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Proceedings Paper

Computer simulation of the breast subcutaneous and retromammary tissue for use in virtual clinical trials
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Paper Abstract

Computer simulation of breast anatomy is an essential component of Virtual Clinical Trials, a preclinical approach to validate breast imaging systems. Realism of breast phantoms affects simulation studies and their acceptance among researchers. Previously, we developed a simulation of tissue compartments defined by the hierarchy of Cooper’s ligaments, based upon recursive partitioning using octrees. In this work, we optimize the simulation parameters to represent realistically the breast subcutaneous and retromammary tissue regions. As seen in clinical images, the subcutaneous and retromammary regions contain predominantly adipose tissue organized into relatively large compartments, as opposed to the predominantly glandular breast interior. To mimic such organization, we divided the phantom volume into “subcutaneous”, “retromammary”, and “interior” regions. Within each region, parameters controlling the size and orientation of tissue compartments were selected separately. In this preliminary study, we varied parameter values and calculated the corresponding average compartment volume in each region. The proposed method was evaluated using anatomic descriptors at both radiological and pathological spatial scales. We simulated the subcutaneous region as spanning 20% of the breast diameter, comparable to published analysis of breast CT images. We simulated tissue compartments with the average volume of 0.94 cm3, 0.89 cm3 and 0.31 cm3 in the subcutaneous, retromammary and interior regions, respectively. Those average volumes match within 12% the values reported from histological analysis. Future evaluation will include a comparison of simulated and clinical parenchymal descriptors. The proposed method will be extended to automate the parameter optimization, and simulate detailed spatial variation, to further improve the realism.

Paper Details

Date Published: 9 March 2017
PDF: 8 pages
Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101325C (9 March 2017); doi: 10.1117/12.2255099
Show Author Affiliations
Predrag R. Bakic, Univ. of Pennsylvania (United States)
David D. Pokrajac, Delaware State Univ. (United States)
Andrew D. A. Maidment, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 10132:
Medical Imaging 2017: Physics of Medical Imaging
Thomas G. Flohr; Joseph Y. Lo; Taly Gilat Schmidt, Editor(s)

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