solution insert.…”

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confidence: 99%

Measuring Identification and Quantification Errors in Spectral CT Material Decomposition

et al. 2018

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Material decomposition methods are used to identify and quantify multiple tissue components in spectral CT but there is no published method to quantify the misidentification of materials. This paper describes a new method for assessing misidentification and mis-quantification in spectral CT. We scanned a phantom containing gadolinium (1, 2, 4, 8 mg/mL), hydroxyapatite (54.3, 211.7, 808.5 mg/mL), water and vegetable oil using a MARS spectral scanner equipped with a poly-energetic X-ray source operated at 118 kVp and a CdTe Medipix3RX camera. Two imaging protocols were used; both with and without 0.375 mm external brass filter. A proprietary material decomposition method identified voxels as gadolinium, hydroxyapatite, lipid or water. Sensitivity and specificity information was used to evaluate material misidentification. Biological samples were also scanned. There were marked differences in identification and quantification between the two protocols even though spectral and linear correlation of gadolinium and hydroxyapatite in the reconstructed images was high and no qualitative segmentation differences in the material decomposed images were observed. At 8 mg/mL, gadolinium was correctly identified for both protocols, but concentration was underestimated by over half for the unfiltered protocol. At 1 mg/mL, gadolinium was misidentified in 38% of voxels for the filtered protocol and 58% of voxels for the unfiltered protocol. Hydroxyapatite was correctly identified at the two higher concentrations for both protocols, but mis-quantified for the unfiltered protocol. Gadolinium concentration as measured in the biological specimen showed a two-fold difference between protocols. In future, this methodology could be used to compare and optimize scanning protocols, image reconstruction methods, and methods for material differentiation in spectral CT.

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“…As an emerging revolution in X-ray-based imaging, spectral molecular CT promises to complement the existing molecular imaging modalities and to be a potential tool for delivering personalised medicine [6–10]. Preclinical results with spectral molecular CT have been very encouraging and indicate that the specific identification and quantification of tissue types and nanoparticles is possible, such as imaging of vulnerable plaque [11, 12], soft tissue quantification [13], reduction in metal-related CT artefacts [14, 15], crystal-induced arthropathies [16, 17], quantitative imaging of excised osteoarthritic cartilage [18], and K-edge imaging of high-Z (atomic number) biomedical nanoparticles [19, 20].…”

Section: Introductionmentioning

confidence: 99%

Spectral Photon-Counting Molecular Imaging for Quantification of Monoclonal Antibody-Conjugated Gold Nanoparticles Targeted to Lymphoma and Breast Cancer: AnIn VitroStudy

Moghiseh

Lowe

Lewis

et al. 2018

Contrast Media & Molecular Imaging

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The purpose of the present study was to demonstrate an in vitro proof of principle that spectral photon-counting CT can measure gold-labelled specific antibodies targeted to specific cancer cells. A crossover study was performed with Raji lymphoma cancer cells and HER2-positive SKBR3 breast cancer cells using a MARS spectral CT scanner. Raji cells were incubated with monoclonal antibody-labelled gold, rituximab (specific antibody to Raji cells), and trastuzumab (as a control); HER2-positive SKBR3 breast cancer cells were incubated with monoclonal antibody-labelled gold, trastuzumab (specific antibody to HER2-positive cancer cells), and rituximab (as a control). The calibration vials with multiple concentrations of nonfunctionalised gold nanoparticles were used to calibrate spectral CT. Spectral imaging results showed that the Raji cells-rituximab-gold and HER2-positive cells-trastuzumab-gold had a quantifiable amount of gold, 5.97 mg and 0.78 mg, respectively. In contrast, both cell lines incubated with control antibody-labelled gold nanoparticles had less gold attached (1.22 mg and 0.15 mg, respectively). These results demonstrate the proof of principle that spectral molecular CT imaging can identify and quantify specific monoclonal antibody-labelled gold nanoparticles taken up by Raji cells and HER2-positive SKBR3 breast cancer cells. The present study reports the future potential of spectral molecular imaging in detecting tumour heterogeneity so that treatment can be tuned accordingly, leading to more effective personalised medicine.

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Reducing beam hardening effects and metal artefacts in spectral CT using Medipix3RX

Cited by 35 publications

References 27 publications

A semi-automated quantitative comparison of metal artifact reduction in photon-counting computed tomography by energy-selective thresholding

A semi-automated quantitative comparison of metal artifact reduction in photon-counting computed tomography by energy-selective thresholding

Measuring Identification and Quantification Errors in Spectral CT Material Decomposition

Spectral Photon-Counting Molecular Imaging for Quantification of Monoclonal Antibody-Conjugated Gold Nanoparticles Targeted to Lymphoma and Breast Cancer: AnIn VitroStudy

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