European Radiology

, Volume 20, Issue 9, pp 2126–2134 | Cite as

Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE

  • N. G. Anderson
  • A. P. Butler
  • N. J. A. Scott
  • N. J. Cook
  • J. S. Butzer
  • N. Schleich
  • M. Firsching
  • R. Grasset
  • N. de Ruiter
  • M. Campbell
  • P. H. Butler
Computed Tomography



Spectral CT differs from dual-energy CT by using a conventional X-ray tube and a photon-counting detector. We wished to produce 3D spectroscopic images of mice that distinguished calcium, iodine and barium.


We developed a desktop spectral CT, dubbed MARS, based around the Medipix2 photon-counting energy-discriminating detector. The single conventional X-ray tube operated at constant voltage (75 kVp) and constant current (150 µA). We anaesthetised with ketamine six black mice (C57BL/6). We introduced iodinated contrast material and barium sulphate into the vascular system, alimentary tract and respiratory tract as we euthanised them. The mice were preserved in resin and imaged at four detector energy levels from 12 keV to 42 keV to include the K-edges of iodine (33.0 keV) and barium (37.4 keV). Principal component analysis was applied to reconstructed images to identify components with independent energy response, then displayed in 2D and 3D.


Iodinated and barium contrast material was spectrally distinct from soft tissue and bone in all six mice. Calcium, iodine and barium were displayed as separate channels on 3D colour images at <55 µm isotropic voxels.


Spectral CT distinguishes contrast agents with K-edges only 4 keV apart. Multi-contrast imaging and molecular CT are potential future applications.


Medipix CT spectroscopy Spectral CT K-edge imaging Contrast material Photon counting detector 



We thank the Medipix2 and Medipix3 collaborations and European Organisation for Nuclear Research (CERN) for use of the Medipix detectors; Graeme Kershaw for fixing the mice in the resin; Judith Dawson for help preparing the manuscript; Steffi Girst for dose estimation.

This work was supported by FRST-Man grant PROJ-13860-NMTS-UOC.

This information was presented at the European Congress of Radiology, March, 2009


  1. 1.
    Firsching M, Niederlohner D, Michel T, Anton G (2006) Quantitative material reconstruction in CT with spectroscopic X-ray pixel detectors—a simulation study. IEEE Nucl Sci Symp Conf Rec 4:2257–2259 accessed at CrossRefGoogle Scholar
  2. 2.
    Roessl E, Proksa R (2007) K-edge imaging in x-ray computed tomography using multi-bin photon counting detectors. Phys Med Biol 52:4679–4696CrossRefPubMedGoogle Scholar
  3. 3.
    Firsching M, Butler AP, Scott N, Anderson NG, Michel T, Anton G (2009) Contrast agent recognition in small animal CT using the Medipix2 detector. Nucl Instrum Methods Phys Res A 607:179–192CrossRefGoogle Scholar
  4. 4.
    Langheinrich AC, Michniewicz A, Sedding DG, Lai B, Jorgensen SM, Bohle RM, Ritman EL (2007) Quantitative x-ray imaging of intraplaque hemorrhage in aortas of ApoE-/-/LDL-/- double knockout mice. Investigative Radiology 42:263–273CrossRefPubMedGoogle Scholar
  5. 5.
    Schültke E, Fiedler S, Nemoz C, Ogieglo L, Kelly ME, Crawford P, Esteve F, Brochard T, Renier M, Requardt H, Le Duc G, Juurlink B, Meguro K (2009) Synchrotron-based intra-venous K-edge digital subtraction angiography in a pig model: a feasibility study. Eur J Radiol, epub Feb 28, doi: 10.1016/j.ejrad.2009.01.019
  6. 6.
    Hubbell JH, Seltzer SM (eds) (1995) Tables of x-ray mass attenuation coefficients and mass-energy absorption coefficients. In: Physical Reference Data. NIST Standard Reference Database 126. Available via Accessed 22 April 2009
  7. 7.
    Achenbach S, Anders K, Kalender WA (2008) Dual-source cardiac computed tomography: image quality and dose considerations. Eur Radiol 18:1188–1198CrossRefPubMedGoogle Scholar
  8. 8.
    Brenner DJ, Hall EJ (2007) Computed tomography—an increasing source of radiation exposure. N Engl J Med 357:2277–2284CrossRefPubMedGoogle Scholar
  9. 9.
    Graser A, Johnson TR, Chandarana H, Macari M (2009) Dual energy CT: preliminary observations and potential clinical applications in the abdomen. Eur Radiol 19:13–23CrossRefPubMedGoogle Scholar
  10. 10.
    Llopart X, Campbell M, Dinapoli R, San Segundo D, Pernigotti E (2002) Medipix2, a 64 k pixel readout chip with 55 µm square elements working in single photon counting mode. IEEE Trans Nucl Sci NS–49:2279CrossRefGoogle Scholar
  11. 11.
    Ballabriga R, Campbell M, Heijne EHM, Llopart X, Tlustos L (2007) The medipix3 prototype, a pixel readout chip working in single photon counting mode with improved spectrometric performance. IEEE Trans Nucl Sci 54:1824CrossRefGoogle Scholar
  12. 12.
    Kelcz F, Peppler WW, Mistretta CA, DeSmet A, McBeath AA (1990) K-edge digital subtraction arthrography of the painful hip prosthesis: a feasibility study. AJR Am J Roentgenol 155:1053–1058PubMedGoogle Scholar
  13. 13.
    Melzer TR, Cook NJ, Butler AP, Watts R, Anderson N, Tipples R, Butler PH (2008) Spectroscopic biomedical imaging with the Medipix2 detector. Australas Phys Eng Sci Med 31:300–306CrossRefPubMedGoogle Scholar
  14. 14.
    Butler APH, Anderson NG, Tipples R, Cook N, Watts R, Meyer J, Bell AJ, Melzer TR, Butler PH (2008) Bio-medical X-ray imaging with spectroscopic pixel detectors. Nucl Instrum Methods Phys Res A 591:141–146CrossRefGoogle Scholar
  15. 15.
    Dierick M, Masschaele B, Van Hoorebeke L (2004) Octopus, a fast and user-friendly tomographic reconstruction package developed in LabView®. Meas Sci Technol 15:1366–1370CrossRefGoogle Scholar
  16. 16.
    Jolliffe IT (2002) Principal component analysis. Springer Series in Statistics, 2nd edn. Springer, New YorkGoogle Scholar
  17. 17.
    Butzer JS, Butler APH, Butler PH, Bones PJ, Cook N, Tlustos L (2008) Medipix imaging: evaluation of datasets with PCA. Image Vis Comput NZ, 23rd Int Conf Proc p1–6 doi: 10.1109/IVCNZ.2008.4762080
  18. 18.
    OpenSceneGraph. Available via
  19. 19.
    Firsching M, Talla PT, Michel T, Anton G (2008) Material resolving X-ray imaging using spectrum reconstruction with Medipix2. Nucl Instrum Methods Phys Res A 591:19–23CrossRefGoogle Scholar
  20. 20.
    Spinosa D, Kaufmann J, Hartwell G (2002) Gadolinium chelates in angiography and interventional radiology: a useful alternative to iodinated contrast media for angiography. Radiology 223:319–325CrossRefPubMedGoogle Scholar
  21. 21.
    Barreto M, Schoenhagen P, Nair A, Amatangelo S, Milite M, Obuchowski NA, Lieber ML, Halliburton SS (2008) Potential of dual-energy computed tomography to characterize atherosclerotic plaque: ex vivo assessment of human coronary arteries in comparison to histology. J Cardiovasc Comput Tomogr 2:234–242CrossRefPubMedGoogle Scholar
  22. 22.
    Hyafil F, Cornily JC, Feig JE, Gordon R, Vucic E, Amirbekian V, Fisher EA, Fuster V, Feldman LJ, Fayad ZA (2007) Noninvasive detection of macrophages using a nanoparticulate contrast agent for computed tomography. Nat Med 13:636–641CrossRefPubMedGoogle Scholar
  23. 23.
    Lemacks M, Kappadath S, Shaw C, Liu X, Whitman G (2002) A dual-energy subtraction technique for microcalcification imaging in digital mammography: a signal-to-noise analysis. Med Phys 29:1739–1751CrossRefPubMedGoogle Scholar
  24. 24.
    Amendoliaa S, Bisognib M, Bottiglib U, Cioccib M, Delogub P, Dipasqualec G, Fantaccib M, Maestrob P, Marzullib V, Mikulecd B, Pernigottib E, Rossob V, Stefaninib A, Stumbob S (2001) Test of a GaAs-based pixel device for digital mammography. Nucl Instrum Methods Phys Res A 460:50–54CrossRefGoogle Scholar
  25. 25.
    Cormode DP, Skajaa T, van Schooneveld MM, Koole R, Jarzyna P, Lobatto ME, Calcagno C, Barazza A, Gordon RE, Zanzonico P, Fisher EA, Fayad ZA, Mulder WJ (2008) Nanocrystal core high-density lipoproteins: a multimodality contrast agent platform. Nano Lett 8:3715–3723CrossRefPubMedGoogle Scholar
  26. 26.
    Popovtzer R, Agrawal A, Kotov NA, Popovtzer A, Balter J, Carey TE, Kopelman R (2008) Targeted gold nanoparticles enable molecular CT imaging of cancer. Nano Lett 8:4593–4596CrossRefPubMedGoogle Scholar
  27. 27.
    Karcaaltincaba M, Akhan O (2007) Imaging of hepatic steatosis and fatty sparing. Eur J Radiol 61:33–43CrossRefPubMedGoogle Scholar
  28. 28.
    Mather ML, Morgan SP, Crowe JA (2007) Meeting the needs of monitoring in tissue engineering. Regen Med 2:145–160CrossRefPubMedGoogle Scholar
  29. 29.
    Batchelar DL, Davidson MTM, Dabrowski W, Cunningham IA (2006) Bone composition imaging using coherent-scatter computed tomography. Assessing bone health beyond bone mineral density. Med Phys 33:904–915Google Scholar
  30. 30.
    Brunner FC, Clemens JC, Hemmer C, Morel C (2009) Imaging performance of the hybrid pixel detectors XPAD3-S. Phys Med Biol 54(6):1773–1789CrossRefPubMedGoogle Scholar
  31. 31.
    Karg J, Niederlohner D, Giersch J, Anton G (2004) The energy weighting technique: measurements and simulations. Nucl Instrum Methods Phys Res A 531:68–74CrossRefGoogle Scholar
  32. 32.
    Schmidt TG (2009) Optimal “image-based” weighting for energy-resolved CT. Med Phys 36:3018–3027CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2010

Authors and Affiliations

  • N. G. Anderson
    • 1
  • A. P. Butler
    • 1
    • 2
  • N. J. A. Scott
    • 3
  • N. J. Cook
    • 4
  • J. S. Butzer
    • 5
  • N. Schleich
    • 2
    • 4
  • M. Firsching
    • 6
  • R. Grasset
    • 7
  • N. de Ruiter
    • 7
  • M. Campbell
    • 8
  • P. H. Butler
    • 2
  1. 1.Department of RadiologyUniversity of OtagoChristchurchNew Zealand
  2. 2.Physics and AstronomyUniversity of CanterburyChristchurchNew Zealand
  3. 3.Department of MedicineUniversity of OtagoChristchurchNew Zealand
  4. 4.Medical Physics and BioengineeringChristchurch HospitalChristchurchNew Zealand
  5. 5.Physics DepartmentKarlsruhe Institute of TechnologyKarlsruheGermany
  6. 6.Physics DepartmentFriedrich Alexander UniversityErlangenGermany
  7. 7.Hitlab NZUniversity of CanterburyChristchurchNew Zealand
  8. 8.Physics SectionEuropean Organisation for Nuclear ResearchGenevaSwitzerland

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