Literature DB >> 31215659

Feasibility of multi-contrast imaging on dual-source photon counting detector (PCD) CT: An initial phantom study.

Shengzhen Tao1, Kishore Rajendran1, Cynthia H McCollough1, Shuai Leng1.   

Abstract

PURPOSE: Photon-counting-detector-computed tomography (PCD-CT) allows separation of multiple, simultaneously imaged contrast agents, such as iodine (I), gadolinium (Gd), and bismuth (Bi). However, PCDs suffer from several technical limitations such as charge sharing, K-edge escape, and pulse pile-up, which compromise spectral separation of multi-energy data and degrade multi-contrast imaging performance. The purpose of this work was to determine the performance of a dual-source (DS) PCD-CT relative to a single-source (SS) PCD-CT for the separation of simultaneously imaged I, Gd, and Bi contrast agents.
METHODS: Phantom experiments were performed using a research whole-body PCD-CT and head/abdomen-sized phantoms containing vials of different I, Gd, Bi concentrations. To emulate a DS-PCD-CT, the phantoms were scanned twice on the SS-PCD-CT using different tube potentials for each scan. A tube potential of 80 kV (energy thresholds = 25/50 keV) was used for low-energy tube, while the high-energy tube used Sn140 kV (Sn indicates tin filter) and thresholds of 25/90 keV. The same phantoms were scanned also on the SS-PCD-CT using the chess acquisition mode. In chess mode, the 4 × 4 subpixels within a macro detector pixel are split into two sets based on a chess-board pattern. With each subpixel set having two energy thresholds, chess mode allows four energy-bin data sets, which permits simultaneous multi-contrast imaging. Because of this design, only 50% area of each detector pixel is configured to receive photons of a pre-defined threshold, leading to 50% dose utilization efficiency. To compensate for this dose inefficiency, the radiation dose for this scan was doubled compared to DS-PCD-CT. A 140 kV tube potential and thresholds = 25/50/75/90 keV were used. These settings were determined based on the K-edges of Gd, and Bi, and were found to yield good differentiation of I/Gd/Bi based on phantom experiments and other literature. The energy-bin images obtained from each scan (scan pair) were used to generate I-, Gd-, Bi-specific image via material decomposition. Root-mean-square-error (RMSE) between the known and measured concentrations was calculated for each scenario. A 20-cm water cylinder phantom was scanned on both systems, which was used for evaluating the magnitude of noise, and noise power spectra (NPS) of I/Gd/Bi-specific images.
RESULTS: Phantom results showed that DS-PCD-CT reduced noise in material-specific images for both head and body phantoms compared to SS-PCD-CT. The noise level of SS-PCD was reduced from 2.55 to 0.90 mg/mL (I), 1.97 to 0.78 mg/mL (Gd), and 0.85 to 0.74 mg/mL (Bi) using DS-PCD. NPS analysis showed that the noise texture of images acquired on both systems is similar. For the body phantom, the RMSE for SS-PCD-CT was reduced relative to DS-PCD-CT from 10.52 to 2.76 mg/mL (I), 7.90 to 2.01 mg/mL (Gd), and 1.91 to 1.16 mg/mL (Bi). A similar trend was observed for the head phantom: RMSE reduced from 2.59 (SS-PCD) to 0.72 (DS-PCD) mg/mL (I), 2.02 to 0.58 mg/mL (Gd), and 0.85 to 0.57 mg/mL (Bi).
CONCLUSION: We demonstrate the feasibility of performing simultaneous imaging of I, Gd, and Bi materials on DS-PCD-CT. Under the condition without cross scattering, DS-PCD reduced the RMSE for quantification of material concentration in relative to a SS-PCD-CT system using chess mode.
© 2019 American Association of Physicists in Medicine.

Entities:  

Keywords:  dual-source CT; multi-contrast imaging; multi-energy CT; photon counting detector; spectral CT

Mesh:

Substances:

Year:  2019        PMID: 31215659      PMCID: PMC6857531          DOI: 10.1002/mp.13668

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  62 in total

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3.  Joint Statistical Iterative Material Image Reconstruction for Spectral Computed Tomography Using a Semi-Empirical Forward Model.

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4.  Material decomposition with prior knowledge aware iterative denoising (MD-PKAID).

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6.  Iterative image-domain decomposition for dual-energy CT.

Authors:  Tianye Niu; Xue Dong; Michael Petrongolo; Lei Zhu
Journal:  Med Phys       Date:  2014-04       Impact factor: 4.071

7.  Dual-source dual-energy CT with additional tin filtration: Dose and image quality evaluation in phantoms and in vivo.

Authors:  Andrew N Primak; Juan Carlos Ramirez Giraldo; Christian D Eusemann; Bernhard Schmidt; Birgit Kantor; Joel G Fletcher; Cynthia H McCollough
Journal:  AJR Am J Roentgenol       Date:  2010-11       Impact factor: 3.959

8.  Strategies for scatter correction in dual source CT.

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9.  Multi-material decomposition using statistical image reconstruction for spectral CT.

Authors:  Yong Long; Jeffrey A Fessler
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10.  Computed Tomography Imaging of Solid Tumors Using a Liposomal-Iodine Contrast Agent in Companion Dogs with Naturally Occurring Cancer.

Authors:  Ketan B Ghaghada; Amy F Sato; Zbigniew A Starosolski; John Berg; David M Vail
Journal:  PLoS One       Date:  2016-03-31       Impact factor: 3.240

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  10 in total

1.  Radiation dose efficiency of multi-energy photon-counting-detector CT for dual-contrast imaging.

Authors:  Liqiang Ren; Kishore Rajendran; Cynthia H McCollough; Lifeng Yu
Journal:  Phys Med Biol       Date:  2019-12-13       Impact factor: 3.609

2.  Simultaneous dual-contrast imaging using energy-integrating detector multi-energy CT: An in vivo feasibility study.

Authors:  Zhongxing Zhou; Liqiang Ren; Kishore Rajendran; Felix E Diehn; Joel G Fletcher; Cynthia H McCollough; Lifeng Yu
Journal:  Med Phys       Date:  2022-01-27       Impact factor: 4.071

3.  Dual-Contrast Biphasic Liver Imaging With Iodine and Gadolinium Using Photon-Counting Detector Computed Tomography: An Exploratory Animal Study.

Authors:  Liqiang Ren; Nathan Huber; Kishore Rajendran; Joel G Fletcher; Cynthia H McCollough; Lifeng Yu
Journal:  Invest Radiol       Date:  2022-02-01       Impact factor: 6.016

4.  Photon Counting CT: Clinical Applications and Future Developments.

Authors:  Scott S Hsieh; Shuai Leng; Kishore Rajendran; Shengzhen Tao; Cynthia H McCollough
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-08-28

5.  Model-based three-material decomposition in dual-energy CT using the volume conservation constraint.

Authors:  Stephen Z Liu; Matthew Tivnan; Greg M Osgood; Jeffrey H Siewerdsen; J Webster Stayman; Wojciech Zbijewski
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6.  Grating-based Spectral CT using Small Angle X-ray Beam Deflections.

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7.  Spectral Photon Counting CT: Imaging Algorithms and Performance Assessment.

Authors:  Adam S Wang; Norbert J Pelc
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Review 8.  Photon-Counting Detector CT: Key Points Radiologists Should Know.

Authors:  Andrea Esquivel; Andrea Ferrero; Achille Mileto; Francis Baffour; Kelly Horst; Prabhakar Shantha Rajiah; Akitoshi Inoue; Shuai Leng; Cynthia McCollough; Joel G Fletcher
Journal:  Korean J Radiol       Date:  2022-09       Impact factor: 7.109

9.  Threshold-dependent iodine imaging and spectral separation in a whole-body photon-counting CT system.

Authors:  S Sawall; L Klein; E Wehrse; L T Rotkopf; C Amato; J Maier; H-P Schlemmer; C H Ziener; S Heinze; M Kachelrieß
Journal:  Eur Radiol       Date:  2021-03-13       Impact factor: 5.315

10.  Simultaneous Dual-Contrast Imaging of Small Bowel With Iodine and Bismuth Using Photon-Counting-Detector Computed Tomography: A Feasibility Animal Study.

Authors:  Liqiang Ren; Kishore Rajendran; Joel G Fletcher; Cynthia H McCollough; Lifeng Yu
Journal:  Invest Radiol       Date:  2020-10       Impact factor: 10.065

  10 in total

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