Recent advances in edge illumination x-ray phase-contrast tomography

Edge illumination (EI) is an x-ray phase-contrast imaging technique, exploiting sensitivity to x-ray refraction to visualize features, which are often not detected by conventional absorption-based radiography. The method does not require a high degree of spatial coherence and is achromatic and, therefore, can be implemented with both synchrotron radiation and commercial x-ray tubes. Using different retrieval algorithms, information about an object's attenuation, refraction, and scattering properties can be obtained. In recent years, a theoretical framework has been developed that enables EI computed tomography (CT) and, hence, three-dimensional imaging. This review provides a summary of these advances, covering the development of different image acquisition schemes, retrieval approaches, and applications. These developments constitute an integral part in the transformation of EI CT into a widely spread imaging tool for use in a range of fields.

Edge illumination X-ray phase tomography of multi-material samples using a single-image phase retrieval algorithm

In this paper we present a single-image phase retrieval algorithm for multi-material samples, developed for the edge illumination (EI) X-ray phase contrast imaging method. The theoretical derivation is provided, along with any assumptions made. The algorithm is evaluated quantitatively using both simulated and experimental results from a computed tomography (CT) scan using the EI laboratory implementation. Qualitative CT results are provided for a biological sample containing both bone and soft-tissue. Using a single EI image per projection and knowledge of the complex refractive index, the algorithm can accurately retrieve the interface between a given pair of materials. A composite CT slice can be created by splicing together multiple CT reconstructions, each retrieved for a different pair of materials.

A method for high-energy, low-dose mammography using edge illumination x-ray phase-contrast imaging

Since the breast is one of the most radiosensitive organs, mammography is arguably the area where lowering radiation dose is of the uttermost importance. Phase-based x-ray imaging methods can provide opportunities in this sense, since they do not require x-rays to be stopped in tissue for image contrast to be generated. Therefore, x-ray energy can be considerably increased compared to those usually exploited by conventional mammography. In this article we show how a novel, optimized approach can lead to considerable dose reductions. This was achieved by matching the edge-illumination phase method, which reaches very high angular sensitivity also at high x-ray energies, to an appropriate image processing algorithm and to a virtually noise-free detection technology capable of reaching almost 100% efficiency at the same energies. Importantly, while proof-of-concept was obtained at a synchrotron, the method has potential for a translation to conventional sources.

Concept of contrast transfer function for edge illumination x-ray phase-contrast imaging and its comparison with the free-space propagation technique

Previous studies on edge illumination (EI) X-ray phase-contrast imaging (XPCi) have investigated the nature and amplitude of the signal provided by this technique. However, the response of the imaging system to different object spatial frequencies was never explicitly considered and studied. This is required in order to predict the performance of a given EI setup for different classes of objects. To this scope, in the present work we derive analytical expressions for the contrast transfer function of an EI imaging system, using the approximation of near-field regime, and study its dependence upon the main experimental parameters. We then exploit these results to compare the frequency response of an EI system with respect of that of a free-space propagation XPCi one. The results achieved in this work can be useful for predicting the signals obtainable for different types of objects and also as a basis for new retrieval methods.

High contrast microstructural visualization of natural acellular matrices by means of phase-based x-ray tomography

Acellular scaffolds obtained via decellularization are a key instrument in regenerative medicine both per se and to drive the development of future-generation synthetic scaffolds that could become available off-the-shelf. In this framework, imaging is key to the understanding of the scaffolds’ internal structure as well as their interaction with cells and other organs, including ideally post-implantation. Scaffolds of a wide range of intricate organs (esophagus, lung, liver and small intestine) were imaged with x-ray phase contrast computed tomography (PC-CT). Image quality was sufficiently high to visualize scaffold microarchitecture and to detect major anatomical features, such as the esophageal mucosal-submucosal separation, pulmonary alveoli and intestinal villi. These results are a long-sought step for the field of regenerative medicine; until now, histology and scanning electron microscopy have been the gold standard to study the scaffold structure. However, they are both destructive: hence, they are not suitable for imaging scaffolds prior to transplantation, and have no prospect for post-transplantation use. PC-CT, on the other hand, is non-destructive, 3D and fully quantitative. Importantly, not only do we demonstrate achievement of high image quality at two different synchrotron facilities, but also with commercial x-ray equipment, which makes the method available to any research laboratory.

X-ray phase contrast tomography; proof of principle for post-mortem imaging

OBJECTIVE

To demonstrate the feasibility of using X-ray phase-contrast tomography to assess internal organs in a post-mortem piglet model, as a possible non-invasive imaging autopsy technique.

METHODS

Tomographic images of a new-born piglet were obtained using a free-space propagation X-ray phase-contrast imaging setup at a synchrotron (European Synchrotron Radiation Facility, Grenoble, France). A monochromatic X-ray beam (52 keV) was used in combination with a detector pixel size of 46 × 46 µm(2). A phase-retrieval algorithm was applied to all projections, which were then reconstructed into tomograms using the filtered-back projection algorithm. Images were assessed for diagnostic quality.

RESULTS

Images obtained with the free-space propagation setup presented high soft-tissue contrast and sufficient resolution for resolving organ structure. All of the main body organs (heart, lungs, kidneys, liver and intestines) were easily identified and adequately visualized. In addition, grey/white matter differentiation in the cerebellum while still contained within the skull was shown.

CONCLUSION

The feasibility of using X-ray phase-contrast tomography as a post-mortem imaging technique in an animal model has been demonstrated. Future studies will focus on translating this experiment to a laboratory-based setup.

ADVANCES IN KNOWLEDGE

Appropriate image processing and analysis enable the simultaneous visualization of both soft- and hard-tissue structures in X-ray phase-contrast images of a complex, thick sample.

X-ray absorption, phase and dark-field tomography through a beam tracking approach

We present a development of the beam-tracking approach that allows its implementation in computed tomography. One absorbing mask placed before the sample and a high resolution detector are used to track variations in the beam intensity distribution caused by the sample. Absorption, refraction, and dark-field are retrieved through a multi-Gaussian interpolation of the beam. Standard filtered back projection is used to reconstruct three dimensional maps of the real and imaginary part of the refractive index, and of the dark-field signal. While the method is here demonstrated using synchrotron radiation, its low coherence requirements suggest a possible implementation with laboratory sources.

Volumetric quantitative characterization of human patellar cartilage with topological and geometrical features on phase-contrast X-ray computed tomography

Phase-contrast X-ray computed tomography (PCI-CT) has attracted significant interest in recent years for its ability to provide significantly improved image contrast in low absorbing materials such as soft biological tissue. In the research context of cartilage imaging, previous studies have demonstrated the ability of PCI-CT to visualize structural details of human patellar cartilage matrix and capture changes to chondrocyte organization induced by osteoarthritis. This study evaluates the use of geometrical and topological features for volumetric characterization of such chondrocyte patterns in the presence (or absence) of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and topological features derived from Minkowski Functionals were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). Our results show that the classification performance of SIM-derived geometrical features (AUC: 0.90 ± 0.09) is significantly better than Minkowski Functionals volume (AUC: 0.54 ± 0.02), surface (AUC: 0.72 ± 0.06), mean breadth (AUC: 0.74 ± 0.06) and Euler characteristic (AUC: 0.78 ± 0.04) (p < 10(-4)). These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as diagnostic imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

Note: Design and realization of a portable edge illumination X-ray phase contrast imaging system

We discuss a portable edge illumination x-ray phase contrast imaging system based on compact piezoelectric motors, which enables its transportation to different environments, e.g., hosting different x-ray source technologies. The analysis of images of standard samples reveals an angular sensitivity of 270 ± 6 nrad, which compares well with the 260 ± 10 nrad reported for previous systems based on stepper motors, demonstrating that system portability can be achieved without affecting phase sensitivity. The results can also be considered a test of the performance of the piezoelectric motors, and as such could be of interest to researchers planning their use in other imaging systems.

Single-image phase retrieval using an edge illumination X-ray phase-contrast imaging setup

A method is proposed which enables the retrieval of the thickness or of the projected electron density of a sample from a single input image acquired with an edge illumination phase-contrast imaging setup. The method assumes the case of a quasi-homogeneous sample, i.e. a sample with a constant ratio between the real and imaginary parts of its complex refractive index. Compared with current methods based on combining two edge illumination images acquired in different configurations of the setup, this new approach presents advantages in terms of simplicity of acquisition procedure and shorter data collection time, which are very important especially for applications such as computed tomography and dynamical imaging. Furthermore, the fact that phase information is directly extracted, instead of its derivative, can enable a simpler image interpretation and be beneficial for subsequent processing such as segmentation. The method is first theoretically derived and its conditions of applicability defined. Quantitative accuracy in the case of homogeneous objects as well as enhanced image quality for the imaging of complex biological samples are demonstrated through experiments at two synchrotron radiation facilities. The large range of applicability, the robustness against noise and the need for only one input image suggest a high potential for investigations in various research subjects.

Achromatic approach to phase-based multi-modal imaging with conventional X-ray sources

Compatibility with polychromatic radiation is an important requirement for an imaging system using conventional rotating anode X-ray sources. With a commercially available energy-resolving single-photon-counting detector we investigated how broadband radiation affects the performance of a multi-modal edge-illumination phase-contrast imaging system. The effect of X-ray energy on phase retrieval is presented, and the achromaticity of the method is experimentally demonstrated. Comparison with simulated measurements integrating over the energy spectrum shows that there is no significant loss of image quality due to the use of polychromatic radiation. This means that, to a good approximation, the imaging system exploits radiation in the same way at all energies typically used in hard-X-ray imaging.

Volumetric Characterization of Human Patellar Cartilage Matrix on Phase Contrast X-Ray Computed Tomography

Phase contrast X-ray computed tomography (PCI-CT) has recently emerged as a novel imaging technique that allows visualization of cartilage soft tissue, subsequent examination of chondrocyte patterns, and their correlation to osteoarthritis. Previous studies have shown that 2D texture features are effective at distinguishing between healthy and osteoarthritic regions of interest annotated in the radial zone of cartilage matrix on PCI-CT images. In this study, we further extend the texture analysis to 3D and investigate the ability of volumetric texture features at characterizing chondrocyte patterns in the cartilage matrix for purposes of classification. Here, we extracted volumetric texture features derived from Minkowski Functionals and gray-level co-occurrence matrices (GLCM) from 496 volumes of interest (VOI) annotated on PCI-CT images of human patellar cartilage specimens. The extracted features were then used in a machine-learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with GLCM features correlation (AUC = 0.83 ± 0.06) and homogeneity (AUC = 0.82 ± 0.07), which significantly outperformed all Minkowski Functionals (p < 0.05). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving GLCM-derived statistical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.

Computer-aided diagnosis for phase-contrast X-ray computed tomography: quantitative characterization of human patellar cartilage with high-dimensional geometric features

Phase-contrast computed tomography (PCI-CT) has shown tremendous potential as an imaging modality for visualizing human cartilage with high spatial resolution. Previous studies have demonstrated the ability of PCI-CT to visualize (1) structural details of the human patellar cartilage matrix and (2) changes to chondrocyte organization induced by osteoarthritis. This study investigates the use of high-dimensional geometric features in characterizing such chondrocyte patterns in the presence or absence of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and statistical features derived from gray-level co-occurrence matrices were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic curve (AUC). SIM-derived geometrical features exhibited the best classification performance (AUC, 0.95 ± 0.06) and were most robust to changes in ROI size. These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated and non-subjective manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

On the origin of contrast in edge illumination X-ray phase-contrast imaging

Edge illumination (EI) has emerged as an X-ray phase-contrast imaging (XPCi) modality which could present significant advantages in terms of translation to clinical and laboratory applications. In this paper, we model its signal through the use of the "transport of intensity" equation. The validity conditions for this approach and its relationship with previous theoretical models for EI XPCi are discussed. The proposed model enables a simple estimation of the different contributions to the signal, which is shown to complement previously obtained results. In particular, it allows taking into account the effect of both slowly and rapidly varying refraction angles, corresponding to large and small object features. The derived framework is then used to investigate the effect on the signal of the smoothness of the mask edges, of the blurring from the source size and of the width of the object edge.

Phase retrieval through a one-dimensional ptychographic engine

Ptychographic techniques are currently the subject of increasing scientific interest due to their capability to retrieve the complex transmission function of an object at very high resolution. However, they impose a substantial burden in terms of acquisition time and dimension of the scanned area, which limits the range of samples that can be studied. We have developed a new method that combines the ptychographic approach in one direction with Fresnel propagation in the other by employing a strongly asymmetric probe. This enables scanning the sample in one direction only, substantially reducing exposure times while covering a large field of view. This approach sacrifices ptychographic-related resolution in one direction, but removes any limitation on the probe dimension in the direction orthogonal to the scanning, enabling the scan of relatively large objects without compromising exposure times.

Spatial resolution of edge illumination X-ray phase-contrast imaging

We analyze the spatial resolution of edge illumination X-ray phase-contrast imaging and its dependence upon various experimental parameters such as source size, source-to-sample and sample-to-detector distances, X-ray energy and size of the beam-shaping aperture. Different propagation regimes, as well as the beam divergence and polychromaticity encountered with laboratory sources, are also considered. We show that spatial resolution in edge illumination phase-contrast imaging presents peculiar features compared to other X-ray phase-contrast techniques. In particular, in the direction orthogonal to the s or mask lines used to shape the beam, this can be better than both the pixel dimension and the projected source size. Numerical simulations based on Fresnel diffraction integrals are presented, which confirm the analytical predictions. The obtained results allow a simple estimation of the spatial resolution for edge-illumination phase imaging in both synchrotron and laboratory setups.

Phase-contrast microscopy at high x-ray energy with a laboratory setup

We report on the design and realization of an x-ray imaging system for quantitative phase-contrast microscopy at high x-ray energy with laboratory-scale instrumentation. Phase and amplitude were separated quantitatively at x-ray energies up to 80 keV with micrometric spatial resolution. The accuracy of the results was tested against numerical simulations, and the spatial resolution was experimentally quantified by measuring a Siemens star phase object. This simple setup should find broad application in those areas of x-ray imaging where high energy and spatial resolution are simultaneously required and in those difficult cases where the sample contains materials with similar x-ray absorption.

Monte Carlo model of a polychromatic laboratory based edge illumination x-ray phase contrast system

A Monte Carlo model of a polychromatic laboratory based (coded aperture) edge illumination x-ray phase contrast imaging system has been developed and validated against experimental data. The ability for the simulation framework to be used to model two-dimensional images is also shown. The Monte Carlo model has been developed using the McXtrace engine and is polychromatic, i.e., results are obtained through the use of the full x-ray spectrum rather than an effective energy. This type of simulation can in future be used to model imaging of objects with complex geometry, for system prototyping, as well as providing a first step towards the development of a simulation for modelling dose delivery as a part of translating the imaging technique for use in clinical environments.

Theory and preliminary experimental verification of quantitative edge illumination x-ray phase contrast tomography

X-ray phase contrast imaging (XPCi) methods are sensitive to phase in addition to attenuation effects and, therefore, can achieve improved image contrast for weakly attenuating materials, such as often encountered in biomedical applications. Several XPCi methods exist, most of which have already been implemented in computed tomographic (CT) modality, thus allowing volumetric imaging. The Edge Illumination (EI) XPCi method had, until now, not been implemented as a CT modality. This article provides indications that quantitative 3D maps of an object's phase and attenuation can be reconstructed from EI XPCi measurements. Moreover, a theory for the reconstruction of combined phase and attenuation maps is presented. Both reconstruction strategies find applications in tissue characterisation and the identification of faint, weakly attenuating details. Experimental results for wires of known materials and for a biological object validate the theory and confirm the superiority of the phase over conventional, attenuation-based image contrast.

Low-dose phase contrast mammography with conventional x-ray sources

PURPOSE

To provide an x-ray phase contrast imaging (XPCI) method working with conventional sources that could be readily translated into clinical practice. XPCI shows potential in synchrotron studies but attempts at translating it for use with conventional sources are subject to limitations in terms of field of view, stability, exposure time, and possibly most importantly, delivered dose.

METHODS

Following the adaptation of our "edge-illumination" XPCI technique for use with conventional x-ray sources through the use of x-ray masks, the authors have further modified the design of such masks to allow further reducing the dose delivered to the sample without affecting the phase sensitivity of the method.

RESULTS

The authors have built a prototype based on the new mask design and used it to image ex vivo breast tissue samples containing malignant lesions. The authors compared images acquired with this prototype to those obtained with a conventional system. The authors demonstrate and quantify image improvements, especially in terms of microcalcification detection. On calcifications detected also by the conventional system, the authors measure contrast increases from five to nine fold; calcifications and other features were also detected which are completely invisible in the conventional image. Dose measurements confirmed that the above enhancements were achieved while delivering doses compatible with clinical practice.

CONCLUSIONS

The authors obtained phase-related image enhancements in mammography by means of a system built with components available off-the-shelf that operates under exposure time and dose conditions compatible with clinical practice. This opens the way to a straightforward translation of phase enhanced imaging methods into clinical practice.

Phase contrast imaging X-ray computed tomography: Quantitative characterization of human patellar cartilage matrix with topological and geometrical features

Current assessment of cartilage is primarily based on identification of indirect markers such as joint space narrowing and increased subchondral bone density on x-ray images. In this context, phase contrast CT imaging (PCI-CT) has recently emerged as a novel imaging technique that allows a direct examination of chondrocyte patterns and their correlation to osteoarthritis through visualization of cartilage soft tissue. This study investigates the use of topological and geometrical approaches for characterizing chondrocyte patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage. For this purpose, topological features derived from Minkowski Functionals and geometric features derived from the Scaling Index Method (SIM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of healthy and osteoarthritic specimens of human patellar cartilage. The extracted features were then used in a machine learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with high-dimensional geometrical feature vectors derived from SIM (0.95 ± 0.06) which outperformed all Minkowski Functionals (p < 0.001). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving SIM-derived geometrical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Strategies for efficient and fast wave optics simulation of coded-aperture and other x-ray phase-contrast imaging methods

We derive a Fourier formulation of coded-aperture x-ray phase-contrast imaging, based on the wave theory of optics in the Fresnel approximation. We use this model to develop a flexible, efficient, and general simulation algorithm that can be easily adapted to other implementations of x-ray phase contrast imaging. Likewise, the algorithm enables a simple extension to 2D aperture designs, different acquisition schemes, etc. Problems related to numerical implementation of the algorithm are analyzed in detail, and simple rules are derived that enable us to avoid or at least mitigate them. Finally, comparisons with experimental data and data obtained with a different simulation algorithm are presented to validate the model and demonstrate its advantages in practical implementations. This also enabled us to demonstrate an increase in computational speed of more than one order of magnitude over a previous algorithm.

Computer-aided diagnosis in phase contrast imaging X-ray computed tomography for quantitative characterization of ex vivo human patellar cartilage

Visualization of ex vivo human patellar cartilage matrix through the phase contrast imaging X-ray computed tomography (PCI-CT) has been previously demonstrated. Such studies revealed osteoarthritis-induced changes to chondrocyte organization in the radial zone. This study investigates the application of texture analysis to characterizing such chondrocyte patterns in the presence and absence of osteoarthritic damage. Texture features derived from Minkowski functionals (MF) and gray-level co-occurrence matrices (GLCM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These texture features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). The best classification performance was observed with the MF features perimeter (AUC: 0.94 ±0.08 ) and "Euler characteristic" (AUC: 0.94 ±0.07 ), and GLCM-derived feature "Correlation" (AUC: 0.93 ±0.07). These results suggest that such texture features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix, enabling classification of cartilage as healthy or osteoarthritic with high accuracy.

X-ray phase-contrast imaging with nanoradian angular resolution

We present a new quantitative x-ray phase-contrast imaging method based on the edge illumination principle, which allows achieving unprecedented nanoradian sensitivity. The extremely high angular resolution is demonstrated theoretically and through experimental images obtained at two different synchrotron radiation facilities. The results, achieved at both very high and very low x-ray energies, show that this highly sensitive technique can be efficiently exploited over a very broad range of experimental conditions. This method can open the way to new, previously inaccessible scientific applications in various fields including biology, medicine and materials science.

Characterizing healthy and osteoarthritic knee cartilage on phase contrast CT with geometric texture features

The current approach to evaluating cartilage degeneration at the knee joint requires visualization of the joint space on radiographic images where indirect cues such as joint space narrowing serve as markers for osteoarthritis. A recent novel approach to visualizing the knee cartilage matrix using phase contrast imaging (PCI) with computed tomography (CT) was shown to allow direct examination of chondrocyte patterns and their subsequent correlation to osteoarthritis. This study aims to characterize chondrocyte cell patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage through texture analysis. Statistical features derived from gray-level co-occurrence matrices (GLCM) and geometric features derived from the Scaling Index Method (SIM) were extracted from 404 regions of interest (ROI) annotated on PCI images of healthy and osteoarthritic specimens of knee cartilage. These texture features were then used in a machine learning task to classify ROIs as healthy or osteoarthritic. A fuzzy k-nearest neighbor classifier was used and its performance was evaluated using the area under the Receiver Operating Characteristic (ROC) curve (AUC). The best classification performance was observed with high-dimensional geometrical feature vectors derived from SIM and GLCM correlation features. With the experimental conditions used in this study, both SIM and GLCM achieved a high classification performance (AUC value of 0.98) in the task of distinguishing between healthy and osteoarthritic ROIs. These results show that such quantitative analysis of chondrocyte patterns in the knee cartilage matrix can distinguish between healthy and osteoarthritic tissue with high accuracy.

Analytical and experimental determination of signal-to-noise ratio and figure of merit in three phase-contrast imaging techniques

We present a theoretical and experimental comparison of three X-ray phase-contrast techniques: propagation-based imaging, analyzer-based imaging and grating interferometry. The signal-to-noise ratio and the figure of merit are quantitatively compared for the three techniques on the same phantoms and using the same X-ray source and detector. Principal dependencies of the signal upon the numerous acquisition parameters, the spatial resolution and X-ray energy are discussed in detail. The sensitivity of each technique, in terms of the smallest detectable phase shift, is also evaluated.

High-resolution breast tomography at high energy: a feasibility study of phase contrast imaging on a whole breast

Previous studies on phase contrast imaging (PCI) mammography have demonstrated an enhancement of breast morphology and cancerous tissue visualization compared to conventional imaging. We show here the first results of the PCI analyser-based imaging (ABI) in computed tomography (CT) mode on whole and large (>12 cm) tumour-bearing breast tissues. We demonstrate in this work the capability of the technique of working at high x-ray energies and producing high-contrast images of large and complex specimens. One entire breast of an 80-year-old woman with invasive ductal cancer was imaged using ABI-CT with monochromatic 70 keV x-rays and an area detector of 92×92 µm² pixel size. Sagittal slices were reconstructed from the acquired data, and compared to corresponding histological sections. Comparison with conventional absorption-based CT was also performed. Five blinded radiologists quantitatively evaluated the visual aspects of the ABI-CT images with respect to sharpness, soft tissue contrast, tissue boundaries and the discrimination of different structures/tissues. ABI-CT excellently depicted the entire 3D architecture of the breast volume by providing high-resolution and high-contrast images of the normal and cancerous breast tissues. These results are an important step in the evolution of PCI-CT towards its clinical implementation.

Amplification of the phase contrast signal at very high x-ray energies

X-ray phase contrast imaging is increasingly being used in several fields, both at synchrotron facilities and with laboratory sources, due to its increased sensitivity compared to conventional x-ray methods. One important problem is the development of methods to make it suitable for use at very high x-ray energies, needed in many applications. We show how the edge illumination concept, which stands at the basis of the coded-aperture method, allows achieving hyperintense phase signals at energies close to 100 keV, by showing images of both weak phase objects and highly absorbing fossils with a high iron content.

Theoretical comparison of three X-ray phase-contrast imaging techniques: propagation-based imaging, analyzer-based imaging and grating interferometry

Various X-ray phase-contrast imaging techniques have been developed and applied over the last twenty years in different domains, such as material sciences, biology and medicine. However, no comprehensive inter-comparison exists in the literature. We present here a theoretical study that compares three among the most used techniques: propagation-based imaging (PBI), analyzer-based imaging (ABI) and grating interferometry (GI). These techniques are evaluated in terms of signal-to-noise ratio, figure of merit and spatial resolution. Both area and edge signals are considered. Dependences upon the object properties (absorption, phase shift) and the experimental acquisition parameters (energy, system point-spread function etc.) are derived and discussed. The results obtained from this analysis can be used as the reference for determining the most suitable technique for a given application.

A simplified approach for computed tomography with an X-ray grating interferometer

We present a simplified acquisition and processing method for X-ray grating interferometry computed tomography (CT). The proposed approach eliminates the need to scan the gratings, thus allowing for a faster CT acquisition compared to methods presently in use. The contrast in the reconstructed images can be expressed as a linear combination of the absorption and refraction within the sample. Experimental images of a test phantom made of known materials and a human bone-cartilage sample prove the correctness of the method and show very good agreement with the theory. The here proposed approach might be highly interesting in many fields where a reduced imaging acquisition time is requested and/or where the radiation dose delivered to the sample has to be kept low, such as, for example, in in-vivo imaging.

In vivo x-ray phase contrast analyzer-based imaging for longitudinal osteoarthritis studies in guinea pigs

Over the last two decades phase contrast x-ray imaging techniques have been extensively studied for applications in the biomedical field. Published results demonstrate the high capability of these imaging modalities of improving the image contrast of biological samples with respect to standard absorption-based radiography and routinely used clinical imaging techniques. A clear depiction of the anatomic structures and a more accurate disease diagnosis may be provided by using radiation doses comparable to or lower than those used in current clinical methods. In the literature many works show images of phantoms and excised biological samples proving the high sensitivity of the phase contrast imaging methods for in vitro investigations. In this scenario, the applications of the so-called analyzer-based x-ray imaging (ABI) phase contrast technique are particularly noteworthy. The objective of this work is to demonstrate the feasibility of in vivo x-ray ABI phase contrast imaging for biomedical applications and in particular with respect to joint anatomic depiction and osteoarthritis detection. ABI in planar and tomographic modes was performed in vivo on articular joints of guinea pigs in order to investigate the animals with respect to osteoarthritis by using highly monochromatic x-rays of 52 keV and a low noise detector with a pixel size of 47 × 47 µm(2). Images give strong evidence of the ability of ABI in depicting both anatomic structures in complex systems as living organisms and all known signs of osteoarthritis with high contrast, high spatial resolution and with an acceptable radiation dose. This paper presents the first proof of principle study of in vivo application of ABI. The technical challenges encountered when imaging an animal in vivo are discussed. This experimental study is an important step toward the study of clinical applications of phase contrast x-ray imaging techniques.