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.

Laser writing is used to structure surfaces in many different ways in materials and life sciences. However, combinatorial patterning applications are still limited. Here we present a method for cost-efficient combinatorial synthesis of very-high-density peptide arrays with natural and synthetic monomers. A laser automatically transfers nanometre-thin solid material spots from different donor slides to an acceptor. Each donor bears a thin polymer film, embedding one type of monomer. Coupling occurs in a separate heating step, where the matrix becomes viscous and building blocks diffuse and couple to the acceptor surface. Furthermore, we can consecutively deposit two material layers of activation reagents and amino acids. Subsequent heat-induced mixing facilitates an in situ activation and coupling of the monomers. This allows us to incorporate building blocks with click chemistry compatibility or a large variety of commercially available non-activated, for example, posttranslationally modified building blocks into the array's peptides with >17,000 spots per cm2.

This paper presents a method for creation of computational models of breast lesions with irregular shapes from patient Digital Breast Tomosynthesis (DBT) images or breast cadavers and whole-body Computed Tomography (CT) images. The approach includes six basic steps: (a) normalization of the intensity of the tomographic images; (b) image noise reduction; (c) binarization of the lesion area, (d) application of morphological operations to further decrease the level of artefacts; (e) application of a region growing technique to segment the lesion; and (f) creation of a final 3D lesion model. The algorithm is semi-automatic as the initial selection of the region of the lesion and the seeds for the region growing are done interactively. A software tool, performing all of the required steps, was developed in MATLAB. The method was tested and evaluated by analysing anonymized sets of DBT patient images diagnosed with lesions. Experienced radiologists evaluated the segmentation of the tumours in the slices and the obtained 3D lesion shapes. They concluded for a quite satisfactory delineation of the lesions. In addition, for three DBT cases, a delineation of the tumours was performed independently by the radiologists. In all cases the abnormality volumes segmented by the proposed algorithm were smaller than those outlined by the experts. The calculated Dice similarity coefficients for algorithm-radiologist and radiologist-radiologist showed similar values. Another selected tumour case was introduced into a computational breast model to recursively assess the algorithm. The relative volume difference between the ground-truth tumour volume and the one obtained by applying the algorithm on the synthetic volume from the virtual DBT study is 5% which demonstrates the satisfactory performance of the proposed segmentation algorithm. The software tool we developed was used to create models of different breast abnormalities, which were then stored in a database for use by researchers working in this field. Anthropomorphic voxel breast phantoms with realistic tissue

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Objective: It is well established that computer based models of x-ray imaging systems are basic and very important tools for developing and evaluating new emerging x-ray imaging techniques, optimizing technical parameters, and performing feasibility studies prior to implementation in clinical practice. Such models are essential for the development and the establishment of new breast x-ray imaging modalities that aim to detect and better characterize breast lesions in their early stage. This work presents a complete software package, called BreastSimulator, dedicated for breast x-ray imaging research. Methods: The package consists of four modules used to create three-dimensional breast models in compressed and uncompressed state, simulate x-ray mammographic images and visualize the results of the simulations. The module that is used to generate breast models, Breast Modeling Module, consists of several sub-modules that are utilized to model the different breast components: external shape, glandular and adipose tissue, breast lesion, skin, pectoralis and lymphatics. The Compression Module is dedicated to simulate the mechanical compression of the breasts. Mammographic projection images are obtained with simulation of x-ray photon transport starting from the x-ray source, passing through the breast model and reaching the detector. This is accomplished in the Image Generation Module. Finally, the results of the simulations, i.e. breast models and mammographic images can be seen with the Visualization Module. Results: Here, we demonstrate the application of the software package in conventional and dual-energy mammography as well as compression studies, as examples to highlight basic functions and applications of Breast Simulator. The first study aimed to define the optimal pair of 'low' and 'high' monochromatic x-ray energies for dual-energy mammography. It involved the synthesis of 225 dual-energy images obtained from combinations of 'low' and 'high' energy images acquired in the energy range 14 to 28 keV. Images were generated from a medium sized dense breast model that contained one calcification. The study showed that 17/28 keV incident monoenergetic beams are optimal to obtain maximal calcification detectability for this breast. The second study demonstrated the effect of breast compression on the quality of the obtained mammograms. It included a breast model based on breast CT slices subjected to simulated compression and generation of mammographic images. Increased image quality is observed for mammograms obtained from breasts with reduced thickness. The characteristics of the x-ray beams that exit a small dense breast model were investigated in the third study. www.sciedu.ca/jbgc