Affiliations: Department of Radiation Safety, Cedars-Sinai Medical
Center, Los Angeles, CA, USA | Department of Imaging, Cedars-Sinai Medical Center,
Los Angeles, CA, USA | Department of Biomedical Sciences, Cedars-Sinai
Medical Center, Los Angeles, CA, USA
Note: [] Corresponding author: Yifang Zhou, Radiation Safety and Imaging,
TSB 190, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA. E-mail:
[email protected]
Abstract: To quantify the trade-offs of dose and image quality among
pre-loaded automatic exposure control (AEC) options in digital mammography, two
AEC tables from the Hologic Selenia digital mammography system were compared:
the default AEC "table 0" and AEC "table 1". Realistically-shaped phantoms
consisting of tissue-equivalent material of various thicknesses (4.5 cm–7
cm) were imaged to obtain a figure of merit (FOM), the squared
contrast-to-noise ratio per mean glandular dose. To relate the results to
pathological findings and to evaluate the overall performance, the measured
contrast-to-noise ratios were applied to simulated lesions on the
anthropomorphic breast phantom images, producing various lesion configurations
which were blindly scored. It was found that the AEC table 1 improves the low
contrast FOM by 11% to 20% for the breast thicknesses of 4.5–6 cm.
However, for the 7 cm thick breast, the AEC table 1 decreases the low contrast
FOM by 17%. For microcalcifications, the AEC table 1 improves the FOM slightly
for the breast thicknesses of 4.5--6 cm and decreases it by 18% at a thickness
of 7 cm. The lesion simulation showed enhanced contrast due to the AEC table 1
for the breast thicknesses of 5 cm, 6 cm, and 7 cm, but the enhancement
gradually reduces as the thickness increases. The lesion reading showed that
the microcalcification detection was scored significantly higher from the AEC
table 1 for the thicknesses 5 cm, 6 cm, and 7 cm. The corresponding improvement
of mass detection scores was also observed but not consistently significant
over the thickness range.
Keywords: Automatic exposure control, digital mammography, figure of merit, mean glandular dose, lesion simulation
