Purpose: To compare the estimate of normalized glandular dose in mammography and breast CT imaging obtained using the actual glandular tissue distribution in the breast to that obtained using the homogeneous tissue mixture approximation. Methods: Twenty volumetric images of patient breasts were acquired with a dedicated breast CT prototype system and the voxels in the breast CT images were automatically classified into skin, adipose, and glandular tissue. The breasts in the classified images underwent simulated mechanical compression to mimic the conditions present during mammographic acquisition. The compressed thickness for each breast was set to that achieved during each patient's last screening cranio‐caudal (CC) acquisition. The volumetric glandular density of each breast was computed using both the compressed and uncompressed classified images, and additional images were created in which all voxels representing adipose and glandular tissue were replaced by a homogeneous mixture of these two tissues in a proportion corresponding to each breast's volumetric glandular density. All four breast images (compressed and uncompressed; heterogeneous and homogeneous tissue) were input into Monte Carlo simulations to estimate the normalized glandular dose during mammography (compressed breasts) and dedicated breast CT (uncompressed breasts). For the mammography simulations the x‐ray spectra used was that used during each patient's last screening CC acquisition. For the breast CT simulations, two x‐ray spectra were used, corresponding to the x‐ray spectra with the lowest and highest energies currently being used in dedicated breast CT prototype systems under clinical investigation. The resulting normalized glandular dose for the heterogeneous and homogeneous versions of each breast for each modality was compared. Results: For mammography, the normalized glandular dose based on the homogeneous tissue approximation was, on average, 27% higher than that estimated using the true heterogeneous glandular tissue distribution (Wilcoxon Signed Rank Testp = 0.00046). For dedicated breast CT, the overestimation of normalized glandular dose was, on average, 8% (49 kVp spectrum, p = 0.00045) and 4% (80 kVp spectrum, p = 0.000089). Only two cases in mammography and two cases in dedicated breast CT with a tube voltage of 49 kVp resulted in lower dose estimates for the homogeneous tissue approximation compared to the heterogeneous tissue distribution. Conclusions: The normalized glandular dose based on the homogeneous tissue mixture approximation results in a significant overestimation of dose to the imaged breast. This overestimation impacts the use of dose estimates in absolute terms, such as for risk estimates, and may impact some comparative studies, such as when modalities or techniques with different x‐ray energies are used. The error introduced by the homogeneous tissue mixture approximation in higher energy x‐ray modalities, such as dedicated breast CT, although statistically significant, may not be of clinical concern. Further...

This paper presents a methodology for three-dimensional (3D) computer modelling of the breast, using a combination of 3D geometrical primitives and voxel matrices that can be further subjected to simulated x-ray imaging, to produce synthetic mammograms. The breast phantom is a composite model of the breast and includes the breast surface, the duct system and terminal ductal lobular units. Cooper's ligaments, the pectoral muscle, the 3D mammographic background and breast abnormalities. A second analytical x-ray matter interaction modelling module is used to generate synthetic images from monoenergetic fan beams. Mammographic images of various synthesized breast models differing in size, shape and composition were produced. A preliminary qualitative assessment performed by three radiologists and a quantitative evaluation study using fractal and grey-level histogram analysis were conducted. A comparative study of extracted features with published data has also been performed. The evaluation results indicated good correlation of characteristics between synthetic and actual radiographs. Applications foreseen are not only in the area of breast imaging experimentation but also in education and training.

Breast physical phantoms are a basic tool for the assessment and verification of performance standards in daily clinical practice of x-ray breast imaging modalities. They are also invaluable in testing and evaluation of new x-ray breast modalities to be potentially established, e.g. breast computed tomography, dual-energy breast CT and phase-contrast mammography and tomography. Nowadays, there is a lack or there are only a limited number of breast physical phantoms available for this purpose.The aim of this study is to explore a range of 3D printing materials such as resins, PLA, ABS, Nylon etc, to determine their attenuation and refractive properties, and to finally compare them to the properties of the breast tissues: adipose, glandular and skin.To achieve this goal, step-wedge phantoms were computationally modeled and then manufactured using stereolithographic and fused-deposition modeling technologies. X-ray images of the phantoms were acquired, using monochromatic beam at ID17, ESRF, Grenoble for three energies-30 keV, 45 keV and 60 keV. Experimental data were further processed to obtain the linear attenuation coefficients of these materials. Comparison with theoretical data for the linear attenuation coefficients and the refractive indexes for breast tissues was performed.From the studied materials, most of the resins, Nylon, Hybrid, PET-G show absorption properties close to the glandular tissue, while ABS shows absorption characteristics close to these of the adipose tissue. For phase-contrast imaging, it turns out that the ABS combined with resin-based materials to represent the adipose and glandular tissues, respectively may be a good combination for manufacturing of a phantom suitable for these studies.These results can be used for the design and the construction of a new physical anthropomorphic phantom of the breast with improved anatomical and radiological characteristics dedicated for advanced mammography imaging techniques implemented at higher photon energies.

This paper presents a mammography simulator and demonstrates its applicability in feasibility studies in dual-energy (DE) subtraction mammography. This mammography simulator is an evolution of a previously presented x-ray imaging simulation system, which has been extended with new functionalities that are specific for DE simulations. The new features include incident exposure and dose calculations, the implementation of a DE subtraction algorithm as well as amendments to the detector and source modelling. The system was then verified by simulating experiments and comparing their results against published data. The simulator was used to carry out a feasibility study of the applicability of DE techniques in mammography, and more precisely to examine whether this modality could result in better visualization and detection of microcalcifications. Investigations were carried out using a 3D breast software phantom of average thickness, monoenergetic and polyenergetic beam spectra and various detector configurations. Dual-shot techniques were simulated. Results showed the advantage of using monoenergetic in comparison with polyenergetic beams. Optimization studies with monochromatic sources were carried out to obtain the optimal low and high incident energies, based on the assessment of the figure of merit of the simulated microcalcifications in the subtracted images. The results of the simulation study with the optimal energies demonstrated that the use of the DE technique can improve visualization and increase detectability, allowing identification of microcalcifications of sizes as small as 200 microm. The quantitative results are also verified by means of a visual inspection of the synthetic images.

A dataset of monoenergetic and polyenergetic DgN coefficients for BCT was provided. Patient specific breast models showed a different volume distribution of glandular dose and determined a DgN 8% lower, on average, than homogeneous breast model.