Share Email Print

Proceedings Paper

Estimating breast thickness for dual-energy subtraction in contrast-enhanced digital mammography using calibration phantoms
Author(s): Kristen C. Lau; Young Joon Kwon; Moez Karim Aziz; Raymond J. Acciavatti; Andrew D. A. Maidment
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Dual-energy contrast-enhanced digital mammography (DE CE-DM) uses an iodinated contrast agent to image the perfusion and vasculature of the breast. DE images are obtained by a weighted logarithmic subtraction of the high-energy (HE) and low-energy (LE) image pairs. We hypothesized that the optimal DE subtraction weighting factor is thickness-dependent, and developed a method for determining breast tissue composition and thickness in DE CE-DM. Phantoms were constructed using uniform blocks of 100% glandular-equivalent and 100% adipose-equivalent material. The thickness of the phantoms ranged from 3 to 8 cm, in 1 cm increments. For a given thickness, the glandular-adipose composition of the phantom was varied using different combinations of blocks. The logarithmic LE and logarithmic HE signal intensities were measured; they decrease linearly with increasing glandularity for a given thickness. The signals decrease with increasing phantom thickness and the x-ray signal decreases linearly with thickness for a given glandularity. As the thickness increases, the attenuation difference per additional glandular block decreases, indicating beam hardening. From the calibration mapping, we have demonstrated that we can predict percent glandular tissue and thickness when given two distinct signal intensities. Our results facilitate the subtraction of tissue at the boundaries of the breast, and aid in discriminating between contrast agent uptake in glandular tissue and subtraction artifacts.

Paper Details

Date Published: 4 April 2016
PDF: 12 pages
Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 978307 (4 April 2016); doi: 10.1117/12.2214748
Show Author Affiliations
Kristen C. Lau, The Univ. of Pennsylvania Health System (United States)
Young Joon Kwon, The Univ. of Pennsylvania Health System (United States)
Moez Karim Aziz, The Univ. of Pennsylvania Health System (United States)
Raymond J. Acciavatti, The Univ. of Pennsylvania Health System (United States)
Andrew D. A. Maidment, The Univ. of Pennsylvania Health System (United States)

Published in SPIE Proceedings Vol. 9783:
Medical Imaging 2016: Physics of Medical Imaging
Despina Kontos; Thomas G. Flohr, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?