Volumetric High-Resolution X-Ray Phase-Contrast Virtual Histology of Breast Specimens With a Compact Laboratory System

Edge-illumination spectral phase-contrast tomography

Following the rapid, but independent, diffusion of x-ray spectral and phase-contrast systems, this work demonstrates the first combination of spectral and phase-contrast computed tomography (CT) obtained by using the edge-illumination technique and a CdTe small-pixel (62μm) spectral detector. A theoretical model is introduced, starting from a standard attenuation-based spectral decomposition and leading to spectral phase-contrast material decomposition. Each step of the model is followed by quantification of accuracy and sensitivity on experimental data of a test phantom containing different solutions with known concentrations. An example of a micro CT application (20μm voxel size) on an iodine-perfusedex vivomurine model is reported. The work demonstrates that spectral-phase contrast combines the advantages of spectral imaging, i.e. high-Zmaterial discrimination capability, and phase-contrast imaging, i.e. soft tissue sensitivity, yielding simultaneously mass density maps of water, calcium, and iodine with an accuracy of 1.1%, 3.5%, and 1.9% (root mean square errors), respectively. Results also show a 9-fold increase in the signal-to-noise ratio of the water channel when compared to standard spectral decomposition. The application to the murine model revealed the potential of the technique in the simultaneous 3D visualization of soft tissue, bone, and vasculature. While being implemented by using a broad spectrum (pink beam) at a synchrotron radiation facility (Elettra, Trieste, Italy), the proposed experimental setup can be readily translated to compact laboratory systems including conventional x-ray tubes.

Integrating X-ray phase-contrast imaging and histology for comparative evaluation of breast tissue malignancies in virtual histology analysis

Detecting breast tissue alterations is essential for cancer diagnosis. However, inherent bidimensionality limits histological procedures' effectiveness in identifying these changes. Our study applies a 3D virtual histology method based on X-ray phase-contrast microtomography (PhC μ CT), performed at a synchrotron facility, to investigate breast tissue samples including different types of lesions, namely intraductal papilloma, micropapillary intracystic carcinoma, and invasive lobular carcinoma. One-to-one comparisons of X-ray and histological images explore the clinical potential of 3D X-ray virtual histology. Results show that PhC μ CT technique provides high spatial resolution and soft tissue sensitivity, while being non-destructive, not requiring a dedicated sample processing and being compatible with conventional histology. PhC μ CT can enhance the visualization of morphological characteristics such as stromal tissue, fibrovascular core, terminal duct lobular unit, stromal/epithelium interface, basement membrane, and adipocytes. Despite not reaching the (sub) cellular level, the three-dimensionality of PhC μ CT images allows to depict in-depth alterations of the breast tissues, potentially revealing pathologically relevant details missed by a single histological section. Compared to serial sectioning, PhC μ CT allows the virtual investigation of the sample volume along any orientation, possibly guiding the pathologist in the choice of the most suitable cutting plane. Overall, PhC μ CT virtual histology holds great promise as a tool adding to conventional histology for improving efficiency, accessibility, and diagnostic accuracy of pathological evaluation.

Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps

Edge illumination (EI) is an X-ray imaging technique that, in addition to conventional absorption contrast, provides refraction and scatter contrast. It relies on an absorption mask in front of the sample that splits the X-ray beam into beamlets, which hits a second absorption mask positioned in front of the detector. The sample mask is then shifted in multiple steps with respect to the detector mask, thereby measuring an illumination curve per detector element. The width, position, and area of this curve estimated with and without the sample in the beam is then compared, which ultimately provides absorption, refraction, and scatter contrast for each detector pixel. From the obtained contrast sinograms, three contrast tomograms can be computed. In summary, conventional EI relies on a two-stage process comprised of a computational and time intensive contrast retrieval process, followed by tomographic reconstruction. In this work, a novel joint reconstruction method is proposed, which utilizes a combined forward model to reconstruct the three contrasts simultaneously, without the need for an intermediate contrast retrieval step. Compared to the state-of-the-art, this approach reduces reconstruction times, as the retrieval step is skipped and allows a much more flexible acquisition scheme, as there is no need to sample a full illumination curve at each projection angle. The proposed method is shown to improve reconstruction quality on subsampled datasets, enabling the reconstruction of three contrasts from single-shot datasets.

Multiscale X-ray phase-contrast tomography: From breast CT to micro-CT for virtual histology

Phase-contrast imaging techniques address the issue of poor soft-tissue contrast encountered in traditional X-ray imaging. This can be accomplished with the propagation-based phase-contrast technique by employing a coherent photon beam, which is available at synchrotron facilities, as well as long sample-to-detector distances. This study demonstrates the optimization of propagation-based phase-contrast computed tomography (CT) techniques for multiscale X-ray imaging of the breast at the Elettra synchrotron facility (Trieste, Italy). Two whole breast mastectomy samples were acquired with propagation-based breast-CT using a monochromatic synchrotron beam at a pixel size of 60 µm. Paraffin-embedded blocks sampled from the same tissues were scanned with propagation-based micro-CT imaging using a polychromatic synchrotron beam at a pixel size of 4 µm. Images of both methodologies and of the same sample were spatially registered. The resulting images showed the transition from whole breast imaging with propagation-based breast-CT methodology to virtual histology with propagation-based micro-CT imaging of the same sample. Additionally, conventional histological images were matched to virtual histology images. Phase-contrast images offer a high resolution with low noise, which allows for a highly precise match between virtual and conventional histology. Furthermore, those techniques allow a clear discernment of breast structures, lesions, and microcalcifications, being a promising clinically-compatible tool for breast imaging in a multiscale approach, to either assist in the detection of cancer in full volume breast samples or to complement structure identification in paraffin-embedded breast tissue samples.

A Condensed History Approach to X-Ray Dark Field Effects in Edge Illumination Phase Contrast Simulations

X-ray dark field signals, measurable in many x-ray phase contrast imaging (XPCI) setups, stem from unresolvable microstructures in the scanned sample. This makes them ideally suited for the detection of certain pathologies, which correlate with changes in the microstructure of a sample. Simulations of x-ray dark field signals can aid in the design and optimization of XPCI setups, and the development of new reconstruction techniques. Current simulation tools, however, require explicit modelling of the sample microstructures according to their size and spatial distribution. This process is cumbersome, does not translate well between different samples, and considerably slows down simulations. In this work, a condensed history approach to modelling x-ray dark field effects is presented, under the assumption of an isotropic distribution of microstructures, and applied to edge illumination phase contrast simulations. It substantially simplifies the sample model, can be easily ported between samples, and is two orders of magnitude faster than conventional dark field simulations, while showing equivalent results.Clinical relevance- Dark field signal provides information on the microstructure distribution within the investigated sample, which can be applied in areas such as histology and lung x-ray imaging. Efficient simulation tools for this dark field signal aid in optimizing scanning setups, acquisition schemes and reconstruction techniques.

Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging

The design of new x-ray phase contrast imaging setups often relies on Monte Carlo simulations for prospective parameter studies. Monte Carlo simulations are known to be accurate but time consuming, leading to long simulation times, especially when many parameter variations are required. This is certainly the case for imaging methods relying on absorbing masks or gratings, with various tunable properties, such as pitch, aperture size, and thickness. In this work, we present the virtual grating approach to overcome this limitation. By replacing the gratings in the simulation with virtual gratings, the parameters of the gratings can be changed after the simulation, thereby significantly reducing the overall simulation time. The method is validated by comparison to explicit grating simulations, followed by representative demonstration cases.

Multi-Modal X-ray Imaging and Analysis for Characterization of Urinary Stones

Backgound: The composition of stones formed in the urinary tract plays an important role in their management over time. The most common imaging method for the non-invasive evaluation of urinary stones is radiography and computed tomography (CT). However, CT is not very sensitive, and cannot differentiate between all critical stone types. In this study, we propose the application, and evaluate the potential, of a multi-modal (or multi-contrast) X-ray imaging technique called speckle-based imaging (SBI) to differentiate between various types of urinary stones. Methods: Three different stone samples were extracted from animal and human urinary tracts and examined in a laboratory-based speckle tracking setup. The results were discussed based on an X-ray diffraction analysis and a comparison with X-ray microtomography and grating-based interferometry. Results: The stones were classified through compositional analysis by X-ray diffraction. The multi-contrast images obtained using the SBI method provided detailed information about the composition of various urinary stone types, and could differentiate between them. X-ray SBI could provide highly sensitive and high-resolution characterizations of different urinary stones in the radiography mode, comparable to those by grating interferometry. Conclusions: This investigation demonstrated the capability of the SBI technique for the non-invasive classification of urinary stones through radiography in a simple and cost-effective laboratory setting. This opens the possibility for further studies concerning full-field in vivo SBI for the clinical imaging of urinary stones.