Comparing x-ray phase-contrast imaging using a Talbot array illuminator to propagation-based imaging for non-homogeneous biomedical samples.

Phase-contrast computed tomography can visualize soft tissue samples with high contrast. At coherent sources, propagation-based imaging (PBI) techniques are among the most common, as they are easy to implement and produce high-resolution images. Their downside is a low degree of quantitative data due to simplifying assumptions of the sample properties in the reconstruction. These assumptions can be avoided, by using quantitative phase-contrast techniques as an alternative. However, these often compromise spatial resolution and require complicated setups. In order to overcome this limitation, we designed and constructed a new imaging setup using a 2D Talbot array illuminator as a wavefront marker and speckle-based imaging phase-retrieval techniques. We developed a post-processing chain that can compensate for wavefront marker drifts and that improves the overall sensitivity. By comparing two measurements of biomedical samples, we demonstrate that the spatial resolution of our setup is comparable to the one of PBI scans while being able to successfully image a sample that breaks the typical homogeneity assumption used in PBI.

Spectral X-ray dark-field signal characterization from dual-energy projection phase-stepping data with a Talbot-Lau interferometer.

Material-selective analysis of spectral X-ray imaging data requires prior knowledge of the energy dependence of the observed signal. Contrary to conventional X-ray imaging, where the material-specific attenuation coefficient is usually precisely known, the linear diffusion coefficient of the X-ray dark-field contrast does not only depend on the material and its microstructure, but also on the setup geometry and is difficult to access. Here, we present an optimization approach to retrieve the energy dependence of the X-ray dark-field signal quantitatively on the example of closed-cell foams from projection data without the need for additional hardware to a standard grating-based X-ray dark-field imaging setup. A model for the visibility is used to determine the linear diffusion coefficient with a least-squares optimization. The comparison of the results to spectrometer measurements of the linear diffusion coefficient suggests the proposed method to provide a good estimate for the energydependent dark-field signal.

X-ray Stain Localization with Near-Field Ptychographic Computed Tomography.

Although X-ray contrast agents offer specific characteristics in terms of targeting and attenuation, their accumulation in the tissue on a cellular level is usually not known and difficult to access, as it requires high resolution and sensitivity. Here, quantitative near-field ptychographic X-ray computed tomography is demonstrated to assess the location of X-ray stains at a resolution sufficient to identify intracellular structures by means of a basis material decomposition. On the example of two different X-ray stains, the nonspecific iodine potassium iodide, and eosin Y, which mostly interacts with proteins and peptides in the cell cytoplasm, the distribution of the stains within the cells in murine kidney samples is assessed and compared to unstained samples with similar structural features. Quantitative nanoscopic stain concentrations are in good agreement with dual-energy micro computed tomography measurements, the state-of-the-art modality for material-selective imaging. The presented approach can be applied to a variety of X-ray stains advancing the development of X-ray contrast agents.

Direct Differentiation of Pathological Changes in the Human Lung Parenchyma With Grating-Based Spectral X-ray Dark-Field Radiography.

Diagnostic lung imaging is often associated with high radiation dose and lacks sensitivity, especially for diagnosing early stages of structural lung diseases. Therefore, diagnostic imaging methods are required which provide sound diagnosis of lung diseases with a high sensitivity as well as low patient dose. In small animal experiments, the sensitivity of grating-based X-ray dark-field imaging to structural changes in the lung tissue was demonstrated. The energy-dependence of the X-ray dark-field signal of lung tissue is a function of its microstructure and not yet known. Furthermore, conventional X-ray dark-field imaging is not capable of differentiating different types of pathological changes, such as fibrosis and emphysema. Here we demonstrate the potential diagnostic power of grating-based X-ray dark-field in combination with spectral imaging in human chest radiography for the direct differentiation of lung diseases. We investigated the energy-dependent linear diffusion coefficient of simulated lung tissue with different diseases in wave-propagation simulations and validated the results with analytical calculations. Additionally, we modeled spectral X-ray dark-field chest radiography scans to exploit these differences in energy-dependency. The results demonstrate the potential to directly differentiate structural changes in the human lung. Consequently, grating-based spectral X-ray dark-field imaging potentially contributes to the differential diagnosis of structural lung diseases at a clinically relevant dose level.

High-resolution and sensitivity bi-directional x-ray phase contrast imaging using 2D Talbot array illuminators.

Two-dimensional (2D) Talbot array illuminators (TAIs) were designed, fabricated, and evaluated for high-resolution high-contrast x-ray phase imaging of soft tissue at 10-20 keV. The TAIs create intensity modulations with a high compression ratio on the micrometer scale at short propagation distances. Their performance was compared with various other wavefront markers in terms of period, visibility, flux efficiency, and flexibility to be adapted for limited beam coherence and detector resolution. Differential x-ray phase contrast and dark-field imaging were demonstrated with a one-dimensional, linear phase stepping approach yielding 2D phase sensitivity using unified modulated pattern analysis (UMPA) for phase retrieval. The method was employed for x-ray phase computed tomography reaching a resolution of 3 µm on an unstained murine artery. It opens new possibilities for three-dimensional, non-destructive, and quantitative imaging of soft matter such as virtual histology. The phase modulators can also be used for various other x-ray applications such as dynamic phase imaging, super-resolution structured illumination microscopy, or wavefront sensing.

Dual-Energy X-Ray Dark-Field Material Decomposition.

Dual-energy imaging is a clinically well-established technique that offers several advantages over conventional X-ray imaging. By performing measurements with two distinct X-ray spectra, differences in energy-dependent attenuation are exploited to obtain material-specific information. This information is used in various imaging applications to improve clinical diagnosis. In recent years, grating-based X-ray dark-field imaging has received increasing attention in the imaging community. The X-ray dark-field signal originates from ultra small-angle scattering within an object and thus provides information about the microstructure far below the spatial resolution of the imaging system. This property has led to a number of promising future imaging applications that are currently being investigated. However, different microstructures can hardly be distinguished with current X-ray dark-field imaging techniques, since the detected dark-field signal only represents the total amount of ultra small-angle scattering. To overcome these limitations, we present a novel concept called dual-energy X-ray dark-field material decomposition, which transfers the basic material decomposition approach from attenuation-based dual-energy imaging to the dark-field imaging modality. We develop a physical model and algorithms for dual-energy dark-field material decomposition and evaluate the proposed concept in experimental measurements. Our results suggest that by sampling the energy-dependent dark-field signal with two different X-ray spectra, a decomposition into two different microstructured materials is possible. Similar to dual-energy imaging, the additional microstructure-specific information could be useful for clinical diagnosis.

Grating-based spectral X-ray dark-field imaging for correlation with structural size measures.

X-ray dark-field (XDF) imaging accesses information on the small-angle scattering properties of the sample. With grating interferometry, the measured scattering signal is related to the sample's autocorrelation function, which was previously demonstrated for simple samples, such as mono-dispersed microspheres for which the autocorrelation function is mathematically given. However, in potential clinical applications of XDF imaging, complex microstructures, such as lung parenchyma are under investigation. Their bahaviour in XDF imaging is not yet known and no mathematical description of the autocorrelation function is derived so far. In this work we demonstrate the previously established correlation of the XDF data of complex sample structures with their autocorrelation function to be impractical. Furthermore, we propose an applicable correlation between XDF and the sample's structural parameter on the basis of mean chord length, a medically-approved measure for alveolar structure, known to be affected by structural lung diseases. Our findings reveal a correlation between energy-dependent XDF imaging and the sample's mean chord length. By that, a connection between a medical measure for alveoli and XDF is achieved, which is particularly important regarding potential future XDF lung imaging applications for the assessment of alveoli size in diagnostic lung imaging.

Single spectrum three-material decomposition with grating-based x-ray phase-contrast CT.

Grating-based x-ray phase-contrast imaging provides three simultaneous image channels originating from a single image acquisition. While the phase signal provides direct access to the electron density in tomography, there is additional information on sub-resolutional structural information which is called dark-field signal in analogy to optical microscopy. The additional availability of the conventional attenuation image qualifies the method for implementation into existing diagnostic routines. The simultaneous access to the attenuation coefficient and the electron density allows for quantitative two-material discrimination as demonstrated lately for measurements at a quasi-monochromatic compact synchrotron source. Here, we investigate the transfer of the method to conventional polychromatic x-ray sources and the additional inclusion of the dark-field signal for three-material decomposition. We evaluate the future potential of grating-based x-ray phase-contrast CT for quantitative three-material discrimination for the specific case of early stroke diagnosis at conventional polychromatic x-ray sources. Compared to conventional CT, the method has the potential to discriminate coagulated blood directly from contrast agent extravasation within a single CT acquisition. Additionally, the dark-field information allows for the clear identification of hydroxyapatite clusters due to their micro-structure despite a similar attenuation as the applied contrast agent. This information on materials with sub-resolutional microstructures is considered to comprise advantages relevant for various pathologies.

A step towards valid detection and quantification of lung cancer volume in experimental mice with contrast agent-based X-ray microtomography.

Tumor volume is a parameter used to evaluate the performance of new therapies in lung cancer research. Conventional methods that are used to estimate tumor size in mouse models fail to provide fast and reliable volumetric data for tumors grown non-subcutaneously. Here, we evaluated the use of iodine-staining combined with micro-computed tomography (micro-CT) to estimate the tumor volume of ex vivo tumor-burdened lungs. We obtained fast high spatial resolution three-dimensional information of the lungs, and we demonstrated that iodine-staining highlights tumors and unhealthy tissue. We processed iodine-stained lungs for histopathological analysis with routine hematoxylin and eosin (H&E) staining. We compared the traditional tumor burden estimation performed manually with H&E histological slices with a semi-automated method using micro-CT datasets. In mouse models that develop lung tumors with well precise boundaries, the method that we describe here enables to perform a quick estimation of tumorous tissue volume in micro-CT images. Our method overestimates the tumor burden in tumors surrounded by abnormal tissue, while traditional histopathological analysis underestimates tumor volume. We propose to embed micro-CT imaging to the traditional workflow of tumorous lung analyses in preclinical cancer research as a strategy to obtain a more accurate estimation of the total lung tumor burden.