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Improving automatic contrast agent extraction system using monochromatic CT number

Australasian Physical & Engineering Sciences in Medicine volume 42, pages 819–826 (2019)Cite this article

Abstract

In a previous study, a phantom study of a contrast agent extraction system with computed tomography (CT) number and raw-data-based electron density (ED) was described. The current study improved this system with monochromatic CT (mCT) number and evaluated an anthropomorphic phantom for delineation of the contrast-enhanced region. Dual-energy CT images were scanned with a tissue-equivalent phantom and an anthropomorphic phantom with an iodinated contrast agent (1–130 mg/mL). The 40, 70, and 130 keV mCT images were reconstructed with 80 and 135 kV CT images. The contrast agent was separated from other materials using the gradient of the mCT number (GmCT) and the threshold mCT numbers. The system was analyzed using in-house software with Python. The evaluation of the accuracy for the contrast agent extraction was performed by measuring the ratio of the volume (ROV). The mCT number of the contrast agent and bone materials, liver, and muscle in the tissue-equivalent phantom was obviously greater than – 78 HU. The deviation of the mCT numbers between bone materials in tissue-equivalent phantom and the contrast agent were larger than 8 HU. The GmCT was within 4.0 in the tissue-equivalent phantom and more than 6.0 in the contrast agent. The ROV was 0.97–1.00 at more than 1 mg/mL contrast agent. Improved the contrast agent extraction system could be used for a patient’s CT image. It could extract the iodinated tumor or lesion automatically. The contrast agent extraction system was improved by the mCT number. It is expected to only extract the contrast-enhanced region automatically.

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References

  1. Kaemmerer N, Brand M, Hammon M, May M, Wuest W, Krauss B et al (2016) Dual-energy computed tomography angiography of the head and neck with single-source computed tomography: a new technical (split filter) approach for bone removal. Invest Radiol 51(10):618–623

    Article  PubMed  Google Scholar 

  2. Primak AN, Fletcher JG, Vrtiska TJ, Dzyubak OP, Lieske JC, Jackson ME et al (2007) Noninvasive differentiation of uric acid versus nonuric acid kidney stones using dual-energy CT. Acad Radiol 14:1441–1447

    Article  PubMed  PubMed Central  Google Scholar 

  3. Michalak G, Grimes J et al (2016) Improved CT number stability across patient size using dual-energy CT virtual monoenergetic imaging. Med Phys 43(1):513

    Article  PubMed  Google Scholar 

  4. Petersilka M, Bruder H, Krauss B et al (2008) Technical principles of dual source CT. Eur J Radiol 68:362–368

    Article  PubMed  Google Scholar 

  5. Meier A, Wurnig M, Desbiolles L, Leschka S et al (2015) Advanced virtual monoenergetic images: improving the contrast of dual-energy CT pulmonary angiography. Clin Radiol 70(11):1244–1251

    Article  CAS  PubMed  Google Scholar 

  6. Kawahara D, Ozawa S, Yokomachi K (2018) Accuracy of the raw-data-based effective atomic numbers and monochromatic CT numbers for contrast agent with a dual-energy CT technique. Br J Radiol 91(1082):20170524

    PubMed  PubMed Central  Google Scholar 

  7. Alvarez RE, Macovski A (1976) Energy-selective reconstructions in X-ray computerized tomography. Phys Med Biol 21(5):733–744

    Article  CAS  PubMed  Google Scholar 

  8. Bamberg F, Dierks A, Nikolaou K et al (2011) Metal artifact reduction by dual energy computed tomography using monoenergetic extrapolation. Eur Radiol 21:1424–1429

    Article  PubMed  Google Scholar 

  9. Yamada S, Ueguchi T, Shimosegawa E et al (2015) Feasibility of improved attenuation correction for SPECT reconstruction in the presence of dense materials using dual-energy virtual monochromatic CT: a phantom study. Open J Med Imaging 5:183–193

    Article  Google Scholar 

  10. Leng S, Yu L, Fletcher JG et al (2015) Maximizing iodine contrast-to-noise ratios in abdominal CT imaging through use of energy domain noise reduction and virtual monoenergetic dual-energy CT. Radiology 276:562–570

    Article  PubMed  PubMed Central  Google Scholar 

  11. Agrawal MD, Oliveira GR, Kalva SP et al (2016) Prospective comparison of reduced-iodine-dose virtual monochromatic imaging dataset from dualenergy CT angiography with standard-iodine-dose single-energy CT angiography for abdominal aortic aneurysm. AJR Am J Roentgenol 207:W125–W132

    Article  PubMed  Google Scholar 

  12. Kang M-J, Park CM, Lee C-H, Goo JM, Lee HJ (2010) Dual-energy CT: clinical applications in various pulmonary diseases. Radiographics 30(3):685–698

    Article  PubMed  Google Scholar 

  13. Yamada S, Ueguchi T, Ogata T (2014) Radiotherapy treatment planning with contrast-enhanced computed tomography: feasibility of dual-energy virtual unenhanced imaging for improved dose calculations. Radiat Oncol 29(9):168

    Article  Google Scholar 

  14. Kawahara D, Oawa S et al (2017) Dosimetric impact of lipiodol in stereotactic body radiation therapy on liver after trans-arterial chemoembolization. Med Phys 44(1):342–348

    Article  CAS  PubMed  Google Scholar 

  15. Kawahara D, Ozawa S, Tanaka S et al (2018) Automatic contrast agent extraction system using electron density data with dual-energy CT. Br J Radiol 9:20180396

    Article  Google Scholar 

  16. Kawahara D, Ozawa S, Yokomachi K et al (2018) Accuracy of the raw-data-based effective atomic numbers and monochromatic CT numbers for contrast agent with a dual-energy CT technique. Br J Radiol 91(1082):20170524

    PubMed  PubMed Central  Google Scholar 

  17. Yu L, Leng S, McCollough CH (2012) Dual-energy CT-based monochromatic imaging. AJR Am J Roentgenol 199(5 Suppl):S9–S15

    Article  PubMed  Google Scholar 

  18. Coursey CA, Nelson RC, Boll DT, Paulson EK, Ho LM, Neville AM, Marin D, Gupta RT, Schindera ST (2010) Dual-energy multidetector CT: how does it work, what can it tell us, and when can we use it in abdominopelvic imaging? Radiographics 30:1037–1055

    Article  PubMed  Google Scholar 

  19. Lastra T, Mule S, Millet I et al (2016) Applications of dual energy computed tomography in abdominal imaging. Diagn Interv Imaging 97(6):593–603

    Article  Google Scholar 

  20. Sverzellati N, Molinari F, Pirronti T (2007) New insights on COPD imaging via CT and MRI. Int J Chron Obstruct Pulmon Dis. 2(3):301–312

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Gkika E, Tanadini-Lang S, Kirste S et al (2017) Interobserver variability in target volume delineation of hepatocellular carcinoma: an analysis of the working group “stereotactic radiotherapy” of the German society for radiation oncology (DEGRO). Strahlenther Onkol 193(10):823–830

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Radiation Therapy Section, Division of Clinical Support, Hiroshima University Hospital, 1-2-3 Kasumi, Minami-ku, Hiroshima City, 734-8551, Japan

    Daisuke Kawahara, Kazushi Yokomachi, Chikako Fujioka & Masayoshi Mori

  2. Department of Radiation Oncology, Institute of Biomedical & Health Sciences, Hiroshima University, Hiroshima City, 734-8551, Japan

    Shuichi Ozawa & Yasushi Nagata

  3. Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima City, 732-0057, Japan

    Shuichi Ozawa & Yasushi Nagata

  4. Departments of Diagnostic Radiology and Radiology, Hiroshima University, Hiroshima City, 732-0057, Japan

    Toru Higaki

Authors
  1. Daisuke Kawahara
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  2. Shuichi Ozawa
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  3. Kazushi Yokomachi
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  4. Toru Higaki
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  5. Chikako Fujioka
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  6. Masayoshi Mori
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  7. Yasushi Nagata
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Correspondence to Daisuke Kawahara.

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The authors did not use the human or other animals. This study only used the phantom.

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Kawahara, D., Ozawa, S., Yokomachi, K. et al. Improving automatic contrast agent extraction system using monochromatic CT number. Australas Phys Eng Sci Med 42, 819–826 (2019). https://doi.org/10.1007/s13246-019-00762-5

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  • DOI: https://doi.org/10.1007/s13246-019-00762-5

Keywords

  • Monochromatic CT number
  • Dual-energy CT
  • Contrast agent