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Proceedings Paper

Two methods for simulation of dense tissue distribution in software breast phantoms
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Paper Abstract

Software breast phantoms have been developed for use in evaluation of novel breast imaging systems. Software phantoms are flexible allowing the simulation of wide variations in breast anatomy, and provide ground truth for the simulated tissue structures. Different levels of phantom realism are required depending on the intended application. Realistic simulation of dense (fibroglandular) tissue is of particular importance; the properties of dense tissue – breast percent density and the spatial distribution – have been related to the risk of breast cancer. In this work, we have compared two methods for simulation of dense tissue distribution in a software breast phantom previously developed at the University of Pennsylvania. The methods compared are: (1) the previously used Gaussian distribution centered at the phantom nipple point, and (2) the proposed combination of two Beta functions, one modeling the dense tissue distribution along the chest wall-to-nipple direction, and the other modeling the radial distribution in each coronal section of the phantom. Dense tissue distributions obtained using these methods have been compared with distributions reported in the literature estimated from the analysis of breast CT images. Qualitatively, the two methods produced rather similar dense tissue distributions. The simulation based upon the use of Beta functions provides more control over the simulated distributions through the selection of the various Beta function parameters. Both methods showed good agreement to the clinical data, suggesting both provide a high level of realism.

Paper Details

Date Published: 19 March 2013
PDF: 10 pages
Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 86680M (19 March 2013); doi: 10.1117/12.2008104
Show Author Affiliations
Joseph H. Chui, Univ. of Pennsylvania (United States)
Rongping Zeng, US Food and Drug Administration (United States)
David D. Pokrajac, Delaware State Univ. (United States)
Subok Park, US Food and Drug Administration (United States)
Kyle J. Myers, US Food and Drug Administration (United States)
Andrew D. A. Maidment, Univ. of Pennsylvania (United States)
Predrag R. Bakic, 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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