Quantitative imaging of chemical composition using dual-energy, dual-source CT

Xin Liu; Andrew N. Primak; Lifeng Yu; Cynthia H. McCollough; Richard L. Morin

doi:10.1117/12.773042

25 March 2008 Quantitative imaging of chemical composition using dual-energy, dual-source CT

Xin Liu, Andrew N. Primak, Lifeng Yu, Cynthia H. McCollough, Richard L. Morin

Proceedings Volume 6913, Medical Imaging 2008: Physics of Medical Imaging; 69134Z (2008) https://doi.org/10.1117/12.773042
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Dual-energy x-ray material decomposition has been proposed as a noninvasive quantitative imaging technique for more than 20 years. In this paper, we summarize previously developed dual-energy material decomposition methods and propose a simple yet accurate method for quantitatively measuring chemical composition in vivo. In order to take advantage of the newly developed dual-source CT, the proposed method is based upon post reconstruction (image space) data. Different from other post reconstruction methods, this method is designed to directly measure element composition (mass fraction) in a tissue by a simple table lookup procedure. The method has been tested in phantom studies and also applied to a clinical case. The results showed that this method is capable of accurately measuring elemental concentrations, such as iron in tissue, under low noise imaging conditions. The advantage of this method lies in its simplicity and fast processing times. We believe that this method can be applied clinically to measure the mass fraction of any chemical element in a two-material object, such as to quantify the iron overload in the liver (hemochromatosis). Further investigations on de-noising techniques, as well as clinical validation, are merited.

Citation Download Citation

Xin Liu, Andrew N. Primak, Lifeng Yu, Cynthia H. McCollough, and Richard L. Morin "Quantitative imaging of chemical composition using dual-energy, dual-source CT", Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69134Z (25 March 2008); https://doi.org/10.1117/12.773042

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