Population of 224 realistic human subject-based computational breast phantoms

Abstract

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230+ dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.

Toward 7T breast MRI clinical study: safety assessment using simulation of heterogeneous breast models in RF exposure

“…We adapted 9 MRI image-derived breast models (0.5-mm isotropic resolution) made available by the University of Wisconsin Cross-Disciplinary Electromagnetics Laboratory 39 and 9 CT image-derived breast models (0.35mm isotropic resolution) from the Carl E. Ravin Advanced Imaging Laboratories at Duke University. 40 All breast models were uncompressed and in the prone position; the set included models from all 4 BI-RADS classifications: a, b, c, and d. Dielectric properties were assigned from the IT'IS Foundation Database. 41 For quantitative analysis, we labeled the breast models by the volumetric fibroglandular tissue (FGT) percentage (FGT%).…”

High-resolution, anthropomorphic, computational breast phantom: fusion of rule-based structures with patient-based anatomy

“…[10], [31], [34], [35] For this study, 30 patient--based phantoms were generated from a new cohort of breast CT images. Theses phantoms were based on a new cohort of 140 patients acquired at the University of Massachusetts on a clinical breast CT system (Koning Corporation, West Henrietta, NY).…”

“…[27], [28] Built upon the original work of Li et al, [29] and improvements made by Segars et al, [30] our lab previously developed a new set of breast phantoms based on in vivo patient CT data to represent a larger number of intact breasts. [31] Although rule--based breast phantoms are more flexible and time--saving, patient--based phantoms have inherently higher realism. However, during the process of image acquisition, reconstruction, denoising, and segmentation, some of the finest details of breasts are lost in patient--based breast phantoms.…”

Anthropomorphic dual-lattice voxel models for optimizing image quality and dose

“…16,17 Due to limited access to specimens and because these do not represent whole, intact breasts, realistic computational breast phantoms were created based on human subjects via segmentation of in vivo breast CT imaging data. [18][19][20] These phantoms provide a large population of a wide range of breast types, volumes, and parenchymal patterns. 20 Since the main purpose of most of the existing whole-body anthropomorphic models is the computation of organ/tissue doses for ionizing radiation or electromagnetic fields, their resolution is generally in the order of a few millimeters.…”

“…[18][19][20] These phantoms provide a large population of a wide range of breast types, volumes, and parenchymal patterns. 20 Since the main purpose of most of the existing whole-body anthropomorphic models is the computation of organ/tissue doses for ionizing radiation or electromagnetic fields, their resolution is generally in the order of a few millimeters. Thus, they are not suited to simulate realistic images for which the desired resolution is of the order of micrometers.…”