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Proceedings Paper

Intrinsic limitations on quantification accuracy of dual energy CT at low dose levels
Author(s): Juan P. Cruz-Bastida; Ran Zhang; Ke Li; Guang-Hong Chen
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Paper Abstract

Radiation dose is still a topic of concern in current computed tomography (CT) clinical practice. While dose reduction strategies have been developed and proven to provide acceptable imaging performance, a recent work1 have demonstrated that filtered-backprojection based CT will lead to inaccurate CT numbers at low dose levels. This conclusion suggest that dual energy CT (DECT) material decomposition at low dose levels may also be strongly biased. The purpose of this work was to systematically investigate the relationship between image-based DECT decomposition accuracy and the mA level. To achieve this goal, a Catphan phantom with different material inserts of known composition was scanned in a benchtop CT system with two different x-ray spectra (60 and 100 kV). Different tube current levels, ranging from 0.5 to 10 mAs were used, and 50 realizations per data set were acquired. Image domain material decomposition was performed with the acquired data, using acrylic and Teflon as material basis. The resulting decompositions were compared to reference values, obtained from the decomposition of averaged scans at a reference dose level. It was observed that both phantom composition and mA levels strongly impact the decomposition accuracy. Particularly, when either the low- or high- energy scan was acquired with a high mA level, a low mA level for the conjugate measurement led to biased decomposition estimates. Fundamentally different trends were identified when comparing decomposition -accuracy and -precision as function of the mA level. Our results also suggest that certain tube current combinations may be optimal in terms of accuracy.

Paper Details

Date Published: 9 March 2018
PDF: 7 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105734L (9 March 2018); doi: 10.1117/12.2293963
Show Author Affiliations
Juan P. Cruz-Bastida, Univ. of Wisconsin School of Medicine and Public Health (United States)
Ran Zhang, Univ. of Wisconsin School of Medicine and Public Health (United States)
Ke Li, Univ. of Wisconsin School of Medicine and Public Health (United States)
Guang-Hong Chen, Univ. of Wisconsin School of Medicine and Public Health (United States)

Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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