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      Multicolor spectral photon-counting computed tomography: in vivo dual contrast imaging with a high count rate scanner

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          Abstract

          A new prototype spectral photon-counting computed tomography (SPCCT) based on a modified clinical CT system has been developed. SPCCT analysis of the energy composition of the transmitted x-ray spectrum potentially allows simultaneous dual contrast agent imaging, however, this has not yet been demonstrated with such a system. We investigated the feasibility of using this system to distinguish gold nanoparticles (AuNP) and an iodinated contrast agent. The contrast agents and calcium phosphate were imaged in phantoms. Conventional CT, gold K-edge, iodine and water images were produced and demonstrated accurate discrimination and quantification of gold and iodine concentrations in a phantom containing mixtures of the contrast agents. In vivo experiments were performed using New Zealand White rabbits at several times points after injections of AuNP and iodinated contrast agents. We found that the contrast material maps clearly differentiated the distributions of gold and iodine in the tissues allowing quantification of the contrast agents’ concentrations, which matched their expected pharmacokinetics. Furthermore, rapid, repetitive scanning was done, which allowed measurement of contrast agent kinetics with high temporal resolution. In conclusion, a clinical scale, high count rate SPCCT system is able to discriminate gold and iodine contrast media in different organs in vivo.

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          Most cited references 39

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          NIH Image to ImageJ: 25 years of image analysis.

          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Experimental feasibility of multi-energy photon-counting K-edge imaging in pre-clinical computed tomography.

            Theoretical considerations predicted the feasibility of K-edge x-ray computed tomography (CT) imaging using energy discriminating detectors with more than two energy bins. This technique enables material-specific imaging in CT, which in combination with high-Z element based contrast agents, opens up possibilities for new medical applications. In this paper, we present a CT system with energy detection capabilities, which was used to demonstrate the feasibility of quantitative K-edge CT imaging experimentally. A phantom was imaged containing PMMA, calcium-hydroxyapatite, water and two contrast agents based on iodine and gadolinium, respectively. Separate images of the attenuation by photoelectric absorption and Compton scattering were reconstructed from energy-resolved projection data using maximum-likelihood basis-component decomposition. The data analysis further enabled the display of images of the individual contrast agents and their concentrations, separated from the anatomical background. Measured concentrations of iodine and gadolinium were in good agreement with the actual concentrations. Prior to the tomographic measurements, the detector response functions for monochromatic illumination using synchrotron radiation were determined in the energy range 25 keV-60 keV. These data were used to calibrate the detector and derive a phenomenological model for the detector response and the energy bin sensitivities.
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              Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications.

              In x-ray computed tomography (CT), materials having different elemental compositions can be represented by identical pixel values on a CT image (ie, CT numbers), depending on the mass density of the material. Thus, the differentiation and classification of different tissue types and contrast agents can be extremely challenging. In dual-energy CT, an additional attenuation measurement is obtained with a second x-ray spectrum (ie, a second "energy"), allowing the differentiation of multiple materials. Alternatively, this allows quantification of the mass density of two or three materials in a mixture with known elemental composition. Recent advances in the use of energy-resolving, photon-counting detectors for CT imaging suggest the ability to acquire data in multiple energy bins, which is expected to further improve the signal-to-noise ratio for material-specific imaging. In this review, the underlying motivation and physical principles of dual- or multi-energy CT are reviewed and each of the current technical approaches is described. In addition, current and evolving clinical applications are introduced.
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                Author and article information

                Contributors
                douek@creatis.insa-lyon.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 July 2017
                6 July 2017
                2017
                : 7
                Affiliations
                [1 ]ISNI 0000 0004 1936 8972, GRID grid.25879.31, Department of Radiology, , University of Pennsylvania, ; Philadelphia, PA USA
                [2 ]ISNI 0000 0001 2163 3825, GRID grid.413852.9, Radiology Department, , Hospices Civils de Lyon, ; Lyon, France
                [3 ]CREATIS, UMR CNRS 5220, Inserm U1044, University Lyon1 Claude Bernard, Lyon, France
                [4 ]ISNI 0000 0001 2150 7757, GRID grid.7849.2, LAGEP Laboratory, , University Lyon 1 Claude Bernard, ; Lyon, France
                [5 ]ISNI 0000 0004 0639 301X, GRID grid.420133.7, , CERMEP, ; Lyon, France
                [6 ]CT Clinical Science, Philips, Suresnes France
                [7 ]ISNI 0000 0001 2248 7639, GRID grid.7468.d, Philips GmbH Innovative Technologies, , Research Laboratories, ; Hamburg, Germany
                [8 ]Global Advanced Technologies, CT, Philips, Haifa Israel
                Article
                4659
                10.1038/s41598-017-04659-9
                5500581
                28684756
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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