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01-09-2010 | Computed Tomography

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

Authors: 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

Published in: European Radiology | Issue 9/2010

Abstract

Objective

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.

Methods

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.

Results

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.

Conclusion

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

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 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4179477&isnumber=4179395 CrossRef

Roessl E, Proksa R (2007) K-edge imaging in x-ray computed tomography using multi-bin photon counting detectors. Phys Med Biol 52:4679–4696CrossRefPubMed

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 607:179–192CrossRef

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 42:263–273CrossRefPubMed

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

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 http://physics.nist.gov/PhysRefData/XrayMassCoef/cover.html. Accessed 22 April 2009

Achenbach S, Anders K, Kalender WA (2008) Dual-source cardiac computed tomography: image quality and dose considerations. Eur Radiol 18:1188–1198CrossRefPubMed

Brenner DJ, Hall EJ (2007) Computed tomography—an increasing source of radiation exposure. N Engl J Med 357:2277–2284CrossRefPubMed

Graser A, Johnson TR, Chandarana H, Macari M (2009) Dual energy CT: preliminary observations and potential clinical applications in the abdomen. Eur Radiol 19:13–23CrossRefPubMed

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–49:2279CrossRef

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 54:1824CrossRef

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 155:1053–1058PubMed

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 31:300–306CrossRefPubMed

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 591:141–146CrossRef

15.

Dierick M, Masschaele B, Van Hoorebeke L (2004) Octopus, a fast and user-friendly tomographic reconstruction package developed in LabView®. Meas Sci Technol 15:1366–1370CrossRef

16.

Jolliffe IT (2002) Principal component analysis. Springer Series in Statistics, 2nd edn. Springer, New York

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.

OpenSceneGraph. Available via http://www.openscenegraph.org/

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 591:19–23CrossRef

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 223:319–325CrossRefPubMed

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 2:234–242CrossRefPubMed

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 13:636–641CrossRefPubMed

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 29:1739–1751CrossRefPubMed

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 460:50–54CrossRef

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 8:3715–3723CrossRefPubMed

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 8:4593–4596CrossRefPubMed

27.

Karcaaltincaba M, Akhan O (2007) Imaging of hepatic steatosis and fatty sparing. Eur J Radiol 61:33–43CrossRefPubMed

28.

Mather ML, Morgan SP, Crowe JA (2007) Meeting the needs of monitoring in tissue engineering. Regen Med 2:145–160CrossRefPubMed

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 33:904–915

30.

Brunner FC, Clemens JC, Hemmer C, Morel C (2009) Imaging performance of the hybrid pixel detectors XPAD3-S. Phys Med Biol 54(6):1773–1789CrossRefPubMed

31.

Karg J, Niederlohner D, Giersch J, Anton G (2004) The energy weighting technique: measurements and simulations. Nucl Instrum Methods Phys Res A 531:68–74CrossRef

32.

Schmidt TG (2009) Optimal “image-based” weighting for energy-resolved CT. Med Phys 36:3018–3027CrossRefPubMed

Title: Spectroscopic (multi-energy) CT distinguishes iodine and barium contrast material in MICE
Authors: 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
Publication date: 01-09-2010
Publisher: Springer-Verlag
Published in: European Radiology / Issue 9/2010
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-010-1768-9

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Objective

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objective

Methods

Results

Conclusion

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