Paper
9 March 2018 Intrinsic limitations on quantification accuracy of dual energy CT at low dose levels
Juan P. Cruz-Bastida, Ran Zhang, Ke Li, Guang-Hong Chen
Author Affiliations +
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.
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Juan P. Cruz-Bastida, Ran Zhang, Ke Li, and Guang-Hong Chen "Intrinsic limitations on quantification accuracy of dual energy CT at low dose levels ", Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105734L (9 March 2018); https://doi.org/10.1117/12.2293963
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KEYWORDS
X-ray computed tomography

Dual energy imaging

Data acquisition

X-rays

Image filtering

Image quality

Medicine

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