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Journal articles on the topic 'Spectral Photon Counting Computed Tomography'

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Published: 7 July 2024

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1

Moghiseh, Mahdieh, Emily Searle, Devyani Dixit, Johoon Kim, Yuxi C. Dong, David P. Cormode, Anthony Butler, and Steven P. Gieseg. "Spectral Photon-Counting CT Imaging of Gold Nanoparticle Labelled Monocytes for Detection of Atherosclerosis: A Preclinical Study." Diagnostics 13, no. 3 (January 29, 2023): 499. http://dx.doi.org/10.3390/diagnostics13030499.

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A key process in the development of atherosclerotic plaques is the recruitment of monocytes into the artery wall. Using spectral photon-counting computed tomography we examine whether monocyte deposition within the artery wall of ApoE-/- mouse can be detected. Primary mouse monocytes were labelled by incubating them with 15 nm gold nanoparticles coated with 11-mercaptoundecanoic acid The monocyte uptake of the particle was confirmed by electron microscopy of the cells before injection into 6-week-old apolipoprotein E deficient (ApoE-/-) mouse that had been fed with the Western diet for 10 weeks. Four days following injection, the mouse was sacrificed and imaged using a MARS spectral photon counting computed tomography scanner with a spectral range of 7 to 120 KeV with five energy bins. Imaging analysis showed the presence of X-ray dense material within the mouse aortic arch which was consistent with the spectral characteristic of gold rather than calcium. The imaging is interpreted as showing the deposition of gold nanoparticles containing monocytes within the mouse aorta. The results of our study determined that spectral photon-counting computed tomography could provide quantitative information about gold nanoparticles labelled monocytes in voxels of 90 × 90 × 90 µm3. The imaging was consistent with previous micro-CT and electron microscopy of mice using the same nanoparticles. This study demonstrates that spectral photon-counting computed tomography, using a MARS small bore scanner, can detect a fundamental atherogenic process within mouse models of atherogenesis. The present study demonstrates the feasibility of spectral photon-counting computed tomography as an emerging molecular imaging modality to detect atherosclerotic disease.

2

Balegamire, Joëlle, Marc Vandamme, Emmanuel Chereul, Salim Si-Mohamed, Samira Azzouz Maache, Eyad Almouazen, Laurent Ettouati, et al. "Iodinated polymer nanoparticles as contrast agent for spectral photon counting computed tomography." Biomaterials Science 8, no. 20 (2020): 5715–28. http://dx.doi.org/10.1039/d0bm01046d.

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3

Sawall, Stefan, Carlo Amato, Laura Klein, Eckhard Wehrse, Joscha Maier, and Marc Kachelrieß. "Toward molecular imaging using spectral photon-counting computed tomography?" Current Opinion in Chemical Biology 63 (August 2021): 163–70. http://dx.doi.org/10.1016/j.cbpa.2021.04.002.

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4

Steadman, Roger, Christoph Herrmann, Oliver Mülhens, and Dale G. Maeding. "ChromAIX: Fast photon-counting ASIC for Spectral Computed Tomography." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 648 (August 2011): S211—S215. http://dx.doi.org/10.1016/j.nima.2010.11.149.

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5

Bratke, Grischa, Tilman Hickethier, Daniel Bar-Ness, Alexander Christian Bunck, David Maintz, Gregor Pahn, Philippe Coulon, Salim Si-Mohamed, Philippe Douek, and Monica Sigovan. "Spectral Photon-Counting Computed Tomography for Coronary Stent Imaging." Investigative Radiology 55, no. 2 (February 2020): 61–67. http://dx.doi.org/10.1097/rli.0000000000000610.

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6

Tortora, Mario, Laura Gemini, Imma D’Iglio, Lorenzo Ugga, Gaia Spadarella, and Renato Cuocolo. "Spectral Photon-Counting Computed Tomography: A Review on Technical Principles and Clinical Applications." Journal of Imaging 8, no. 4 (April 15, 2022): 112. http://dx.doi.org/10.3390/jimaging8040112.

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Photon-counting computed tomography (CT) is a technology that has attracted increasing interest in recent years since, thanks to new-generation detectors, it holds the promise to radically change the clinical use of CT imaging. Photon-counting detectors overcome the major limitations of conventional CT detectors by providing very high spatial resolution without electronic noise, providing a higher contrast-to-noise ratio, and optimizing spectral images. Additionally, photon-counting CT can lead to reduced radiation exposure, reconstruction of higher spatial resolution images, reduction of image artifacts, optimization of the use of contrast agents, and create new opportunities for quantitative imaging. The aim of this review is to briefly explain the technical principles of photon-counting CT and, more extensively, the potential clinical applications of this technology.

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Yu, Zhicong, Shuai Leng, Zhoubo Li, and Cynthia H. McCollough. "Spectral prior image constrained compressed sensing (spectral PICCS) for photon-counting computed tomography." Physics in Medicine and Biology 61, no. 18 (August 23, 2016): 6707–32. http://dx.doi.org/10.1088/0031-9155/61/18/6707.

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8

Meloni, Antonella, Erica Maffei, Alberto Clemente, Carmelo De Gori, Mariaelena Occhipinti, Vicenzo Positano, Sergio Berti, et al. "Spectral Photon-Counting Computed Tomography: Technical Principles and Applications in the Assessment of Cardiovascular Diseases." Journal of Clinical Medicine 13, no. 8 (April 18, 2024): 2359. http://dx.doi.org/10.3390/jcm13082359.

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Spectral Photon-Counting Computed Tomography (SPCCT) represents a groundbreaking advancement in X-ray imaging technology. The core innovation of SPCCT lies in its photon-counting detectors, which can count the exact number of incoming x-ray photons and individually measure their energy. The first part of this review summarizes the key elements of SPCCT technology, such as energy binning, energy weighting, and material decomposition. Its energy-discriminating ability represents the key to the increase in the contrast between different tissues, the elimination of the electronic noise, and the correction of beam-hardening artifacts. Material decomposition provides valuable insights into specific elements’ composition, concentration, and distribution. The capability of SPCCT to operate in three or more energy regimes allows for the differentiation of several contrast agents, facilitating quantitative assessments of elements with specific energy thresholds within the diagnostic energy range. The second part of this review provides a brief overview of the applications of SPCCT in the assessment of various cardiovascular disease processes. SPCCT can support the study of myocardial blood perfusion and enable enhanced tissue characterization and the identification of contrast agents, in a manner that was previously unattainable.

9

Si-Mohamed, Salim, David P. Cormode, Daniel Bar-Ness, Monica Sigovan, Pratap C. Naha, Jean-Baptiste Langlois, Lara Chalabreysse, et al. "Evaluation of spectral photon counting computed tomography K-edge imaging for determination of gold nanoparticle biodistribution in vivo." Nanoscale 9, no. 46 (2017): 18246–57. http://dx.doi.org/10.1039/c7nr01153a.

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10

Si-Mohamed, Salim Aymeric, Jade Miailhes, Pierre-Antoine Rodesch, Sara Boccalini, Hugo Lacombe, Valérie Leitman, Vincent Cottin, Loic Boussel, and Philippe Douek. "Spectral Photon-Counting CT Technology in Chest Imaging." Journal of Clinical Medicine 10, no. 24 (December 9, 2021): 5757. http://dx.doi.org/10.3390/jcm10245757.

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The X-ray imaging field is currently undergoing a period of rapid technological innovation in diagnostic imaging equipment. An important recent development is the advent of new X-ray detectors, i.e., photon-counting detectors (PCD), which have been introduced in recent clinical prototype systems, called PCD computed tomography (PCD-CT) or photon-counting CT (PCCT) or spectral photon-counting CT (SPCCT) systems. PCD allows a pixel up to 200 microns pixels at iso-center, which is much smaller than that can be obtained with conventional energy integrating detectors (EID). PCDs have also a higher dose efficiency than EID mainly because of electronic noise suppression. In addition, the energy-resolving capabilities of these detectors allow generating spectral basis imaging, such as the mono-energetic images or the water/iodine material images as well as the K-edge imaging of a contrast agent based on atoms of high atomic number. In recent years, studies have therefore been conducted to determine the potential of PCD-CT as an alternative to conventional CT for chest imaging.

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Gustavsson, Mikael, Farooq Ul Amin, Anders Bjorklid, Andreas Ehliar, Cheng Xu, and Christer Svensson. "A High-Rate Energy-Resolving Photon-Counting ASIC for Spectral Computed Tomography." IEEE Transactions on Nuclear Science 59, no. 1 (February 2012): 30–39. http://dx.doi.org/10.1109/tns.2011.2169811.

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Bornefalk, Hans, and Mats Danielsson. "Photon-counting spectral computed tomography using silicon strip detectors: a feasibility study." Physics in Medicine and Biology 55, no. 7 (March 19, 2010): 1999–2022. http://dx.doi.org/10.1088/0031-9155/55/7/014.

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Weidinger, Thomas, Thorsten M. Buzug, Thomas Flohr, Steffen Kappler, and Karl Stierstorfer. "Polychromatic Iterative Statistical Material Image Reconstruction for Photon-Counting Computed Tomography." International Journal of Biomedical Imaging 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/5871604.

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This work proposes a dedicated statistical algorithm to perform a direct reconstruction of material-decomposed images from data acquired with photon-counting detectors (PCDs) in computed tomography. It is based on local approximations (surrogates) of the negative logarithmic Poisson probability function. Exploiting the convexity of this function allows for parallel updates of all image pixels. Parallel updates can compensate for the rather slow convergence that is intrinsic to statistical algorithms. We investigate the accuracy of the algorithm for ideal photon-counting detectors. Complementarily, we apply the algorithm to simulation data of a realistic PCD with its spectral resolution limited by K-escape, charge sharing, and pulse-pileup. For data from both an ideal and realistic PCD, the proposed algorithm is able to correct beam-hardening artifacts and quantitatively determine the material fractions of the chosen basis materials. Via regularization we were able to achieve a reduction of image noise for the realistic PCD that is up to 90% lower compared to material images form a linear, image-based material decomposition using FBP images. Additionally, we find a dependence of the algorithms convergence speed on the threshold selection within the PCD.

14

Liu, Xuejin, Mats Persson, Hans Bornefalk, Staffan Karlsson, Cheng Xu, Mats Danielsson, and Ben Huber. "Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications." Journal of Medical Imaging 2, no. 3 (September 11, 2015): 033502. http://dx.doi.org/10.1117/1.jmi.2.3.033502.

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Devadithya, Sandamali, and David Castañón. "Enhanced Material Estimation with Multi-Spectral CT." Electronic Imaging 2021, no. 15 (January 18, 2021): 229–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.15.coimg-229.

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Conventional X-ray computed tomography (CT) systems obtain single- or dual-energy measurements, from which dual-energy CT has emerged as the superior way to recognize materials. Recently photon counting detectors have facilitated multi-spectral CT which captures spectral information by counting photon arrivals at different energy windows. However, the narrow energy bins result in a lower signal-to-noise ratio in each bin, particularly in the lower energy bins. This effect is significant and challenging when high-attenuation materials such as metal are present in the area to be imaged. In this paper, we propose a novel technique to estimate material properties with multi-spectral CT in the presence of high-attenuation materials. Our approach combines basis decomposition concepts using multiple-spectral bin information, as well as individual energy bin reconstructions. We show that this approach is robust in the presence of metal and outperforms alternative techniques for material estimation with multi-spectral CT as well with the state-of-art dual-energy CT.

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Cammin, Jochen, Steffen Kappler, Thomas Weidinger, and Katsuyuki Taguchi. "Evaluation of models of spectral distortions in photon-counting detectors for computed tomography." Journal of Medical Imaging 3, no. 2 (May 6, 2016): 023503. http://dx.doi.org/10.1117/1.jmi.3.2.023503.

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de Vries, Anke, Ewald Roessl, Esther Kneepkens, Axel Thran, Bernhard Brendel, Gerhard Martens, Roland Proska, Klaas Nicolay, and Holger Grüll. "Quantitative Spectral K-Edge Imaging in Preclinical Photon-Counting X-Ray Computed Tomography." Investigative Radiology 50, no. 4 (August 2015): 297–304. http://dx.doi.org/10.1097/rli.0000000000000126.

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18

Stamp, Lisa K., Nigel G. Anderson, Fabio Becce, Maya Rajeswari, Matthew Polson, Olivier Guyen, Anais Viry, Chloe Choi, Tracy E. Kirkbride, and Aamir Y. Raja. "Clinical Utility of Multi‐Energy Spectral Photon‐Counting Computed Tomography in Crystal Arthritis." Arthritis & Rheumatology 71, no. 7 (May 28, 2019): 1158–62. http://dx.doi.org/10.1002/art.40848.

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19

Grönberg, Fredrik, Johan Lundberg, Martin Sjölin, Mats Persson, Robert Bujila, Hans Bornefalk, Håkan Almqvist, Staffan Holmin, and Mats Danielsson. "Feasibility of unconstrained three-material decomposition: imaging an excised human heart using a prototype silicon photon-counting CT detector." European Radiology 30, no. 11 (June 25, 2020): 5904–12. http://dx.doi.org/10.1007/s00330-020-07017-y.

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Abstract Rationale and objectives The purpose of this study was to evaluate the feasibility of unconstrained three-material decomposition in a human tissue specimen containing iodinated contrast agent, using an experimental multi-bin photon-counting silicon detector. It was further to evaluate potential added clinical value compared to a 1st-generation state-of-the-art dual-energy computed tomography system. Materials and methods A prototype photon-counting silicon detector in a bench-top setup for x-ray tomographic imaging was calibrated using a multi-material calibration phantom. A heart with calcified plaque was obtained from a deceased patient, and the coronary arteries were injected with an iodinated contrast agent mixed with gelatin. The heart was imaged in the experimental setup and on a 1st-generation state-of-the-art dual-energy computed tomography system. Projection-based three-material decomposition without any constraints was performed with the photon-counting detector data, and the resulting images were compared with those obtained from the dual-energy system. Results The photon-counting detector images show better separation of iodine and calcium compared to the dual-energy images. Additional experiments confirmed that unbiased estimates of soft tissue, calcium, and iodine could be achieved without any constraints. Conclusion The proposed experimental system could provide added clinical value compared to current dual-energy systems for imaging tasks where mix-up of iodine and calcium is an issue, and the anatomy is sufficiently small to allow iodine to be differentiated from calcium. Considering its previously shown count rate capability, these results show promise for future integration of this detector in a clinical CT scanner. Key Points • Spectral photon-counting detectors can solve some of the fundamental problems with conventional single-energy CT. • Dual-energy methods can be used to differentiate iodine and calcium, but to do so must rely on constraints, since solving for three unknowns with only two measurements is not possible. Photon-counting detectors can improve upon these methods by allowing unconstrained three-material decomposition. • A prototype photon-counting silicon detector with high count rate capability allows performing unconstrained three-material decomposition and qualitatively shows better differentiation of iodine and calcium than dual-energy CT.

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Liu, Xuejin, Mats Persson, Hans Bornefalk, Staffan Karlsson, Cheng Xu, Mats Danielsson, and Ben Huber. "Errata: Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications." Journal of Medical Imaging 3, no. 4 (October 25, 2016): 049801. http://dx.doi.org/10.1117/1.jmi.3.4.049801.

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Rodesch, Pierre-Antoine, Devon Richtsmeier, Kevin Murphy, Kris Iniewski, and Magdalena Bazalova-Carter. "Photon-counting detector step-wedge calibration enabling water and iodine material decomposition." Journal of Instrumentation 19, no. 05 (May 1, 2024): P05030. http://dx.doi.org/10.1088/1748-0221/19/05/p05030.

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Abstract Photon-counting detector computed tomography (PCD-CT) has demonstrated improvements in conventional image quality compared to energy integrating detector (EID) CT. PCD-CT has the advantage of being able to operate in conventional and spectral mode simultaneously by sorting photons according to selected energy thresholds. However, to reconstruct spectral images PCD-CT requires extensive calibration and specifically fine-tuning a spectral response. This response is then used to perform material decomposition (MD). We propose a step-wedge phantom made of water and iodine to calibrate a prototype PCD-CT system. Four methods were tested and compared based on calibration accuracy and CT image quality. The exhaustive PCD response was not well calibrated, but a reduced model was defined that was able to perform accurate water/iodine MD and to reduce the ring artifact intensity. The impact of the number of energy bins (from two to seven) was also studied. The number of bins did not affect the spectral accuracy. However, compared to the two energy bin configuration, the seven bin configuration decreased the noise by 10% and 15% in the water and iodine maps, respectively. The model was tested on ex-vivo tissue samples injected with iodine to demonstrate the results of the water/iodine MD on biological materials.

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Boccalini, Sara, Salim A. Si-Mohamed, Hugo Lacombe, Adja Diaw, Mohammad Varasteh, Pierre-Antoine Rodesch, Marjorie Villien, et al. "First In-Human Results of Computed Tomography Angiography for Coronary Stent Assessment With a Spectral Photon Counting Computed Tomography." Investigative Radiology 57, no. 4 (October 28, 2021): 212–21. http://dx.doi.org/10.1097/rli.0000000000000835.

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Si-Mohamed, Salim, Daniel Bar-Ness, Monica Sigovan, David P. Cormode, Philippe Coulon, Emmanuel Coche, Alain Vlassenbroek, Gabrielle Normand, Loic Boussel, and Philippe Douek. "Review of an initial experience with an experimental spectral photon-counting computed tomography system." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 873 (November 2017): 27–35. http://dx.doi.org/10.1016/j.nima.2017.04.014.

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Cammin, Jochen, Steffen Kappler, Thomas Weidinger, and Katsuyuki Taguchi. "Errata: Evaluation of models of spectral distortions in photon-counting detectors for computed tomography." Journal of Medical Imaging 3, no. 2 (May 18, 2016): 029801. http://dx.doi.org/10.1117/1.jmi.3.2.029801.

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Curtis, Tyler E., and Ryan K. Roeder. "Quantification of multiple mixed contrast and tissue compositions using photon-counting spectral computed tomography." Journal of Medical Imaging 6, no. 01 (February 11, 2019): 1. http://dx.doi.org/10.1117/1.jmi.6.1.013501.

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26

Lee, Seungwan, Yu-Na Choi, and Hee-Joung Kim. "Quantitative material decomposition using spectral computed tomography with an energy-resolved photon-counting detector." Physics in Medicine and Biology 59, no. 18 (August 28, 2014): 5457–82. http://dx.doi.org/10.1088/0031-9155/59/18/5457.

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Borges, Ana P., Célia Antunes, and Filipe Caseiro-Alves. "Spectral CT: Current Liver Applications." Diagnostics 13, no. 10 (May 9, 2023): 1673. http://dx.doi.org/10.3390/diagnostics13101673.

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Using two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.

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Neumann, Jonas, Tristan Nowak, Bernhard Schmidt, and Joachim von Zanthier. "An Image-Based Prior Knowledge-Free Approach for a Multi-Material Decomposition in Photon-Counting Computed Tomography." Diagnostics 14, no. 12 (June 14, 2024): 1262. http://dx.doi.org/10.3390/diagnostics14121262.

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Photon-counting CT systems generally allow for acquiring multiple spectral datasets and thus for decomposing CT images into multiple materials. We introduce a prior knowledge-free deterministic material decomposition approach for quantifying three material concentrations on a commercial photon-counting CT system based on a single CT scan. We acquired two phantom measurement series: one to calibrate and one to test the algorithm. For evaluation, we used an anthropomorphic abdominal phantom with inserts of either aqueous iodine solution, aqueous tungsten solution, or water. Material CT numbers were predicted based on a polynomial in the following parameters: Water-equivalent object diameter, object center-to-isocenter distance, voxel-to-isocenter distance, voxel-to-object center distance, and X-ray tube current. The material decomposition was performed as a generalized least-squares estimation. The algorithm provided material maps of iodine, tungsten, and water with average estimation errors of 4% in the contrast agent maps and 1% in the water map with respect to the material concentrations in the inserts. The contrast-to-noise ratio in the iodine and tungsten map was 36% and 16% compared to the noise-minimal threshold image. We were able to decompose four spectral images into iodine, tungsten, and water.

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Chen, Han, Cheng Xu, Mats Persson, and Mats Danielsson. "Optimization of beam quality for photon-counting spectral computed tomography in head imaging: simulation study." Journal of Medical Imaging 2, no. 4 (November 6, 2015): 043504. http://dx.doi.org/10.1117/1.jmi.2.4.043504.

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Sotenskii, R. V., V. A. Rozhkov, D. A. Shashurin, E. V. Suslova, and G. A. Chelkov. "Novel algorithm for qualitative and quantitative material analysis by the K-edges for photon-counting computed tomography." Journal of Instrumentation 19, no. 04 (April 1, 2024): P04009. http://dx.doi.org/10.1088/1748-0221/19/04/p04009.

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Abstract The use of photon-counting detectors (PCD) in X-ray computed tomography (CT) allows for obtaining specific spectral information about the materials present in the studied object. This provides the capability to detect contrast agents (CAs) based on elements with high atomic numbers, which opens up significant prospects for diagnostics and preclinical trials. This work presents a criterion for the extraction of a contrast agent and the determination of its concentration based on the K-edge absorption. The criterion is built on the study of the spectral characteristics of CAs. It considers scenarios where more than two contrast agents are simultaneously used in a wide range of concentrations in the study. The experiment was conducted using a laboratory microtomographic system based on the Medipix3RX detector family. The criterion utilizes five energy thresholds for the identification of a single contrast agent. Lanthanides were used as contrast agents.

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Bhattarai, Abhisek, Ray Tanaka, Andy Wai Kan Yeung, and Varut Vardhanabhuti. "Photon-Counting CT Material Decomposition in Bone Imaging." Journal of Imaging 9, no. 10 (October 2, 2023): 209. http://dx.doi.org/10.3390/jimaging9100209.

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The accurate screening of osteoporosis is important for identifying persons at risk. The diagnosis of bone conditions using dual X-ray absorptiometry is limited to extracting areal bone mineral density (BMD) and fails to provide any structural information. Computed tomography (CT) is excellent for morphological imaging but not ideal for material quantification. Advanced photon-counting detector CT (PCD-CT) possesses high spectral sensitivity and material decomposition capabilities to simultaneously determine qualitative and quantitative information. In this study, we explored the diagnostic utility of PCD-CT to provide high-resolution 3-D imaging of bone microarchitecture and composition for the sensitive diagnosis of bone in untreated and ovariectomized rats. PCD-CT accurately decomposed the calcium content within hydroxyapatite phantoms (r = 0.99). MicroCT analysis of tibial bone revealed significant differences in the morphological parameters between the untreated and ovariectomized samples. However, differences in the structural parameters of the mandible between the treatment groups were not observed. BMD determined with microCT and calcium concentration decomposed using PCD-CT differed significantly between the treatment groups in both the tibia and mandible. Quantitative analysis with PCD-CT is sensitive in determining the distribution of calcium and water components in bone and may have utility in the screening and diagnosis of bone conditions such as osteoporosis.

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Di Trapani, Vittorio, and Francesco Brun. "Pre- and post-reconstruction digital image processing solutions for computed tomography with spectral photon counting detectors." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 1010 (September 2021): 165510. http://dx.doi.org/10.1016/j.nima.2021.165510.

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Nasirudin, Radin A., Kai Mei, Petar Panchev, Andreas Fehringer, Franz Pfeiffer, Ernst J. Rummeny, Martin Fiebich, and Peter B. Noël. "Reduction of Metal Artifact in Single Photon-Counting Computed Tomography by Spectral-Driven Iterative Reconstruction Technique." PLOS ONE 10, no. 5 (May 8, 2015): e0124831. http://dx.doi.org/10.1371/journal.pone.0124831.

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Li, Xuru, Xueqin Sun, Yanbo Zhang, Jinxiao Pan, and Ping Chen. "Tensor Dictionary Learning with an Enhanced Sparsity Constraint for Sparse-View Spectral CT Reconstruction." Photonics 9, no. 1 (January 8, 2022): 35. http://dx.doi.org/10.3390/photonics9010035.

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Spectral computed tomography (CT) can divide collected photons into multi-energy channels and gain multi-channel projections synchronously by using photon-counting detectors. However, reconstructed images usually contain severe noise due to the limited number of photons in the corresponding energy channel. Tensor dictionary learning (TDL)-based methods have achieved better performance, but usually lose image edge information and details, especially from an under-sampling dataset. To address this problem, this paper proposes a method termed TDL with an enhanced sparsity constraint for spectral CT reconstruction. The proposed algorithm inherits the superiority of TDL by exploring the correlation of spectral CT images. Moreover, the method designs a regularization using the L0-norm of the image gradient to constrain images and the difference between images and a prior image in each energy channel simultaneously, further improving the ability to preserve edge information and subtle image details. The split-Bregman algorithm has been applied to address the proposed objective minimization model. Several numerical simulations and realistic preclinical mice are studied to assess the effectiveness of the proposed algorithm. The results demonstrate that the proposed method improves the quality of spectral CT images in terms of noise elimination, edge preservation, and image detail recovery compared to the several existing better methods.

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Stański, Marcin, Ilona Michałowska, Adam Lemanowicz, Katarzyna Karmelita-Katulska, Przemysław Ratajczak, Agata Sławińska, and Zbigniew Serafin. "Dual-Energy and Photon-Counting Computed Tomography in Vascular Applications—Technical Background and Post-Processing Techniques." Diagnostics 14, no. 12 (June 11, 2024): 1223. http://dx.doi.org/10.3390/diagnostics14121223.

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The field of computed tomography (CT), which is a basic diagnostic tool in clinical practice, has recently undergone rapid technological advances. These include the evolution of dual-energy CT (DECT) and development of photon-counting computed tomography (PCCT). DECT enables the acquisition of CT images at two different energy spectra, which allows for the differentiation of certain materials, mainly calcium and iodine. PCCT is a recent technology that enables a scanner to quantify the energy of each photon gathered by the detector. This method gives the possibility to decrease the radiation dose and increase the spatial and temporal resolutions of scans. Both of these techniques have found a wide range of applications in radiology, including vascular studies. In this narrative review, the authors present the principles of DECT and PCCT, outline their advantages and drawbacks, and briefly discuss the application of these methods in vascular radiology.

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Nasirudin, Radin A., Kai Mei, Petar Penchev, Andreas Fehringer, Franz Pfeiffer, Ernst J. Rummeny, Martin Fiebich, and Peter B. Noël. "Correction: Reduction of Metal Artifact in Single Photon-Counting Computed Tomography by Spectral-Driven Iterative Reconstruction Technique." PLOS ONE 10, no. 6 (June 22, 2015): e0131500. http://dx.doi.org/10.1371/journal.pone.0131500.

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Abascal, Juan, Cecile Olivier, Suzanne Bussod, Françoise Peyrin, and Christine Chappard. "QUANTIFICATION OF CARTILAGE AND SUBCHONDRAL BONE CYSTS ON KNEE SPECIMENS BASED ON SPECTRAL PHOTON-COUNTING COMPUTED TOMOGRAPHY." Osteoarthritis and Cartilage 32 (April 2024): S338. http://dx.doi.org/10.1016/j.joca.2024.02.498.

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Riederer, Isabelle, Salim Si-Mohamed, Sebastian Ehn, Daniel Bar-Ness, Peter B. Noël, Alexander A. Fingerle, Franz Pfeiffer, Ernst J. Rummeny, Philippe Douek, and Daniela Pfeiffer. "Differentiation between blood and iodine in a bovine brain—Initial experience with Spectral Photon-Counting Computed Tomography (SPCCT)." PLOS ONE 14, no. 2 (February 25, 2019): e0212679. http://dx.doi.org/10.1371/journal.pone.0212679.

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Curtis, Tyler E., and Ryan K. Roeder. "Effects of calibration methods on quantitative material decomposition in photon-counting spectral computed tomography using a maximuma posterioriestimator." Medical Physics 44, no. 10 (August 8, 2017): 5187–97. http://dx.doi.org/10.1002/mp.12457.

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Lee, Sung Hyun, Naoki Sunaguchi, Akie Nagao, Yoshiyuki Hirano, Hiroshi Sakurai, Yosuke Kano, Masami Torikoshi, Tatsuaki Kanai, and Mutsumi Tashiro. "Calculation of Stopping-Power Ratio from Multiple CT Numbers Using Photon-Counting CT System: Two- and Three-Parameter-Fitting Method." Sensors 21, no. 4 (February 9, 2021): 1215. http://dx.doi.org/10.3390/s21041215.

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The two-parameter-fitting method (PFM) is commonly used to calculate the stopping-power ratio (SPR). This study proposes a new formalism: a three-PFM, which can be used in multiple spectral computed tomography (CT). Using a photon-counting CT system, seven rod-shaped samples of aluminium, graphite, and poly(methyl methacrylate) (PMMA), and four types of biological phantom materials were placed in a water-filled sample holder. The X-ray tube voltage and current were set at 150 kV and 40 μμA respectively, and four CT images were obtained at four threshold settings. A semi-empirical correction method that corrects the difference between the CT values from the photon-counting CT images and theoretical values in each spectral region was also introduced. Both the two- and three-PFMs were used to calculate the effective atomic number and electron density from multiple CT numbers. The mean excitation energy was calculated via parameterisation with the effective atomic number, and the SPR was then calculated from the calculated electron density and mean excitation energy. Then, the SPRs from both methods were compared with the theoretical values. To estimate the noise level of the CT numbers obtained from the photon-counting CT, CT numbers, including noise, were simulated to evaluate the robustness of the aforementioned PFMs. For the aluminium and graphite, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 17.1% and 7.1%, respectively. For the PMMA and biological phantom materials, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 5.5% and 2.0%, respectively. It was concluded that the three-PFM, compared with the two-PFM, can yield SPRs that are closer to the theoretical values and is less affected by noise.

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Inkinen, Satu I., Mikael A. K. Juntunen, Juuso Ketola, Kristiina Korhonen, Pasi Sepponen, Antti Kotiaho, Vesa-Matti Pohjanen, and Miika Nieminen. "Virtual monochromatic imaging reduces beam hardening artefacts in cardiac interior photon counting computed tomography: a phantom study with cadaveric specimens." Biomedical Physics & Engineering Express 8, no. 1 (December 31, 2021): 015029. http://dx.doi.org/10.1088/2057-1976/ac4397.

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Abstract In interior cardiac computed tomography (CT) imaging, the x-ray beam is collimated to a limited field-of-view covering the heart volume, which decreases the radiation exposure to surrounding tissues. Spectral CT enables the creation of virtual monochromatic images (VMIs) through a computational material decomposition process. This study investigates the utility of VMIs for beam hardening (BH) reduction in interior cardiac CT, and further, the suitability of VMIs for coronary artery calcium (CAC) scoring and volume assessment is studied using spectral photon counting detector CT (PCD-CT). Ex vivo coronary artery samples (N = 18) were inserted in an epoxy rod phantom. The rod was scanned in the conventional CT geometry, and subsequently, the rod was positioned in a torso phantom and re-measured in the interior PCD-CT geometry. The total energy (TE) 10–100 keV reconstructions from PCD-CT were used as a reference. The low energy 10–60 keV and high energy 60–100 keV data were used to perform projection domain material decomposition to polymethyl methacrylate and calcium hydroxylapatite basis. The truncated basis-material sinograms were extended using the adaptive detruncation method. VMIs from 30–180 keV range were computed from the detruncated virtual monochromatic sinograms using filtered back projection. Detrending was applied as a post-processing method prior to CAC scoring. The results showed that BH artefacts from the exterior structures can be suppressed with high (≥100 keV) VMIs. With appropriate selection of the monoenergy (46 keV), the underestimation trend of CAC scores and volumes shown in Bland-Altman (BA) plots for TE interior PCD-CT was mitigated, as the BA slope values were −0.02 for the 46 keV VMI compared to −0.21 the conventional TE image. To conclude, spectral PCD-CT imaging using VMIs could be applied to reduce BH artefacts interior CT geometry, and further, optimal selection of VMI may improve the accuracy of CAC scoring assessment in interior PCD-CT.

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Hayashi, Daichi, Frank W. Roemer, Thomas Link, Xiaojuan Li, Feliks Kogan, Neil A. Segal, Patrick Omoumi, and Ali Guermazi. "Latest advancements in imaging techniques in OA." Therapeutic Advances in Musculoskeletal Disease 14 (January 2022): 1759720X2211466. http://dx.doi.org/10.1177/1759720x221146621.

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The osteoarthritis (OA) research community has been advocating a shift from radiography-based screening criteria and outcome measures in OA clinical trials to a magnetic resonance imaging (MRI)-based definition of eligibility and endpoint. For conventional morphological MRI, various semiquantitative evaluation tools are available. We have lately witnessed a remarkable technological advance in MRI techniques, including compositional/physiologic imaging and automated quantitative analyses of articular and periarticular structures. More recently, additional technologies were introduced, including positron emission tomography (PET)-MRI, weight-bearing computed tomography (CT), photon-counting spectral CT, shear wave elastography, contrast-enhanced ultrasound, multiscale X-ray phase contrast imaging, and spectroscopic photoacoustic imaging of cartilage. On top of these, we now live in an era in which artificial intelligence is increasingly utilized in medicine. Osteoarthritis imaging is no exception. Successful implementation of artificial intelligence (AI) will hopefully improve the workflow of radiologists, as well as the level of precision and reproducibility in the interpretation of images.

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Allphin, Alex J., Ali Mahzarnia, Darin P. Clark, Yi Qi, Zay Y. Han, Prajwal Bhandari, Ketan B. Ghaghada, Alexandra Badea, and Cristian T. Badea. "Advanced photon counting CT imaging pipeline for cardiac phenotyping of apolipoprotein E mouse models." PLOS ONE 18, no. 10 (October 5, 2023): e0291733. http://dx.doi.org/10.1371/journal.pone.0291733.

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Background Cardiovascular disease (CVD) is associated with the apolipoprotein E (APOE) gene and lipid metabolism. This study aimed to develop an imaging-based pipeline to comprehensively assess cardiac structure and function in mouse models expressing different APOE genotypes using photon-counting computed tomography (PCCT). Methods 123 mice grouped based on APOE genotype (APOE2, APOE3, APOE4, APOE knockout (KO)), gender, human NOS2 factor, and diet (control or high fat) were used in this study. The pipeline included PCCT imaging on a custom-built system with contrast-enhanced in vivo imaging and intrinsic cardiac gating, spectral and temporal iterative reconstruction, spectral decomposition, and deep learning cardiac segmentation. Statistical analysis evaluated genotype, diet, sex, and body weight effects on cardiac measurements. Results Our results showed that PCCT offered high quality imaging with reduced noise. Material decomposition enabled separation of calcified plaques from iodine enhanced blood in APOE KO mice. Deep learning-based segmentation showed good performance with Dice scores of 0.91 for CT-based segmentation and 0.89 for iodine map-based segmentation. Genotype-specific differences were observed in left ventricular volumes, heart rate, stroke volume, ejection fraction, and cardiac index. Statistically significant differences were found between control and high fat diets for APOE2 and APOE4 genotypes in heart rate and stroke volume. Sex and weight were also significant predictors of cardiac measurements. The inclusion of the human NOS2 gene modulated these effects. Conclusions This study demonstrates the potential of PCCT in assessing cardiac structure and function in mouse models of CVD which can help in understanding the interplay between genetic factors, diet, and cardiovascular health.

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Lowe, Chiara, Ana Ortega-Gil, Mahdieh Moghiseh, Nigel G. Anderson, Arrate Munoz-Barrutia, Juan Jose Vaquero, Aamir Y. Raja, et al. "Molecular Imaging of Pulmonary Tuberculosis in an Ex-Vivo Mouse Model Using Spectral Photon-Counting Computed Tomography and Micro-CT." IEEE Access 9 (2021): 67201–8. http://dx.doi.org/10.1109/access.2021.3076432.

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Kang, Sooncheol, Jisoo Eom, Burnyoung Kim, and Seungwan Lee. "Evaluation of gold K-edge imaging using spectral computed tomography with a photon-counting detector: A Monte Carlo simulation study." Optik 140 (July 2017): 253–60. http://dx.doi.org/10.1016/j.ijleo.2017.04.062.

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Dillinger, Daniel, Daniel Overhoff, Christian Booz, Hanns L. Kaatsch, Joel Piechotka, Achim Hagen, Matthias F. Froelich, Thomas J. Vogl, and Stephan Waldeck. "Impact of CT Photon-Counting Virtual Monoenergetic Imaging on Visualization of Abdominal Arterial Vessels." Diagnostics 13, no. 5 (March 1, 2023): 938. http://dx.doi.org/10.3390/diagnostics13050938.

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Purpose: The novel photon-counting detector (PCD) technique acquires spectral data for virtual monoenergetic imaging (VMI) in every examination. The aim of this study was the evaluation of the impact of VMI of abdominal arterial vessels on quantitative and qualitative subjective image parameters. Methods: A total of 20 patients that underwent an arterial phase computed tomography (CT) scan of the abdomen with a novel PCD CT (Siemens NAEOTOM alpha) were analyzed regarding attenuation at different energy levels in virtual monoenergetic imaging. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated and compared between the different virtual monoenergetic (VME) levels with correlation to vessel diameter. In addition, subjective image parameters (overall subjective image quality, subjective image noise and vessel contrast) were evaluated. Results: Our research showed decreasing attenuation levels with increasing energy levels in virtual monoenergetic imaging regardless of vessel diameter. CNR showed best overall results at 60 keV, and SNR at 70 keV with no significant difference to 60 keV (p = 0.294). Subjective image quality was rated best at 70 keV for overall image quality, vessel contrast and noise. Conclusions: Our data suggest that VMI at 60–70 keV provides the best objective and subjective image quality concerning vessel contrast irrespective of vessel size.

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Smith, Kevin, Matthew Getzin, Josephine J. Garfield, Sanika Suvarnapathaki, Gulden Camci-Unal, Ge Wang, and Manos Gkikas. "Nanophosphor-Based Contrast Agents for Spectral X-ray Imaging." Nanomaterials 9, no. 8 (July 30, 2019): 1092. http://dx.doi.org/10.3390/nano9081092.

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Lanthanide-based nanophosphors (NPhs) are herein developed as contrast agents for spectral X-ray imaging, highlighting the chemical, macromolecular and structural differences derived from ligand exchange on computed tomography (CT) and solvent dispersibility. Taking advantage of the ability of spectral X-ray imaging with photon-counting detectors to perform image acquisition, analysis, and processing at different energy windows (bins), enhanced signal of our K-edge materials was derived, improving sensitivity of CT imaging, and differentiation between water, tumor-mimic phantoms, and contrast materials. Our results indicate that the most effective of our oleic acid-stabilized K-edge nanoparticles can achieve 2–4x higher contrast than the examined iodinated molecules, making them suitable for deep tissue imaging of tissues or tumors. On the other hand, ligand exchange yielding poly(acrylic acid)-stabilized K-edge nanoparticles allows for high dispersibility and homogeneity in water, but with a lower contrast due to the high density of the polymer grafted, unless further engineering is probed. This is the first well-defined study that manages to correlate NPh grafting density with CT numbers and water dispersibility, laying the groundwork for the development of the next generation CT-guided diagnostic and/or theranostic materials.

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Tóth, Adrienn, Jordan H. Chamberlin, Salvador Mendez, Akos Varga-Szemes, and Andrew D. Hardie. "Iodine quantification of renal lesions: Preliminary results using spectral-based material extraction on photon-counting CT." Journal of Clinical Imaging Science 14 (March 8, 2024): 7. http://dx.doi.org/10.25259/jcis_1_2024.

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Objectives: To assess the range of quantitative iodine values in renal cysts (RC) (with a few renal neoplasms [RNs] as a comparison) to develop an expected range of values for RC that can be used in future studies for their differentiation. Material and Methods: Consecutive patients (n = 140) with renal lesions who had undergone abdominal examination on a clinical photon-counting computed tomography (PCCT) were retrospectively included. Automated iodine quantification maps were reconstructed, and region of interest (ROI) measurements of iodine concentration (IC) (mg/cm3) were performed on whole renal lesions. In addition, for heterogeneous lesions, a secondary ROI was placed on the area most suspicious for malignancy. The discriminatory values of minimum, maximum, mean, and standard deviation for IC were compared using simple logistic regression and receiver operating characteristic curves (area under the curve [AUC]). Results: A total of 259 renal lesions (243 RC and 16 RN) were analyzed. There were significant differences between RC and RN for all IC measures with the best-performing metrics being mean and maximum IC of the entire lesion ROI (AUC 0.912 and 0.917, respectively) but also mean and minimum IC of the most suspicious area in heterogeneous lesions (AUC 0.983 and 0.992, respectively). Most RC fell within a range of low measured iodine values although a few had higher values. Conclusion: Automated iodine quantification maps reconstructed from clinical PCCT have a high diagnostic ability to differentiate RCs and neoplasms. The data from this pilot study can be used to help establish quantitative values for clinical differentiation of renal lesions.

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Sadeghian, Maryam, Parisa Akhlaghi, and Asghar Mesbahi. "Investigation of imaging properties of novel contrast agents based on gold, silver and bismuth nanoparticles in spectral computed tomography using Monte Carlo simulation." Polish Journal of Medical Physics and Engineering 26, no. 1 (March 1, 2020): 21–29. http://dx.doi.org/10.2478/pjmpe-2020-0003.

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AbstractIn the present paper, some imaging properties of nanoparticles-based contrast agents including gold, bismuth, and silver were assessed and compared with conventional (iodinated) contrast agent in spectral computed tomography (CT). A spectral CT scanner with photon-counting detectors (PCD) and 6 energy bins was simulated using the Monte Carlo (MC) simulation method. The nanoparticles were designed with a diameter of 50 nm at concentrations of 2, 4, and 8 mg/ml. Water-filled cylindrical phantom was modeled with a diameter of 10 cm containing a hole with a diameter of 5 cm in its center, where was filled with contrast agents. The MC results were used to reconstruct images. Image reconstruction was accomplished with the filtered back-projection (FBP) method with hamming filter and linear interpolation method. CT number and contrast-to-noise ratio (CNR) of all studied contrast materials were calculated in spectral images. The simulations indicated that nanoparticle-based contrast agents have a higher CT number and CNR than the iodinated contrast agent at the same concentration and for all energy bins. In general, gold nanoparticles produced the highest CT number and CNR compared to silver and bismuth nanoparticles at the same concentration. However, at low energies (below 80 keV), silver nanoparticles performed similarly to gold nanoparticles and at high energies (120 keV), bismuth nanoparticles can be a good substitute for gold nanoparticles.

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Pipek, Jindřich, Roman Grill, Marián Betušiak, and Kris Iniewski. "Modelling Polarization Effects in a CdZnTe Sensor at Low Bias." Sensors 23, no. 12 (June 17, 2023): 5681. http://dx.doi.org/10.3390/s23125681.

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Semi-insulating CdTe and CdZnTe crystals fabricated into pixelated sensors and integrated into radiation detection modules have demonstrated a remarkable ability to operate under rapidly changing X-ray irradiation environments. Such challenging conditions are required by all photon-counting-based applications, including medical computed tomography (CT), airport scanners, and non-destructive testing (NDT). Although, maximum flux rates and operating conditions differ in each case. In this paper, we investigated the possibility of using the detector under high-flux X-ray irradiation with a low electric field satisfactory for maintaining good counting operation. We numerically simulated electric field profiles visualized via Pockels effect measurement in a detector affected by high-flux polarization. Solving coupled drift–diffusion and Poisson’s equations, we defined the defect model, consistently depicting polarization. Subsequently, we simulated the charge transport and evaluated the collected charge, including the construction of an X-ray spectrum on a commercial 2-mm-thick pixelated CdZnTe detector with 330 µm pixel pitch used in spectral CT applications. We analyzed the effect of allied electronics on the quality of the spectrum and suggested setup optimization to improve the shape of the spectrum.