The english version of the website is under development. Wherever text appears in Greek, it means it has not been translated yet.

Δημοσίευση

Dual-energy contrast-enhanced digital mammography: Glandular dose estimation using a Monte Carlo code and voxel phantom.

TitleDual-energy contrast-enhanced digital mammography: Glandular dose estimation using a Monte Carlo code and voxel phantom.
Publication TypeJournal Article
Year of Publication2015
AuthorsTzamicha, E., Yakoumakis E., Tsalafoutas I. A., Dimitriadis A., Georgiou E., Tsapaki V., & Chalazonitis A.
JournalPhys Med
Volume31
Issue7
Pagination785-91
Date Published2015 Nov
ISSN1724-191X
Abstract

PURPOSE: To estimate the mean glandular dose of contrast enhanced digital mammography, using the EGSnrc Monte Carlo code and female adult voxel phantom.METHODS: Automatic exposure control of full field digital mammography system was used for the selection of the X-ray spectrum and the exposure settings for dual energy imaging. Measurements of the air-kerma and of the half value layers were performed and a Monte Carlo simulation of the digital mammography system was used to compute the mean glandular dose, for breast phantoms of various thicknesses, glandularities and for different X-ray spectra (low and high energy).RESULTS: For breast phantoms of 2.0-8.0 cm thick and 0.1-100% glandular fraction, CC view acquisition, from AEC settings, can result in a mean glandular dose of 0.450 ± 0.022 mGy -2.575 ± 0.033 mGy for low energy images and 0.061 ± 0.021 mGy - 0.232 ± 0.033 mGy for high energy images. In MLO view acquisition mean glandular dose values ranged between 0.488 ± 0.007 mGy - 2.080 ± 0.021 mGy for low energy images and 0.065 ± 0.012 mGy - 0.215 ± 0.010 mGy for high energy images.CONCLUSION: The low kV part of contrast enhanced digital mammography is the main contributor to total mean glandular breast dose. The results of this study can be used to provide an estimated mean glandular dose for individual cases.

DOI10.1016/j.ejmp.2015.03.013
Alternate JournalPhys Med
PubMed ID25900891

Contact

Secretariat of the School of Medicine
 

Connect

School of Medicine's presence in social networks
Follow Us or Connect with us.