Abstract
We investigated the accuracy of the computed tomography (CT) numbers of virtual non-contrast (VNC) images for two different material decomposition algorithms using the same image data for different diluted contrast agent concentrations. A container filled with contrast agents was inserted into a cylindrical phantom and scanned with dual-energy protocols (80/Sn140 kV, 100/Sn140 kV) using a dual-source CT. VNC images were generated by the 2-material decomposition (MD) algorithm using the energy of each tube voltage and the linear attenuation coefficient, calculated from the theoretical spectral curve of the agent and the CT number of the image, respectively. Furthermore, VNC images using 3-material decomposition (3-MD) algorithm were produced by applying LiverVNC, an analysis parameter implemented in the scanner. The robustness of both the algorithms was verified by investigating the CT numbers of the agents in the VNC. The closer the CT number is to 0 HU, the more robust the algorithm. Without beam-hardening correction, the CT numbers increased with an increase in concentration in both the algorithms, maximal at 50 mg/ml concentration, with CT numbers of 38 HU for 2-MD, 86 HU for 3-MD. With correction, CT numbers were ± 10 HU or less for both the algorithms up to 30 mg/ml concentration, whereas, for concentrations above 40 mg/ml, the maximal averaged CT number was 12 HU for 2-MD, 22 HU for 3-MD. For both the algorithms, the accuracy of the CT numbers was maintained in the low-concentration range; parameter adjustment was necessary to maintain the accuracy at concentrations higher than clinically expected.
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Ananthakrishnan L, Duan X, Rajiah P, Soesbe TC, Lewis MA, Xi Y, Fielding JR, Lenkinski RE, Leyendecker JR, Abbara S. Phantom validation of spectral detector computed tomography–derived virtual monoenergetic, Virtual Noncontrast, and Iodine Quantification Images. J Comput Assist Tomogr. 2018;42:959–64.
Sauter AP, Muenzel D, Dangelmaier J, Braren R, Pfeiffer F, Rummeny EJ, Noël PB, Fingerle AA. Dual-layer spectral computed tomography: virtual non-contrast in comparison to true non-contrast images. Eur J Radiol. 2018;104:108–14.
Jacobsen MC, Schellingerhout D, Wood CA, Tamm EP, Godoy MC, Sun J, Cody DD. Intermanufacturer comparison of dual-energy CT iodine quantification and monochromatic attenuation: a phantom study. Radiology. 2017;287:224–34.
Wang Q, Shi G, Qi X, Fan X, Wang L. Quantitative analysis of the dual-energy CT virtual spectral curve for focal liver lesions characterization. Eur J Radiol. 2014;83:1759–64.
Hua CH, Shapira N, Merchant TE, Klahr P, Yagil Y. Accuracy of electron density, effective atomic number, and iodine concentration determination with a dual-layer dual-energy computed tomography system. Med Phys. 2018;45:2486–97.
Zhang LJ, Peng J, Wu SY, Wang ZJ, Wu XS, Zhou CS, Ji XM, Lu GM. Liver virtual non-enhanced CT with dual-source, dual-energy CT: a preliminary study. Eur Radiol. 2010;20:2257–64.
Graser A, Johnson TR, Chandarana H, Macari M. Dual energy CT: preliminary observations and potential clinical applications in the abdomen. Eur Radiol. 2009;19:13–23.
Shaida N, Bowden DJ, Barrett T, Godfrey EM, Taylor A, Winterbottom AP, See TC, Lomas DJ, Shaw AS. Acceptability of virtual unenhanced CT of the aorta as a replacement for the conventional unenhanced phase. Clin Radiol. 2012;67:461–7.
Santamaria-Pang A, Dutta S, Makrogiannis S, Hara A, Pavlicek W, Silva A, Thomsen B, Robertson S, Okerlund D, Langan DA, Bhotika R. Automated liver lesion characterization using fast kVp switching dual energy computed tomography imaging. In: Proc. SPIE 7624. Medical Imaging 2010: Computer-Aided Diagnosis. 76240V.
Graser A, Johnson TR, Hecht EM, Becker CR, Leidecker C, Staehler M, Stief CG, Hildebrandt H, Godoy MC, Finn ME, Stepansky F, Reiser MF, Macari M. Dual-energy CT in patients suspected of having renal masses: Can virtual nonenhanced images replace true nonenhanced images? Radiology. 2009;252:433–40.
Maaß C, Baer M, Kachelrieß M. Image-based dual energy CT using optimized precorrection functions: a practical new approach of material decomposition in image domain. Med Phys. 2009;36:3818–29.
Toepker M, Moritz T, Krauss B, Weber M, Euller G, Mang T, Wolf F, Herold CJ, Ringl H. Virtual non-contrast in second-generation, dual-energy computed tomography: reliability of attenuation values. Eur J Radiol. 2012;81:e398–405.
Takeuchi M, Kawai T, Ito M, Ogawa M, Ohashi K, Hara M, Shibamoto Y. Split-bolus CT-urography using dual-energy CT: Feasibility, image quality and dose reduction. Eur J Radiol. 2012;81:3160–5.
Goodsitt MM, Christodoulou EG, Larson SC. Accuracies of the synthesized monochromatic CT numbers and effective atomic numbers obtained with a rapid kVp switching dual energy CT scanner. Med Phys. 2011;38:2222–32.
Vetter JR, Holden JE. Correction for scattered radiation and other background signals in dual-energy computed tomography material thickness measurements. Med Phys. 1988;15:726–31.
Sato K, Kageyama R, Sawatani Y, Takano H, Kayano S, Takane Y, Saito H. Accuracy of spectral curves at different phantom sizes and iodine concentrations using dual-source dual-energy computed tomography. Phys Eng Sci Med. 2021;44:103–16.
Agostini A, Borgheresi A, Mari A, Floridi C, Bruno F, Carotti M, Schicchi N, Barile A, Maggi S, Giovagnoni A. Dual-energy CT: theoretical principles and clinical applications. Radiol Medica. 2019;124:1281–95.
Kalender WA, Perman WH, Vetter JR, Klotz E. Evaluation of a prototype dual-energy computed tomographic apparatus. I Phantom studies. Med Phys. 1986;13:334–9.
Kawai T, Takeuchi M, Hara M, Ohashi K, Suzuki H, Yamada K, Sugiyama Y, Shibamoto Y. Accuracy of iodine removal using dual-energy CT with or without a tin filter: an experimental phantom study. Acta Radiol. 2013;54:954–60.
Li JH, Du YM, Huang HM. Accuracy of dual-energy computed tomography for the quantification of iodine in a soft tissue-mimicking phantom. J Appl Clin Med Phys. 2015;16:418–26.
Johnson T, Fink C, Schönberg SO, Reiser MF. Dual energy CT in clinical practice. In: Krauss B, Schmidt B, Flohr TG, editors. Dual Source CT. Berlin: Springer; 2011. p. 10–20.
Krauss B, Grant KL, Schmidt BT, Flohr TG. The importance of spectral separation: an assessment of dual-energy spectral separation for quantitative ability and dose efficiency. Investig Radiol. 2015;50:114–8.
Zhang D, Li X, Liu B. Objective characterization of GE discovery CT750 HD scanner: gemstone spectral imaging mode. Med Phys. 2011;38:1178–88.
Bracco S.p.A. Iomeron prescribing infformation. Milan, Italy.
Berger MJ, Hubbell JH, Seltzer SM, Chang J, Coursey JS, Sukumar R, Zucker DS, Olsen K (2010) XCOM: Photon Cross Sections Database, NIST Standard Reference Database 8 (XGAM). http://physics.nist.gov/xcom. Accessed 10 Dec 2021.
American College of Radiology. Computed tomography quality control manual. ACR publication. 2017;74.
Kolossváry M, Szilveszte B, Karády J, Drobni ZD, Merkely B, Maurovich-Horvat P. Effect of image reconstruction algorithms on volumetric and radiomic parameters of coronary plaques. J Cardiovasc Comput Tomogr. 2019;13:325–30.
Engle KJ, Herrmann C, Zeitler G. X-ray scattering in single- and dual-source CT. Med Phys. 2007;35:318–32.
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Takane, Y., Sato, K., Kageyama, R. et al. Accuracy of virtual non-contrast images with different algorithms in dual-energy computed tomography. Radiol Phys Technol 15, 234–244 (2022). https://doi.org/10.1007/s12194-022-00668-0
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DOI: https://doi.org/10.1007/s12194-022-00668-0