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Proceedings Paper

Automatic insertion of simulated microcalcification clusters in a software breast phantom
Author(s): Varsha Shankla; David D. Pokrajac; Susan P. Weinstein; Michael DeLeo; Catherine Tuite; Robyn Roth; Emily F. Conant; Andrew D.A. Maidment; Predrag R. Bakic
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Paper Abstract

An automated method has been developed to insert realistic clusters of simulated microcalcifications (MCs) into computer models of breast anatomy. This algorithm has been developed as part of a virtual clinical trial (VCT) software pipeline, which includes the simulation of breast anatomy, mechanical compression, image acquisition, image processing, display and interpretation. An automated insertion method has value in VCTs involving large numbers of images. The insertion method was designed to support various insertion placement strategies, governed by probability distribution functions (pdf). The pdf can be predicated on histological or biological models of tumor growth, or estimated from the locations of actual calcification clusters. To validate the automated insertion method, a 2-AFC observer study was designed to compare two placement strategies, undirected and directed. The undirected strategy could place a MC cluster anywhere within the phantom volume. The directed strategy placed MC clusters within fibroglandular tissue on the assumption that calcifications originate from epithelial breast tissue. Three radiologists were asked to select between two simulated phantom images, one from each placement strategy. Furthermore, questions were posed to probe the rationale behind the observer’s selection. The radiologists found the resulting cluster placement to be realistic in 92% of cases, validating the automated insertion method. There was a significant preference for the cluster to be positioned on a background of adipose or mixed adipose/fibroglandular tissues. Based upon these results, this automated lesion placement method will be included in our VCT simulation pipeline.

Paper Details

Date Published: 19 March 2014
PDF: 12 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90331Z (19 March 2014); doi: 10.1117/12.2044337
Show Author Affiliations
Varsha Shankla, Univ. of Pennsylvania (United States)
David D. Pokrajac, Delaware State Univ. (United States)
Susan P. Weinstein, Univ. of Pennsylvania (United States)
Michael DeLeo, Univ. of Pennsylvania (United States)
Catherine Tuite, Univ. of Pennsylvania (United States)
Robyn Roth, Univ. of Pennsylvania (United States)
Emily F. Conant, Univ. of Pennsylvania (United States)
Andrew D.A. Maidment, Univ. of Pennsylvania (United States)
Predrag R. Bakic, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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