Physics of Medical Imaging

Investigation of x-ray spectra for iodinated contrast-enhanced dedicated breast CT

[+] Author Affiliations
Stephen J. Glick, Andrey Makeev

US Food and Drug Administration, Center for Devices and Radiological Health, Silver Spring, Maryland, United States

J. Med. Imag. 4(1), 013504 (Jan 26, 2017). doi:10.1117/1.JMI.4.1.013504
History: Received August 25, 2016; Accepted January 4, 2017
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Abstract.  Screening for breast cancer with mammography has been very successful, resulting in part to a reduction of breast cancer mortality by approximately 39% since 1990. However, mammography still has limitations in performance, especially for women with dense breast tissue. Iodinated contrast-enhanced, dedicated breast CT (BCT) has been proposed to improve lesion analysis and the accuracy of diagnostic workup for patients suspected of having breast cancer. A mathematical analysis to explore the use of various x-ray filters for iodinated contrast-enhanced BCT is presented. To assess task-based performance, the ideal linear observer signal-to-noise ratio (SNR) is used as a figure-of-merit under the assumptions of a linear, shift-invariant imaging system. To estimate signal and noise propagation through the BCT detector, a parallel-cascade model was used. The lesion model was embedded into a structured background and included a realistic level of iodine uptake. SNR was computed for 84,000 different exposure settings by varying the kV setting, x-ray filter materials and thickness, breast size, and composition and radiation dose. It is shown that some x-ray filter material/thickness combinations can provide up to 75% improvement in the linear ideal observer SNR over a conventionally used x-ray filter for BCT. This improvement in SNR can be traded off for substantial reductions in mean glandular dose.

Figures in this Article
© 2017 Society of Photo-Optical Instrumentation Engineers

Topics

Breast ; X-rays ; Sensors

Citation

Stephen J. Glick and Andrey Makeev
"Investigation of x-ray spectra for iodinated contrast-enhanced dedicated breast CT", J. Med. Imag. 4(1), 013504 (Jan 26, 2017). ; http://dx.doi.org/10.1117/1.JMI.4.1.013504


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