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Characterization of adipose compartments in mastectomy CT images
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Paper Abstract

Anthropomorphic software breast phantoms are generated by simulating breast anatomy. Virtual Clinical Trial (VCT) tools are developed for evaluating novel imaging modalities, based on anthropomorphic breast phantoms. Simulation of breast anatomical structures requires informed selection of parameters, which is crucial for the simulation realism. Our goal is to optimize the parameter selection based upon the analysis of clinical images.

Adipose compartments defined by Cooper’s ligaments significantly contribute to breast image texture (parenchymal pattern) which affects image interpretation and lesion detection. We have investigated the distribution and orientation of compartments segmented from CT images of a mastectomy specimen. Ellipsoidal fitting was applied to 205 segmented compartments, by matching the moments of inertia. The goodness-of-fit was measured by calculating Dice coefficients. Compartment size, shape, and orientation were characterized by estimating the volume, axis ratio, and Euler’s angles of fitted ellipsoids. Potential correlations between estimated parameters were tested.

We found that the adipose compartments are well approximated with ellipsoids (average Dice coefficient of 0.79). The compartment size is correlated with the barycenter-chest wall distance (r=0.235, p-value<0.001). The goodness-of-fit to ellipsoids is correlated to the compartment shape (r=0.344, p-value<0.001). The shape is also correlated with barycenter coordinates. The compartment orientation is correlated to their size (Euler angle α: r=0.188, p-value=0.007; angle β: r=0.156, p-value=0.025) and the barycenter-chest wall distance (r=0.159, p-value=0.023). These results from the characterization of adipose compartments and the observed correlations could help improve the realism of simulated breast anatomy.

Paper Details

Date Published: 9 March 2018
PDF: 10 pages
Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 1057356 (9 March 2018); doi: 10.1117/12.2293706
Show Author Affiliations
Abdullah-Al-Zubaer Imran, Univ. of California, Los Angeles (United States)
Delaware State Univ. (United States)
Predrag R. Bakic, The Univ. of Pennsylvania (United States)
David D. Pokrajac, Delaware State Univ. (United States)

Published in SPIE Proceedings Vol. 10573:
Medical Imaging 2018: Physics of Medical Imaging
Joseph Y. Lo; Taly Gilat Schmidt; Guang-Hong Chen, Editor(s)

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