Propagation-based Phase-contrast Imaging Research Articles

Computational simulations and assessment of two approaches for x-ray phase contrast imaging

X-ray phase-contrast imaging is a high-resolution imaging that permits an increase of the perceptibility of the details in three-dimensional objects, such as human tissues compared to conventional absorption imaging. There are different approaches for implementing phase-contrast imaging and their introduction into clinical practice requires advanced computational tools. A long-term goal of our research is the development of computational models of breast phase-contrast imaging. The aim of this study is to develop a software module for implementing grating-based phase-contrast imaging. For this purpose, an existing in-house software application for x-ray imaging with a function to model and simulate propagation-based phase-contrast x-ray images has been extended to include a model of grating-based imaging. To test the new functionality, four computational phantoms reflecting features, which can be screened in the real breast tissue and which differ in their complexity, were designed. Planar x-ray images in absorption, propagation-based and grating-based modes were generated and compared. Results showed improved visual appearance of the simulated objects in images obtained by simulating grating-based imaging setup. The developed subroutine is planned to be experimentally validated at synchrotron facility. The new software functionality will be exploited in studies related to new x-ray imaging techniques for breast screening and diagnosing.

Phase-contrast X-ray tomography resolves the terminal bronchioles in free-breathing mice

Phase-contrast X-ray lung imaging has broken new ground in preclinical respiratory research by improving contrast at air/tissue interfaces. To minimize blur from respiratory motion, intubation and mechanical ventilation is commonly employed for end-inspiration gated imaging at synchrotrons and in the laboratory. Inevitably, the prospect of ventilation induced lung injury (VILI) renders mechanical ventilation a confounding factor in respiratory studies of animal models. Here we demonstrate proof-of-principle 3D imaging of the tracheobronchial tree in free-breathing mice without mechanical ventilation at radiation levels compatible with longitudinal studies. We use a prospective gating approach for end-expiration propagation-based phase-contrast X-ray imaging where the natural breathing of the mouse dictates the acquisition flow. We achieve intrapulmonary spatial resolution in the 30-μm-range, sufficient for resolving terminal bronchioles in the 60-μm-range distinguished from the surrounding lung parenchyma. These results should enable non-invasive longitudinal studies of native state murine airways for translational lung disease research in the laboratory.

A robust, semi-automated approach for counting cementum increments imaged with synchrotron X-ray computed tomography.

Cementum, the tissue attaching mammal tooth roots to the periodontal ligament, grows appositionally throughout life, displaying a series of circum-annual incremental features. These have been studied for decades as a direct record of chronological lifespan. The majority of previous studies on cementum have used traditional thin-section histological methods to image and analyse increments. However, several caveats have been raised in terms of studying cementum increments in thin-sections. Firstly, the limited number of thin-sections and the two-dimensional perspective they impart provide an incomplete interpretation of cementum structure, and studies often struggle or fail to overcome complications in increment patterns that complicate or inhibit increment counting. Increments have been repeatedly shown to both split and coalesce, creating accessory increments that can bias increment counts. Secondly, identification and counting of cementum increments using human vision is subjective, and it has led to inaccurate readings in several experiments studying individuals of known age. Here, we have attempted to optimise a recently introduced imaging modality for cementum imaging; X-ray propagation-based phase-contrast imaging (PPCI). X-ray PPCI was performed for a sample of rhesus macaque (Macaca mulatta) lower first molars (n = 10) from a laboratory population of known age. PPCI allowed the qualitative identification of primary/annual versus intermittent secondary increments formed by splitting/coalescence. A new method for semi-automatic increment counting was then integrated into a purpose-built software package for studying cementum increments, to count increments in regions with minimal complications. Qualitative comparison with data from conventional cementochronology, based on histological examination of tissue thin-sections, confirmed that X-ray PPCI reliably and non-destructively records cementum increments (given the appropriate preparation of specimens prior to X-ray imaging). Validation of the increment counting algorithm suggests that it is robust and provides accurate estimates of increment counts. In summary, we show that our new increment counting method has the potential to overcome caveats of conventional cementochronology approaches, when used to analyse three-dimensional images provided by X-ray PPCI.

Evaporation kinetics in highly porous tetrapodal zinc oxide networks studied using in situ SR\xb5CT

Tetrapodal zinc oxide (t-ZnO) is used to fabricate polymer composites for many different applications ranging from biomedicine to electronics. In recent times, macroscopic framework structures from t-ZnO have been used as a versatile sacrificial template for the synthesis of multi-scaled foam structures from different nanomaterials such as graphene, hexagonal boron nitride or gallium nitride. Many of these fabrication methods rely on wet-chemical coating processes using nanomaterial dispersions, leading to a strong interest in the actual coating mechanism and factors influencing it. Depending on the type of medium (e.g. solvent) used, different results regarding the homogeneity of the nanomaterial coating can be achieved. In order to understand how a medium influences the coating behavior, the evaporation process of water and ethanol is investigated in this work using in situ synchrotron radiation-based micro computed tomography (SRµCT). By employing propagation-based phase contrast imaging, both the t-ZnO network and the medium can be visualized. Thus, the evaporation process can be monitored non-destructively in three dimensions. This investigation showed that using a polar medium such as water leads to uniform evaporation and, by that, a homogeneous coating of the entire network.

Comparison of microstructural imagingof the root canal isthmus using propagation-based X-ray phase-contrast and absorptionmicro-computed tomography.

Clear and complete microstructural imaging of the root canal isthmus is an important part of pathological investigations in research and clinical practice. X-ray micro-computed tomography (μCT) is a widely used non-destructive imaging technique, which allows for distortion-free three-dimensional (3D) visualisation. While absorption μCT typically has poor contrast resolution for observing the root canal isthmus, especially for weak-absorbing tissues, propagation-based X-ray phase-contrast imaging (PBI) is a powerful imaging method, which in its combination with μCT (PB-PCμCT) enables high-resolution and high-contrast microstructural imagingof the weak-absorbing tissues in samples. To investigate the feasibility and ability of PB-PCμCT in microstructural imaging of the root canal isthmus, conventional absorption μCT and PB-PCμCT experiments were performed. The two-dimensional (2D) and 3D comparison results demonstrated that, compared to absorption μCT, PB-PCμCT has the ability to image the root canal isthmus more clearly and completely, and thus, it has great potential to serve as a valuable tool for biomedical and preclinical studies on the root canal isthmus.

Laboratory phase-contrast nanotomography of unstained Bombus terrestris compound eyes.

Imaging the visual systems of bumblebees and other pollinating insects may increase understanding of their dependence on specific habitats and how they will be affected by climate change. Current high-resolution imaging methods are either limited to two dimensions (light- and electron microscopy) or have limited access (synchrotron radiation x-ray tomography). For x-ray imaging, heavy metal stains are often used to increase contrast. Here, we present micron-resolution imaging of compound eyes of buff-tailed bumblebees (Bombus terrestris) using a table-top x-ray nanotomography (nano-CT) system. By propagation-based phase-contrast imaging, the use of stains was avoided and the microanatomy could more accurately be reconstructed than in samples stained with phosphotungstic acid or osmium tetroxide. The findings in the nano-CT images of the compound eye were confirmed by comparisons with light- and transmission electron microscopy of the same sample and finally, comparisons to synchrotron radiation tomography as well as to a commercial micro-CT system weredone.

In Silico Phase-Contrast X-Ray Imaging of Anthropomorphic Voxel-Based Phantoms

Propagation-based phase-contrast X-ray imaging is an emerging technique that can improve dose efficiency in clinical imaging. In silico tools are key to understanding the fundamental imaging mechanisms and develop new applications. Here, due to the coherent nature of the phase-contrast effects, tools based on wave propagation (WP) are preferred over Monte Carlo (MC) based methods. WP simulations require very high wave-front sampling which typically limits simulations to small idealized objects. Virtual anthropomorphic voxel-based phantoms are typically provided with a resolution lower than imposed sampling requirements and, thus, cannot be directly translated for use in WP simulations. In the present paper we propose a general strategy to enable the use of these phantoms for WP simulations. The strategy is based on upsampling in the 3D domain followed by projection resulting in high-resolution maps of the projected thickness for each phantom material. These maps can then be efficiently used for simulations of Fresnel diffraction to generate in silico phase-contrast X-ray images. We demonstrate the strategy on an anthropomorphic breast phantom to simulate propagation-based phase-contrast mammography using a laboratory micro-focus X-ray source.

Optimizing and applying high-resolution, in-line laboratory phase-contrast X-ray imaging for low-density material samples.

In-line, or propagation-based phase-contrast X-ray imaging (PBI) is an attractive alternative to the attenuation-based modality for low-density, soft samples showing low attenuation contrast. With the growing availability of micro- and nano-focus X-ray tubes, the method is increasingly applied in the laboratory. Here, we discuss the technique and demonstrate its advantages for selected low-density, low attenuation material samples using a lab-based micro- and nano-computed tomography systems Easytom XL Ultra, providing micron and sub-micron range resolution PBI images. We demonstrate a multi-step optimization of the lab-based PBI technique on our scanner that includes choosing the optimal detector-source hardware combination available in the setup, then optimizing the imaging geometry and finally the phase retrieval process through a parametric study. We point out and elaborate on the effect of noise correlation and texturing due to phase retrieval. We demonstrate the overall benefits of using the phase image and the phase retrieval for the selected samples such as improved image quality, increased contrast-to-noise ratio while only marginally influencing the spatial resolution. The improvement in image quality also enables further image processing steps for detailed structural analysis of the samples, which would be much more complicated if not impossible based on the transmissionimage.

Synchrotron radiation X-ray microtomography for the visualization of intra-cochlear anatomy in human temporal bones implanted with a perimodiolar cochlear implant electrode array.

Recently, synchrotron radiation computed microtomography (SRµCT) has emerged as a promising tool for non-destructive, in situ visualization of cochlear implant electrode arrays inserted into a human cochlea. Histological techniques have been the `gold standard' technique for accurate localization of cochlear implant electrodes but are suboptimal for precise three-dimensional measurements. Here, an SRµCT experimental setup is proposed that offers the benefit ofa high spatial and contrast resolution (isotropic voxel size = 4.95 µm and propagation-based phase-contrast imaging), while visualizing the soft-tissue structures and electrode array of the cochlear implant simultaneously. In this work, perimodiolar electrode arrays have been tested, which incorporate thick and closely spaced platinum-iridium contacts and wiring. These data can assist cochlear implant and hearing research, can be used to verify electrode segmentation techniques for clinical computed tomography or could be utilized to evaluate cochlear implant electrode array designs.

Convolutional neuronal networks combined with X-ray phase-contrast imaging for a fast and observer-independent discrimination of cartilage and liver diseases stages

We applied transfer learning using Convolutional Neuronal Networks to high resolution X-ray phase contrast computed tomography datasets and tested the potential of the systems to accurately classify Computed Tomography images of different stages of two diseases, i.e. osteoarthritis and liver fibrosis. The purpose is to identify a time-effective and observer-independent methodology to identify pathological conditions. Propagation-based X-ray phase contrast imaging WAS used with polychromatic X-rays to obtain a 3D visualization of 4 human cartilage plugs and 6 rat liver samples with a voxel size of 0.7 × 0.7 × 0.7 µm3 and 2.2 × 2.2 × 2.2 µm3, respectively. Images with a size of 224 × 224 pixels are used to train three pre-trained convolutional neuronal networks for data classification, which are the VGG16, the Inception V3, and the Xception networks. We evaluated the performance of the three systems in terms of classification accuracy and studied the effect of the variation of the number of inputs, training images and of iterations. The VGG16 network provides the highest classification accuracy when the training and the validation-test of the network are performed using data from the same samples for both the cartilage (99.8%) and the liver (95.5%) datasets. The Inception V3 and Xception networks achieve an accuracy of 84.7% (43.1%) and of 72.6% (53.7%), respectively, for the cartilage (liver) images. By using data from different samples for the training and validation-test processes, the Xception network provided the highest test accuracy for the cartilage dataset (75.7%), while for the liver dataset the VGG16 network gave the best results (75.4%). By using convolutional neuronal networks we show that it is possible to classify large datasets of biomedical images in less than 25 min on a 8 CPU processor machine providing a precise, robust, fast and observer-independent method for the discrimination/classification of different stages of osteoarthritis and liver diseases.

Dark-field signal extraction in propagation-based phase-contrast imaging

A method for extracting the dark-field signal in propagation-based phase-contrast imaging is proposed. In the case of objects consisting predominantly of a single material, or several different materials with similar ratios of the real decrement to the imaginary part of the complex refractive index, the proposed method requires a single image for extraction of the dark-field signal in two-dimensional projection imaging. In the case of three-dimensional tomographic imaging, the method needs only one image to be collected at each projection angle. Initial examples using simulated and experimental data indicate that this method can improve visualization of small sharp features inside a larger object, e.g. the visualization of microcalcifications in propagation-based x-ray breast cancer imaging. It is suggested that the proposed approach may be useful in other forms of biomedical imaging, where it can help one to obtain additional small-angle scattering information without increasing the radiation dose to the sample.

Low-dose in situ prelocation of protein microcrystals by 2D X-ray phase-contrast imaging for serial crystallography.

Serial protein crystallography has emerged as a powerful method of data collection on small crystals from challenging targets, such as membrane proteins. Multiple microcrystals need to be located on large and often flat mounts while exposing them to an X-ray dose that is as low as possible. A crystal-prelocation method is demonstrated here using low-dose 2D full-field propagation-based X-ray phase-contrast imaging at the X-ray imaging beamline TOMCAT at the Swiss Light Source (SLS). This imaging step provides microcrystal coordinates for automated serial data collection at a microfocus macromolecular crystallography beamline on samples with an essentially flat geometry. This prelocation method was applied to microcrystals of a soluble protein and a membrane protein, grown in a commonly used double-sandwich in situ crystallization plate. The inner sandwiches of thin plastic film enclosing the microcrystals in lipid cubic phase were flash cooled and imaged at TOMCAT. Based on the obtained crystal coordinates, both still and rotation wedge serial data were collected automatically at the SLS PXI beamline, yielding in both cases a high indexing rate. This workflow can be easily implemented at many synchrotron facilities using existing equipment, or potentially integrated as an online technique in the next-generation macromolecular crystallography beamline, and thus benefit a number of dose-sensitive challenging protein targets.

Spectral x-ray imaging: Conditions under which propagation-based phase-contrast is beneficial

Energy-resolved attenuation data in spectral x-ray imaging enables material decomposition, in which the different materials inside an object can be identified and separated virtually. Material decomposition has the drawback of increased noise in the resulting material images relative to the measured images. Recently, spectral x-ray imaging was combined with propagation-based x-ray phase-contrast imaging, an x-ray technique that has the potential to greatly reduce image noise by utilizing wave-optical effects. The net combined effects on image noise of performing spectral material decomposition with phase-contrast are not yet well understood, and we provide a detailed theoretical investigation of this topic here. In particular, we investigate how the addition of phase-contrast in spectral imaging affects material decomposition compared to using conventional spectral attenuation data. We show how the underlying equations can be rearranged into parts that resemble low- and high-pass filters on the input images, from which we are able to identify different energy-dependent cases where phase-contrast is or is not advantageous. Our results suggest that the benefits of phase-contrast in the context of material decomposition are primarily restricted to x-ray energies under a certain threshold, where that threshold depends on the given material combination, and sits in a region where photoelectric absorption dominates x-ray attenuation. Additionally, we show that decomposition of the electron density using an image basis spanned by functions of the Alvarez-Macovski model benefits from phase-contrast, regardless of the x-ray energies. All our findings are based purely on theoretical considerations, and can, therefore, be used to determine the feasibility and utility of propagation-based phase-contrast in spectral x-ray imaging ahead of any data collection.

Experimental optimization of X-ray propagation-based phase contrast imaging geometry.

Propagation-based phase contrast imaging (PB-PCI) with an X-ray lab source is a powerful technique to study low absorption samples, e.g. soft tissue or plastics, on the micrometer scale but is often limited by the low flux and coherence of the source. The setup geometry is essential for the performance since there is a trade-off where a short source distance yields a high contrast-to-noise ratio (CNR) but a low relative fringe contrast. While theoretical optimization strategies based on Fresnel propagation have been reported, there is a need for experimental testing of these models. Here, we systematically investigate this trade-off experimentally using two different setups with high-resolution detectors: a custom-built system with a Cu X-ray source and a commercial system (Zeiss Xradia) with a W source. The fringe contrast, CNR and fringe separation for a low-absorption test sample were measured for 130 different combinations of magnification and overall distances. We find that these figures-of-merit are sensitive to the magnification and that an optimum can be found that is independent of the overall source-detector distance. In general, we find that the theoretical models show excellent agreement with the measurements. However, this requires the complicated X-ray spectrum to be considered, in particular for the broadband W source.

The versatile X-ray beamline of the Munich Compact Light Source: design, instrumentation and applications.

Inverse Compton scattering provides means to generate low-divergence partially coherent quasi-monochromatic, i.e. synchrotron-like, X-ray radiation on a laboratory scale. This enables the transfer of synchrotron techniques into university or industrial environments. Here, the Munich Compact Light Source is presented, which is such a compact synchrotron radiation facility based on an inverse Compton X-ray source (ICS). The recent improvements of the ICS are reported first and then the various experimental techniques which are most suited to the ICS installed at the Technical University of Munich are reviewed. For the latter, a multipurpose X-ray application beamline with two end-stations was designed. The beamline's design and geometry are presented in detail including the different set-ups as well as the available detector options. Application examples of the classes of experiments that can be performed are summarized afterwards. Among them are dynamic in vivo respiratory imaging, propagation-based phase-contrast imaging, grating-based phase-contrast imaging, X-ray microtomography, K-edge subtraction imaging and X-ray spectroscopy. Finally, plans to upgrade the beamline in order to enhance its capabilities are discussed.

Evaluation of the Weighted Mean X-ray Energy for an Imaging System Via Propagation-Based Phase-Contrast Imaging.

For imaging events of extremely short duration, like shock waves or explosions, it is necessary to be able to image the object with a single-shot exposure. A suitable setup is given by a laser-induced X-ray source such as the one that can be found at GSI (Helmholtzzentrum für Schwerionenforschung GmbH) in Darmstadt (Society for Heavy Ion Research), Germany. There, it is possible to direct a pulse from the high-energy laser Petawatt High Energy Laser for Heavy Ion eXperiments (PHELIX) on a tungsten wire to generate a picosecond polychromatic X-ray pulse, called backlighter. For grating-based single-shot phase-contrast imaging of shock waves or exploding wires, it is important to know the weighted mean energy of the X-ray spectrum for choosing a suitable setup. In propagation-based phase-contrast imaging the knowledge of the weighted mean energy is necessary to be able to reconstruct quantitative phase images of unknown objects. Hence, we developed a method to evaluate the weighted mean energy of the X-ray backlighter spectrum using propagation-based phase-contrast images. In a first step wave-field simulations are performed to verify the results. Furthermore, our evaluation is cross-checked with monochromatic synchrotron measurements with known energy at Diamond Light Source (DLS, Didcot, UK) for proof of concepts.

Material Decomposition Using Spectral Propagation-Based Phase-Contrast X-Ray Imaging.

Material decomposition in X-ray imaging uses the energy-dependence of attenuation to digitally decompose an object into specific constituent materials, generally at the cost of enhanced image noise. Propagation-based X-ray phase-contrast imaging is a developing technique that can be used to reduce image noise, in particular from weakly attenuating objects. In this paper, we combine spectral phase-contrast imaging with material decomposition to both better visualize weakly attenuating features and separate them from overlying objects in radiography. We derive an algorithm that performs both tasks simultaneously and verify it against numerical simulations and experimental measurements of ideal two-component samples composed of pure aluminum and poly(methyl methacrylate). Additionally, we showcase first imaging results of a rabbit kitten's lung. The attenuation signal of a thorax, in particular, is dominated by the strongly attenuating bones of the ribcage. Combined with the weak soft tissue signal, this makes it difficult to visualize the fine anatomical structures across the whole lung. In all cases, clean material decomposition was achieved, without residual phase-contrast effects, from which we generate an un-obstructed image of the lung, free of bones. Spectral propagation-based phase-contrast imaging has the potential to be a valuable tool, not only in future lung research, but also in other systems for which phase-contrast imaging in combination with material decomposition proves to be advantageous.

A phase-retrieval toolbox for X-ray holography and tomography.

Propagation-based phase-contrast X-ray imaging is by now a well established imaging technique, which - as a full-field technique - is particularly useful for tomography applications. Since it can be implemented with synchrotron radiation and at laboratory micro-focus sources, it covers a wide range of applications. A limiting factor in its development has been the phase-retrieval step, which was often performed using methods with a limited regime of applicability, typically based on linearization. In this work, a much larger set of algorithms, which covers a wide range of cases (experimental parameters, objects and constraints), is compiled into a single toolbox - the HoloTomoToolbox - which is made publicly available. Importantly, the unified structure of the implemented phase-retrieval functions facilitates their use and performance test on different experimental data.

Photon-counting, energy-resolving and super-resolution phase contrast X-ray imaging using an integrating detector.

This work demonstrates the use of a scientific-CMOS (sCMOS) energy-integrating detector as a photon-counting detector, thereby eliminating dark current and read-out noise issues, that simultaneously provides both energy resolution and sub-pixel spatial resolution for X-ray imaging. These capabilities are obtained by analyzing visible light photon clouds that result when X-ray photons produce fluorescence from a scintillator in front of the visible light sensor. Using low-fluence monochromatic X-ray projections to avoid overlapping photon clouds, the centroid of individual X-ray photon interactions was identified. This enabled a tripling of the spatial resolution of the detector to 6.71 ± 0.04 µm. By calculating the total charge deposited by this interaction, an energy resolution of 61.2 ± 0.1% at 17 keV was obtained. When combined with propagation-based phase contrast imaging and phase retrieval, a signal-to-noise ratio of up to 15 ± 3 was achieved for an X-ray fluence of less than 3 photons/mm2.

Three-dimensional visualization of microvasculature from few-projection data using a novel CT reconstruction algorithm for propagation-based X-ray phase-contrast imaging.

Propagation-based X-ray phase-contrast imaging (PBI) is a powerful nondestructive imaging technique that can reveal the internal detailed structures in weakly absorbing samples. Extending PBI to CT (PBCT) enables high-resolution and high-contrast 3D visualization of microvasculature, which can be used for the understanding, diagnosis and therapy of diseases involving vasculopathy, such as cardiovascular disease, stroke and tumor. However, the long scan time for PBCT impedes its wider use in biomedical and preclinical microvascular studies. To address this issue, a novel CT reconstruction algorithm for PBCT is presented that aims at shortening the scan time for microvascular samples by reducing the number of projections while maintaining the high quality of reconstructed images. The proposed algorithm combines the filtered backprojection method into the iterative reconstruction framework, and a weighted guided image filtering approach (WGIF) is utilized to optimize the intermediate reconstructed images. Notably, the homogeneity assumption on the microvasculature sample is adopted as prior knowledge, and therefore, a prior image of microvasculature structures can be acquired by a k-means clustering approach. Then, the prior image is used as the guided image in the WGIF procedure to effectively suppress streaking artifacts and preserve microvasculature structures. To evaluate the effectiveness and capability of the proposed algorithm, simulation experiments on 3D microvasculature numerical phantom and real experiments with CT reconstruction on the microvasculature sample are performed. The results demonstrate that the proposed algorithm can, under noise-free and noisy conditions, significantly reduce the artifacts and effectively preserve the microvasculature structures on the reconstructed images and thus enables it to be used for clear and accurate 3D visualization of microvasculature from few-projection data. Therefore, for 3D visualization of microvasculature, the proposed algorithm can be considered an effective approach for reducing the scan time required by PBCT.