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Proceedings Paper

Dependence of radiation dose on area and volumetric mammographic breast density estimation
Author(s): H. Jing; B. Keller; Jae Young Choi; R. Crescenzi; E. Conant; A. Maidment; D. Kontos
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Paper Abstract

Mammographic breast density is a strong risk factor for breast cancer. Studies on imaging dose in mammography have primarily focused on imaging quality and diagnostic accuracy, while little work has been done on understanding its effect on the estimation of breast density. Studies on the effect of dose on mammographic density estimation can be useful in dose reduction for the purpose of density estimation and monitoring. In this study, we investigate the dependence of percent area (PD%) and volumetric (VD%) breast density estimation on imaging dose using an anthropomorphic breast phantom (Rachel, Gammex). A set of digital mammograms were obtained with a GE Senographe 2000D FFDM system, using 220 unique combinations of different imaging physics, namely target/filter, kVp and mAs. Specifically, 8 different mAs settings were defined as corresponding to 10%, 20%, 40%, 70%, 100%, 150%, 200% and 300% of 1.8 mGy reference average glandular dose (AGD) for standard phototimed exposure. Breast density was estimated using fully-automated FDA-cleared software (Quantra v.2.0, Hologic Inc.). The obtained estimates were analyzed to study the effect of the imaging dose, using ANOVA and linear regression. Results show that there is a statistically significant dependence of density estimation on x-ray imaging dose (p-value=0.014 and <0.001 for PD% and VD%, respectively), while the actual variation of the estimation across the different levels of dose is relatively low (standard deviation of 2.87% and 0.66% for PD% and VD% respectively), the differences could be significant when breast density measures are used for risk estimation.

Paper Details

Date Published: 6 March 2013
PDF: 7 pages
Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 866827 (6 March 2013); doi: 10.1117/12.2007989
Show Author Affiliations
H. Jing, Perelman School of Medicine at the Univ. of Pennsylvania (United States)
B. Keller, Perelman School of Medicine at the Univ. of Pennsylvania (United States)
Jae Young Choi, Perelman School of Medicine at the Univ. of Pennsylvania (United States)
R. Crescenzi, Perelman School of Medicine at the Univ. of Pennsylvania (United States)
E. Conant, Perelman School of Medicine at the Univ. of Pennsylvania (United States)
A. Maidment, Perelman School of Medicine at the Univ. of Pennsylvania (United States)
D. Kontos, Perelman School of Medicine at the Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 8668:
Medical Imaging 2013: Physics of Medical Imaging
Robert M. Nishikawa; Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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