Automatic insertion of simulated microcalcification clusters in a software breast phantom

Varsha Shankla; David D. Pokrajac; Susan P. Weinstein; Michael DeLeo; Catherine Tuite; Robyn Roth; Emily F. Conant M.D.; Andrew D.A. Maidment; Predrag R. Bakic

doi:10.1117/12.2044337

19 March 2014 Automatic insertion of simulated microcalcification clusters in a software breast phantom

Varsha Shankla, David D. Pokrajac, Susan P. Weinstein, Michael DeLeo, Catherine Tuite, Robyn Roth, Emily F. Conant M.D., Andrew D.A. Maidment, Predrag R. Bakic

Author Affiliations +

Proceedings Volume 9033, Medical Imaging 2014: Physics of Medical Imaging; 90331Z (2014) https://doi.org/10.1117/12.2044337
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

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.

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Varsha Shankla, David D. Pokrajac, Susan P. Weinstein, Michael DeLeo, Catherine Tuite, Robyn Roth, Emily F. Conant M.D., Andrew D.A. Maidment, and Predrag R. Bakic "Automatic insertion of simulated microcalcification clusters in a software breast phantom", Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90331Z (19 March 2014); https://doi.org/10.1117/12.2044337

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