We show that a distribution of micrometer-sized calcifications in the human breast which are not visible in clinical x-ray mammography at diagnostic dose levels can produce a significant dark-field signal in a grating-based x-ray phase-contrast imaging setup with a tungsten anode x-ray tube operated at 40 kVp. A breast specimen with invasive ductal carcinoma was investigated immediately after surgery by Talbot-Lau x-ray interferometry with a design energy of 25 keV. The sample contained two tumors which were visible in ultrasound and contrast-agent enhanced MRI but invisible in clinical x-ray mammography, in specimen radiography and in the attenuation images obtained with the Talbot-Lau interferometer. One of the tumors produced significant dark-field contrast with an exposure of 0.85 mGy air-kerma. Staining of histological slices revealed sparsely distributed grains of calcium phosphate with sizes varying between 1 and 40 μm in the region of this tumor. By combining the histological investigations with an x-ray wave-field simulation we demonstrate that a corresponding distribution of grains of calcium phosphate in the form of hydroxylapatite has the ability to produce a dark-field signal which would-to a substantial degree-explain the measured dark-field image. Thus we have found the appearance of new information (compared to attenuation and differential phase images) in the dark-field image. The second tumor in the same sample did not contain a significant fraction of these very fine calcification grains and was invisible in the dark-field image. We conclude that some tumors which are invisible in x-ray absorption mammography might be detected in the x-ray dark-field image at tolerable dose levels.

These results provide the understanding of the noise characteristics of grating-based phase-contrast imaging and will help to improve image quality.

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Abstract:Over the recent years X-ray differential phase-contrast imaging was developed for the hard X-ray regime as produced from laboratory X-ray sources. The technique uses a grating-based Talbot-Lau interferometer and was shown to yield image contrast gain, which makes it very interesting to the fields of medical imaging and non-destructive testing, respectively. In addition to X-ray attenuation contrast, the differential phase-contrast and dark-field images provide different structural information about a specimen. For the dark-field even at length scales much smaller than the spatial resolution of the imaging system. Physical interpretation of the dark-field information as present in radiographic and tomographic (CT) images requires a detailed look onto the geometric orientation between specimen and the setup. During phase-stepping the drop in intensity modulation, due to local scattering effects within the specimen is reproduced in the dark-field signal. This signal shows strong dependencies on micro-porosity and micro-fibers if these are numerous enough in the object. Since a gratinginterferometer using a common unidirectional line grating is sensitive to X-ray scattering in one plane only, the dark-field image is influenced by the fiber orientations with respect to the grating bars, which can be exploited to obtain anisotropic structural information. With this contribution, we attempt to extend existing models for 2D projections to 3D data by analyzing dark-field contrast tomography of anisotropically structured materials such as carbon fiber reinforced carbon (CFRC).

Abstract:A simulation framework for coherent X-ray imaging, based on scalar diffraction theory, is presented. It contains a core C++ library and an additional Python interface. A workflow is presented to include contributions of inelastic scattering obtained with Monte-Carlo methods. X-ray Talbot-Lau interferometry is the primary focus of the framework. Simulations are in agreement with measurements obtained with such an interferometer. Especially, the dark-field signal of densely packed PMMA microspheres is predicted. A realistic modeling of the microsphere distribution, which is necessary for correct results, is presented. The framework can be used for both setup design and optimization but also to test and improve reconstruction methods.