Generation of voxelized breast phantoms from surgical mastectomy specimens

Abstract

Purpose:In the research and development of dedicated tomographic breast imaging systems, digital breast object models, also known as digital phantoms, are useful tools. While various digital breast phantoms do exist, the purpose of this study was to develop a realistic high-resolution model suitable for simulating three-dimensional (3D) breast imaging modalities. The primary goal was to design a model capable of producing simulations with realistic breast tissue structure. Methods: The methodology for generating an ensemble of digital breast phantoms was based on imaging surgical mastectomy specimens using a benchtop, cone-beam computed tomography system. This approach allowed low-noise, high-resolution projection views of the mastectomy specimens at each angular position. Reconstructions of these projection sets were processed using correction techniques and diffusion filtering prior to segmentation into breast tissue types in order to generate phantoms. Results: Eight compressed digital phantoms and 20 uncompressed phantoms from which an additional 96 pseudocompressed digital phantoms with voxel dimensions of 0.2 mm 3 were generated. Two distinct tissue classification models were used in forming breast phantoms. The binary model classified each tissue voxel as either adipose or fibroglandular. A multivalue scaled model classified each tissue voxel as percentage of adipose tissue (range 1%-99%). Power spectral analysis was performed to compare simulated reconstructions using the breast phantoms to the original breast specimen reconstruction, and fits were observed to be similar. Conclusions: The digital breast phantoms developed herein provide a high-resolution anthropomorphic model of the 3D uncompressed and compressed breast that are suitable for use in evaluating and optimizing tomographic breast imaging modalities. The authors believe that other research groups might find the phantoms useful, and therefore they offer to make them available for wider use.

The compressed breast during mammography and breast tomosynthesis:in vivoshape characterization and modeling

“…Several areas of research in DM and DBT, such as many of the approaches for scatter correction (Sechopoulos et al , 2007b; Feng and Sechopoulos, 2011; Feng et al , 2014; Diaz et al , 2014; Kim et al , 2015) and thickness correction (Snoeren and Karssemeijer, 2004; Kallenberg and Karssemeijer, 2012) algorithms, require simulating realistic 3D compressed breast shapes (some approaches for scatter correction such as the one proposed by Kim et al (2015) do not require this). Moreover, other areas of research like patient dosimetry (Dance, 1990; Dance et al , 2000; Sechopoulos et al , 2007a; Sechopoulos et al , 2012), breast density estimation (Pertuz et al , 2016; Gubern-Merida et al , 2014), image registration and segmentation (Richard et al , 2006; Hipwell et al , 2016), and 3D breast software phantoms (Bakic et al , 2002; Bakic et al , 2011; Wang et al , 2012; O’Connor et al , 2013; Hsu et al , 2013; Kiarashi et al , 2015) could also benefit from objective shape models of compressed breasts to improve their accuracy and relevance.…”

Population of 224 realistic human subject-based computational breast phantoms

“…These types of phantoms have been largely based on dedicated bCT data from mastectomy specimens. 20,21 However, these specimens do not adequately represent intact breasts. Currently, only a small number of voxelized phantoms using this method exist due to limited access to specimens.…”

Development of realistic physical breast phantoms matched to virtual breast phantoms based on human subject data

“…[10][11][12][13][14][15] More sophisticated modeling of the breast anatomy has been done in the context of virtual breast phantoms. [16][17][18][19][20][21][22][23][24][25][26] Virtual phantoms provide great utility to inform the design of clinical trials or possibly eliminate unnecessary costs and irradiation necessary for such clinical trials by potentially substituting human subjects. 27,28 These phantoms broadly fall into one of the two categories: rule-based phantoms that are mathematically defined and phantoms that are based on the anatomy of specific human subjects.…”