Search

Recent trends in hard X-ray micro-computed tomography (microCT) aim at increasing both spatial and temporal resolutions. These challenges require intense photon beams. Filtered synchrotron radiation beams, also referred to as `pink beams', which are emitted by wigglers or bending magnets, meet this need, owing to their broad energy range. In this work, the new microCT station installed at the biomedical beamline ID17 of the European Synchrotron is described and an overview of the preliminary results obtained for different biomedical-imaging applications is given. This new instrument expands the capabilities of the beamline towards sub-micrometre voxel size scale and simultaneous multi-resolution imaging. The current setup allows the acquisition of tomographic datasets more than one order of magnitude faster than with a monochromatic beam configuration.

Purpose This study provides the first experimental application of multiscale three-dimensional (3D) X-ray Phase Contrast Imaging Computed Tomography (XPCI-CT) virtual histology for the inspection and quantitative assessment of the late stage effects of radio-induced lesions on lungs in a small animal model. Methods and Materials Healthy male Fischer rats were irradiated with X-ray standard broad beams and Microbeam Radiation Therapy (MRT), a high dose rate (14 kGy/s), FLASH spatially-fractionated X-ray therapy to avoid the beamlets smearing due to cardiosynchronous movements of the organs during the irradiation. After organ dissection, ex-vivo XPCI-CT was applied to all the samples and the results were quantitatively analysed and correlated to histologic data. Results XPCI-CT enables the 3D visualization of lung tissues with unprecedented contrast and sensitivity allowing alveoli, vessels and bronchi hierarchical visualization. XPCI-CT discriminates in 3D radio-induced lesions such as fibrotic scars, Ca/Fe deposits and, in addition, allows a full-organ accurate quantification of the fibrotic tissue within the irradiated organs. The radiation-induced fibrotic tissue content is less than 10% of the analyzed volume for all the MRT treated organs while it reaches the 34% in the case of irradiations with 50 Gy using a broad beam. Conclusions XPCI-CT is an effective imaging technique able to provide detailed 3D information for the assessment of lung pathology and treatment efficacy in a small animal model.

Chronic pain (CP) represents a complex pathology profoundly involving both neural and glial compartments of the central nervous system. While most CP studies have also investigated the macroscopic brain vascular system, its microstructural architecture still remains largely unexplored. Further, the adaptive modifications of the vascular microstructure as consequence of diseases or pathological insults did not receive adequate attention. Here we show microtomographic signs of diffuse and conspicuous microvascular neogenesis in somatosensory cortex of CP animal models already peaking at 15 days from the model instantiation. Progressive fading of this microvessel neogenesis then ensued in the next six months yet maintaining higher vascular density with a preserved small fraction of them. Due to the important consequences on the neuron-glial-vessel arrangements and on the resulting metabolic and functional disorders of the local networks, novel additional scenarios of CP are thus conceivable with profound consequences of potential future CP diagnostic and therapeutic appraisals. Significance Statement Chronic pain (CP) is an excruciating condition with various clinical presentations. Major signs are characterized by a rich repertoire of pain quality, intensity and length. While neuronal and glial anomalies have been associated to CP less attention has been granted to the micro-vessel and capillary compartments of the involved brain regions. Our research illustrates how the microvessel compartments of the somatosensory cortex in experimental animals present profound and long-lasting signs of extensive neogenesis (about fourfold) early within the first two weeks from the CP start, undergoing a slow and incomplete decline within six months. These results may change the CP clinical picture with potential novel therapeutic approaches to it.

Chronic pain (CP) is a condition characterized by a wide spectrum of clinical signs and symptoms, missing a sound modelling at the neuronal network scale. Recently, we presented a general theory showing common electrophysiological traits in different CP rat models, i.e. a collapse of relevant functional connectivity network properties, such as modularity, in the somatosensory thalamo-cortical (TC) network. In this work, we preliminary investigated by anin silicoaccurate simulator of the six-layer mammalian cortical networks that evidenced the crucial collapse of network modularity in CP simulated conditions and the consequent reduction of network adaptive processes. On this track, in studies on CP experimental animals affected by sciatic nerve multiple ligature (Bennett-Xie model), by synchrotron-generated X-ray microbeam (MB) irradiations (7 parallel beams, 100um width), we targetedin vivothe CP involved hindlimb somatosensory projection cortex that, because of the doses radiation (360 Gy, peak at each beam), non-invasively produced fast and precise tissue destruction along the 7 beam projections. These parcellated the cortical tissue and restored the cortical network statistics related to modularity and information processing efficiency as evidenced from post irradiationin vivoelectrophysiological recordings. In addition, by MB treatment there was an ensuing removal of behavioral signs of allodynia and hyperalgesia accompanied by recovered normal gait schemes yet preserving the normal sensory thresholds of the experimental rats up to three months after the MB irradiation. Finally, novel and unprecedented therapeutic appraisals for CP are devised.Significance StatementChronic pain (CP) is an excruciating condition with severe effects on patients’ life. Apart from many clinical and experimental studies no current theory on CP is generally accepted. Recently, we proposed a general theory of CP in experimental animals as characterized by strong alteration of the connections among neurons in different brain regions. We show here onin silicosimulations that specific connectivity changes in the somatosensory cortex recover the lost functional integrity. Concurrently, in experimental animals, we re-modulated,in vivo, some anatomical connections of the somatosensory cortex by extremely thin synchrotron generated X-ray microbeam irradiations. The resulting behavioral and electrophysiological signs of CP disappeared yet maintaining normal sensory responses. No adverse or pathological effects on blank animals were observable.

Objectives The purpose of our study was to evaluate the potential of x-ray propagation-based phase-contrast imaging (PCI) computed tomography (CT) for the detection and characterization of early changes after ischemia-reperfusion (IR) in a standardized rat liver transplantation (LTx) model. Materials and Methods Syngeneic orthotopic liver transplantation was performed in male Lewis rats. Ischemia-reperfusion injury (IRI)-induced changes of liver parenchyma were investigated in a time-dependent manner (2, 16, 24, and 32 hours). X-ray phase-contrast images of formalin-fixated liver specimens were acquired in CT mode by using a voxel size of 8 x 8 x 8 mu m(3). Necrapoptotic cell death was visualized with the TdT-mediated dUTP-biotin nick end labeling technique, and alterations of liver graft microhemodynamics, that is, acinar and sinusoidal perfusion failure, were evaluated by in vivo fluorescence microscopy. Results Acquired and reconstructed PCI-CT images showed an increase in necrotic liver parenchyma dependent on cold storage time, measuring 5.7% +/- 1.6% after 2 hours (comparable to 2.6% +/- 0.4% for sham livers), 11.5% +/- 2.1% (16 hours;P < 0.05 vs control), 23.0% +/- 0.5% (24 hours;P < 0.001 vs control), and 31.3% +/- 2.2% (32 hours;P < 0.001 vs control). There were a significant lower number of perfused acini in dependence on increasing cold storage time. The acinar perfusion index reached 0.970 +/- 0.006 after 2 hours of cold ischemia (comparable to 0.960 +/- 0.009 for sham livers) and declined continuously after 16, 24, and 32 hours cold ischemia (0.58 +/- 0.03, 0.49 +/- 0.02, 0.41 +/- 0.03, each P < 0.0001 vs controls). Comparable results were found for sinusoidal perfusion, reaching 1.8% +/- 0.4% of nonperfused sinusoids for 2 hours of cold ischemia and 8.2% +/- 0.8% after 16 hours, 18.8% +/- 1.4% after 24 hours, and 39.0% +/- 2.4% after 32 hours (each P < 0.0001 vs controls). Prolonged cold ischemia was associated with an increasing number of TdT-mediated dUTP-biotin nick end labeling-positive cells (hepatocytes and sinusoidal lining cells), reaching 0.4 +/- 0.1 (sham), 0.7 +/- 0.4 (2 hours), 6.4 +/- 1.1 (16 hours), 2.1 +/- 0.3 (24 hours), and 14.7 +/- 3.5 (32 hours;P = 0.002) for hepatocytes. Conclusions X-ray PCI of histological liver specimens can detect IR-induced tissue necrosis and can provide detailed complementary 3-dimensional information to standard histopathologic findings.

Background Dense and unbiased cellular-resolution representations of extended volumetric central nervous system soft-tissue anatomy are difficult to obtain, even in experimental post-mortem settings. Interestingly, X-ray phase-contrast computed tomography (X-PCI-CT), an emerging soft-tissue-sensitive volumetric imaging technique, can provide multiscale organ- to cellular-level morphological visualizations of neuroanatomical structure. New Method Here, we tested different nervous-tissue fixation procedures, conventionally used for transmission electron microscopy, to better establish X-PCI-CT-specific sample-preparation protocols. Extracted rat spinal medullas were alternatively fixed with a standard paraformaldehyde-only aldehyde-based protocol, or in combination with glutaraldehyde. Some specimens were additionally post-fixed with osmium tetroxide. Multiscale X-PCI-CT datasets were collected at several synchrotron radiation facilities, using state-of-the-art setups with effective image voxel sizes of 3.03 to 0.33 μm3, and compared to high-field magnetic resonance imaging, histology and vascular fluorescence microscopy data. Results Multiscale X-PCI-CT of aldehyde-fixed spinal cord specimens resulted in dense histology-like volumetric representations and quantifications of extended deep spinal micro-vascular networks and of intra-medullary cell populations. Osmium post-fixation increased intra-medullary contrast between white and gray-matter tissues, and enhanced delineation of intra-medullary cellular structure, e.g. axon fibers and motor neuron perikarya. Comparison with Existing Methods Volumetric X-PCI-CT provides complementary contrast and higher spatial resolution compared to 9.4 T MRI. X-PCI-CT’s advantage over planar histology is the volumetric nature of the cellular-level data obtained, using samples much larger than those fit for volumetric vascular fluorescence microscopy. Conclusions Deliberately choosing (post-)fixation protocols tailored for optimal nervous-tissue structural preservation is of paramount importance in achieving effective and targeted neuroimaging via the X-PCI-CT technique.

OBJECTIVE. The aim of this study was to quantitatively assess hyaline cartilage and subchondral bone conditions in a fully preserved cadaveric human knee joint using high-resolution x-ray propagation-based phase-contrast imaging (PBI) CT and to compare the performance of the new technique with conventional CT and MRI. MATERIALS AND METHODS. A cadaveric human knee was examined using an x-ray beam of 60 keV, a detector with a 90-mm 2 FOV, and a pixel size of 46 × 46 µm 2 . PBI CT images were reconstructed with both the filtered back projection algorithm and the equally sloped tomography method. Conventional 3-T MRI and CT were also performed. Measurements of cartilage thickness, cartilage lesions, International Cartilage Repair Society scoring, and detection of subchondral bone changes were evaluated. Visual inspection of the specimen akin to arthroscopy was conducted and served as a standard of reference for lesion detection. RESULTS. Loss of cartilage height was visible on PBI CT and MRI. Quantification of cartilage thickness showed a strong correlation between the two modalities. Cartilage lesions appeared darker than the adjacent cartilage on PBI CT. PBI CT showed similar agreement to MRI for depicting cartilage substance defects or lesions compared with the visual inspection. The assessment of subchondral bone cysts showed moderate to strong agreement between PBI CT and CT. CONCLUSION. In contrast to the standard clinical methods of MRI and CT, PBI CT is able to simultaneously depict cartilage and bony changes at high resolution. Though still an experimental technique, PBI CT is a promising high-resolution imaging method to evaluate comprehensive changes of osteoarthritic disease in a clinical setting.

CONTENTS 50.1 Introduction 50.2 General Considerations 50.3 Analyzer-Based Imaging 50.3.1 The Rocking Curve 50.3.2 A Simple Model of AB Image Formation 50.3.2.1 The Sample Introduces Refraction, But No USAXS 50.3.2.2 The Sample Introduces USAXS, But No Refraction 50.3.2.3 The Sample Introduces Both Refraction and USAXS 50.3.3 Phase Retrieval 50.3.3.1 The Sample Introduces Refraction, But No USAXS 50.3.3.2 The Sample Introduces USAXS, But No Refraction 50.3.3.3 The Sample Introduces Both Refraction and USAXS 50.3.3.4 Other Approaches to Phase Retrieval 50.3.4 Requirements 50.4 Edge Illumination 50.4.1 The Illumination Curve 50.4.2 Phase Retrieval and Sensitivity 50.4.3 Coherence Requirements 50.5 Computed Tomography 50.6 Applications to Biomedical Imaging 50.6.1 Breast 50.6.2 Musculoskeletal Phase-Contrast Imaging 50.6.3 Lung 50.6.4 Neuroimaging 50.6.5 Vasculature, Circulation, and Other Tissues 50.7 Conclusion References

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.

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated to be effective for visualization of the human cartilage matrix at micrometer resolution, thereby capturing osteoarthritis induced changes to chondrocyte organization. This study aims to systematically assess the efficacy of deep transfer learning methods for classifying between healthy and diseased tissue patterns. We extracted features from two different convolutional neural network architectures, CaffeNet and Inception-v3 for characterizing such patterns. These features were quantitatively evaluated in a classification task measured by the area (AUC) under the Receiver Operating Characteristic (ROC) curve as well as qualitative visualization through a dimension reduction approach t-Distributed Stochastic Neighbor Embedding (t-SNE). The best classification performance, for CaffeNet, was observed when using features from the last convolutional layer and the last fully connected layer (AUCs > 0.91 ). Meanwhile, off-the-shelf features from Inception-v3 produced similar classification performance (AUC > 0.95 ). Visualization of features from these layers further confirmed adequate characterization of chondrocyte patterns for reliably distinguishing between healthy and osteoarthritic tissue classes. Such techniques, can be potentially used for detecting the presence of osteoarthritis related changes in the human patellar cartilage.

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.

Purpose Experimental neuroimaging provides a wide range of methods for the visualization of brain anatomic morphology down to subcellular detail. Still, each technique-specific detection mechanism presents compromises among the achievable field-of-view size, spatial resolution, and nervous tissue sensitivity, leading to partial sample coverage, unresolved morphologic structures, or sparse labeling of neuronal populations and often also to obligatory sample dissection or other sample invasive manipulations. X-ray phase-contrast imaging computed tomography (PCI-CT) is an experimental imaging method that simultaneously provides micrometric spatial resolution, high soft-tissue sensitivity, and exvivo full organ rodent brain coverage without any need for sample dissection, staining or labeling, or contrast agent injection. In the present study, we explored the benefits and limitations of PCI-CT use for invitro imaging of normal and cancerous brain neuromorphology after invivo treatment with synchrotron-generated x-ray microbeam radiation therapy (MRT), a spatially fractionated experimental high-dose radiosurgery. The goals were visualization of the MRT effects on nervous tissue and a qualitative comparison of the results to the histologic and high-field magnetic resonance imaging findings. Methods and Materials MRT was administered invivo to the brain of both healthy and cancer-bearing rats. At 45days after treatment, the brain was dissected out and imaged exvivo using propagation-based PCI-CT. Results PCI-CT visualizes the brain anatomy and microvasculature in 3 dimensions and distinguishes cancerous tissue morphology, necrosis, and intratumor accumulation of iron and calcium deposits. Moreover, PCI-CT detects the effects of MRT throughout the treatment target areas (eg, the formation of micrometer-thick radiation-induced tissue ablation). The observed neurostructures were confirmed by histologic and immunohistochemistry examination and related to the micro-magnetic resonance imaging data. Conclusions PCI-CT enabled a unique 3D neuroimaging approach for exvivo studies on small animal models in that it concurrently delivers high-resolution insight of local brain tissue morphology in both normal and cancerous micro-milieu, localizes radiosurgical damage, and highlights the deep microvasculature. This method could assist experimental small animal neurology studies in the postmortem evaluation of neuropathology or treatment effects. &nbsp

The effectiveness of phase contrast X-ray computed tomography (PCI-CT) in visualizing human patellar cartilage matrix has been demonstrated due to its ability to capture soft tissue contrast on a micrometer resolution scale. Recent studies have shown that off-the-shelf Convolutional Neural Network (CNN) features learned from a non-medical data set can be used for medical image classification. In this paper, we investigate the ability of features extracted from two different CNNs for characterizing chondrocyte patterns in the cartilage matrix. We obtained features from 842 regions of interest annotated on PCI-CT images of human patellar cartilage using CaffeNet and Inception-v3 Network, which were then used in a machine learning task involving support vector machines with radial basis function kernel to classify the ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area (AUC) under the Receiver Operating Characteristic (ROC) curve. The best classification performance was observed with features from Inception-v3 network (AUC = 0.95), which outperforms features extracted from CaffeNet (AUC = 0.91). These results suggest that such characterization of chondrocyte patterns using features from internal layers of CNNs can be used to distinguish between healthy and osteoarthritic tissue with high accuracy.

Medical imaging and radiation therapy are widely used synchrotron-based techniques which have one thing in common: a significant dose delivery to typically biological samples. Among the ways to provide the experimenters with image guidance techniques indicating optimization strategies, Monte Carlo simulation has become the gold standard for accurately predicting radiation dose levels under specific irradiation conditions. A highly important hampering factor of this method is, however, its slow statistical convergence. A track length estimator (TLE) module has been coded and implemented for the first time in the open-source Monte Carlo codeGATE/Geant4. Results obtained with the module and the procedures used to validate them are presented. A database of energy-absorption coefficients was also generated, which is used by the TLE calculations and is now also included inGATE/Geant4. The validation was carried out by comparing the TLE-simulated doses with experimental data in a synchrotron radiation computed tomography experiment. The TLE technique shows good agreementversusboth experimental measurements and the results of a classical Monte Carlo simulation. Compared with the latter, it is possible to reach a pre-defined statistical uncertainty in about two to three orders of magnitude less time for complex geometries without loss of accuracy.

A collection of more than 1800 carbonized papyri, discovered in the Roman ‘Villa dei Papiri’ at Herculaneum is the unique classical library survived from antiquity. These papyri were charred during 79 A.D. Vesuvius eruption, a circumstance which providentially preserved them until now. This magnificent collection contains an impressive amount of treatises by Greek philosophers and, especially, Philodemus of Gadara, an Epicurean thinker of 1st century BC. We read many portions of text hidden inside carbonized Herculaneum papyri using enhanced X-ray phase-contrast tomography non-destructive technique and a new set of numerical algorithms for ‘virtual-unrolling’. Our success lies in revealing the largest portion of Greek text ever detected so far inside unopened scrolls, with unprecedented spatial resolution and contrast, all without damaging these precious historical manuscripts. Parts of text have been decoded and the ‘voice’ of the Epicurean philosopher Philodemus is brought back again after 2000 years from Herculaneum papyri.

Purpose Edge illumination (EI) X-ray phase-contrast imaging (XPCI) has been under development at University College London in recent years, and has shown great potential for both laboratory and synchrotron applications. In this work, we propose a new acquisition and processing scheme. Contrary to existing retrieval methods for EI, which require as input two images acquired in different setup configurations, the proposed approach can retrieve an approximate map of the X-ray phase from a single image, thus significantly simplifying the acquisition procedure and reducing data collection times. Methods The retrieval method is analytically derived, based on the assumption of a quasi-homogeneous object, i.e. an object featuring a constant ratio between refractive index and absorption coefficient. The noise properties of the input and retrieved images are also theoretically analyzed under the developed formalism. The method is applied to experimental synchrotron images of a biological object. Results The experimental results show that the method can provide high-quality images, where the “edge” signal typical of XPCI images is transformed to an “area” contrast that enables an easier interpretation of the sample geometry. Moreover, the retrieved images confirm that the method is highly stable against noise. Conclusions We anticipate that the developed approach will become the method of choice for a variety of applications of EI XPCI, thanks to its ability to simplify the acquisition procedure and reduce acquisitions time and dose to the sample. Future work will focus on the adaptation of the method to computed tomography and to polychromatic radiation from X-ray tubes.

We report results of the computed tomography reconstruction of the index of refraction in a whole rabbit knee joint examined at the photon energy of 51 keV. Refraction based images make it possible to delineate the bone, cartilage, and soft tissues without adjusting the contrast window width and level. Density variations, which are related to tissue composition and are not visible in absorption X-ray images, are detected in the obtained refraction based images. We discuss why refraction-based images provide better detectability of low contrast features than absorption images.

Mammography is the primary imaging tool for screening and diagnosis of human breast cancers, but ∼10–20% of palpable tumors are not detectable on mammograms and only about 40% of biopsied lesions are malignant. Here we report a high-resolution, low-dose phase contrast X-ray tomographic method for 3D diagnosis of human breast cancers. By combining phase contrast X-ray imaging with an image reconstruction method known as equally sloped tomography, we imaged a human breast in three dimensions and identified a malignant cancer with a pixel size of 92 μm and a radiation dose less than that of dual-view mammography. According to a blind evaluation by five independent radiologists, our method can reduce the radiation dose and acquisition time by ∼74% relative to conventional phase contrast X-ray tomography, while maintaining high image resolution and image contrast. These results demonstrate that high-resolution 3D diagnostic imaging of human breast cancers can, in principle, be performed at clinical compatible doses.

Diffraction enhanced imaging (DEI), also called analyzer-based imaging (ABI), cultivated within the synchrotron community, has the potential to revolutionize medical imaging through reduced dose and enhanced contrast imaging.

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 highlymonochromatic x-rays of 52 keV and a low noise detector with a pixel size of 47 × 47 μm2. 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 ofABI. 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. © 2010 Institute of Physics and Engineering in Medicine.

In x-ray phase-contrast analyzer-based imaging, the contrast is provided by a combination of absorption, refraction and scattering effects. Several extraction algorithms, which attempt to separate and quantify these different physical contributions, have been proposed and applied. In a previous work, we presented a quantitative comparison of five among the most well-known extraction algorithms based on the geometrical optics approximation applied to planar images: diffraction-enhanced imaging (DEI), extended diffraction-enhanced imaging (E-DEI), generalized diffraction-enhanced imaging (G-DEI), multiple-image radiography (MIR) and Gaussian curve fitting (GCF). In this paper, we compare these algorithms in the case of the computed tomography (CT) modality. The extraction algorithms are applied to analyzer-based CT images of both plastic phantoms and biological samples (cartilage-on-bone cylinders). Absorption, refraction and scattering signals are derived. Results obtained with the different algorithms may vary greatly, especially in the case of large refraction angles. We show that ABI-CT extraction algorithms can provide an excellent tool to enhance the visualization of cartilage internal structures, which may find applications in a clinical context. Besides, by using the refraction images, the refractive index decrements for both the cartilage matrix and the cartilage cells have been estimated.

X-ray computed tomography (CT) is a powerful and routinely used clinical diagnostic technique, which is well tolerated by patients, and which provides high-resolution images and volumetric information about the body. However, two important limitations still affect this examination procedure: (1) its low sensitivity with respect to soft tissues, and (2) the hazards associated with x-ray exposure. Conventional radiology is based on the detection of the different photon absorption properties that characterize biological tissues, and thus the obtainable image contrast from soft and/or similar tissues is intrinsically limited. In this scenario, x-ray phase contrast imaging (XPCI) has been extensively tested and proven to overcome some of the main issues surrounding standard x-ray imaging. In addition to the absorption signal, XPCI relies on detecting the phase shifts induced by an object. Interestingly, as the order of magnitude of the phase contrast is higher than that of absorption, XPCI can, in principle, offer higher sensitivity at lower radiation doses. However, other technical aspects may counterbalance this gain, and an optimized setup and image processing solutions need to be implemented. The work presented here describes the strategies and developments we have realized, with the aim of controlling the radiation dose for the highly sensitive and quantitative XPCI-CT. Different algorithms for the phase retrieval and CT reconstruction of the XPCI data are presented. The CT algorithms we have implemented, namely the equally sloped tomography and the dictionary learning method, allow the image quality to be preserved while reducing the number of angular projections required by a factor of five. The results applied to breast imaging report accurate reconstructions at clinically compatible doses of the 3D distribution of the refractive properties of full human organs obtained by using three different phase retrieval methods. The described methodologies and the presented results have been validated by a team of clinical radiologists and represent an important step in the exploitation of XPCI-CT for in vivo and possible clinical applications.

Monitoring the progression of osteoarthritis (OA) and the effects of therapy during clinical trials is still a challenge for present clinical imaging techniques since they present intrinsic limitations and can be sensitive only in case of advanced OA stages. In very severe cases, partial or complete joint replacement surgery is the only solution for reducing pain and restoring the joint functions. Poor imaging quality in practically all medical imaging technologies with respect to joint surfaces and to metal implant imaging calls for the development of new techniques that are sensitive to stages preceding the point of irreversible damage of the cartilage tissue. In this scenario, X-ray phase contrast modalities could play an important role since they can provide improved contrast compared to conventional absorption radiography, with a similar or even reduced tissue radiation dose. In this study, the analyzer-based imaging (ABI), a technique sensitive to the X-ray refraction and permitting a high scatter rejection, has been successfully applied in vitro on excised human synovial joints and sheep implants. Pathological and healthy joints as well as metal implants have been imaged in projection and computed tomography ABI mode at high resolution and clinically compatible doses (

The first practical application of X-rays, more than 100 years ago, was for biomedical imaging. Although not central to the initial development of 3 rd generation synchrotron light sources, imaging techniques have today established themselves as a core element of the research program at all major light sources, including the ESRF, where X-ray imaging has been identified as one of five main themes for its Upgrade Programme [1].

Medical application of synchrotron radiation (SR) is a fast-growing field of research. Since the advent of the angiography studies at SSRL first and then at NSLS in the U.S. in the 1990s, preclinical and clinical research protocols have been developed at Hasylab (Germany), Photon Factory (Japan), ELETTRA (Italia) and at the ESRF (France). Despite the fact that there are only a few dedicated beamlines in the world (two new ones are under construction at the Australian and Canadian synchrotrons), medical research is carried out in almost all synchrotron facilities.

X-ray radiography plays an important role in the study of artworks and archaeological artifacts. The internal structure of objects provides information on genesis, authenticity, painting technique, material condition and conservation history. Transmission radiography, however, does not provide information on the exact elemental composition of objects and heavy metal layers can shadow or obscure the ones including lighter elements. This paper presents the first application of synchrotron-based K-edge absorption imaging applied to paintings. Using highly monochromatic radiation, K-edge imaging is used to obtain elemental distribution images over large areas. Such elemental maps visualize the distribution of an individual pigment throughout the paint stratigraphy. This provides color information on hidden paint layers, which is of great relevance to art historians and painting conservators. The main advantage is the quick data acquisition time and the sensitivity to elements throughout the entire paint stratigraphy. The examination of a test painting is shown and further instrumental developments are discussed.

Two x-ray phase contrast imaging techniques are compared in a quantitative way for future mammographic applications: diffraction enhanced imaging (DEI) and phase propagation imaging (PPI). DEI involves, downstream of the sample, an analyser crystal acting as an angular filter for x-rays refracted by the sample. PPI simply uses the propagation (Fresnel diffraction) of the monochromatic and partially coherent x-ray beam over large distances. The information given by the two techniques is assessed by theoretical simulations and compared at the level of the experimental results for different kinds of samples (phantoms and real tissues). The imaging parameters such as the energy, the angular position of the analyser crystal in the DEI case or the sample to detector distance in the PPI case were varied in order to optimize the image quality in terms of contrast, visibility and figure of merit.

Recent developments have shown that high resolution phase contrast x-ray computed tomography (CT) of the breast can be performed at clinically compatible doses. Results have yet been obtained in vitro on full breasts, and the clinical translation of the technique seems more and more possible. This work presents a method to quickly estimate the average dose in the organ using the software GATE. The influence of different parameters on the dose distribution, like breast composition and thickness, and for preclinical test, the presence of a skin/PMMA external layer, has been investigated. Several correction factors, to be applied to the given dose database, are also introduced to allow the use of these results in geometries different from those studied here. An energy optimization study is presented that considers also the influence on the energy choice of x-ray detector. A simple analytical method to estimate the best energy that minimizes the dose-transmittance ratio in CT imaging is presented and compared with the results of simulations.

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

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.

In this paper, the excellence cluster “Munich-Centre for Advance Photonics” (MAP) is presented. One of the aims of the project is the development of innovative X-ray-based diagnostics imaging techniques to be implemented at an ultra-compact high-energy and high-brilliance X-ray source. The basis of the project and the developments towards the clinical application of phase contrast imaging applied to mammography and cartilage studies will be presented and discussed.

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.

Phase-contrast x-ray imaging (PCI) is an innovative method that is sensitive to the refraction of the x-rays in matter. PCI is particularly adapted to visualize weakly absorbing details like those often encountered in biology and medicine. In past years, PCI has become one of the most used imaging methods in laboratory and preclinical studies: its unique characteristics allow high contrast 3D visualization of thick and complex samples even at high spatial resolution. Applications have covered a wide range of pathologies and organs, and are more and more often performed in vivo. Several techniques are now available to exploit and visualize the phase-contrast: propagation- and analyzer-based, crystal and grating interferometry and non-interferometric methods like the coded aperture. In this review, covering the last five years, we will givean overview of the main theoretical and experimental developments and of the important steps performed towards the clinical implementation of PCI. © 2013 Institute of Physics and Engineering in Medicine.

Analyzer-based imaging is a powerful phase-sensitive technique that generates improved contrast compared to standard absorption radiography. Combining numerically two images taken on either side at +/-1/2 of the full width at half-maximum (FWHM) of the rocking curve provides images of "pure refraction" and of "apparent absorption." In this study, a similar approach is made by combining symmetrical images with respect to the peak of the analyzer rocking curve but at general positions, +/-alpha.FWHM. These two approaches do not consider the ultrasmall angle scattering produced by the object independently, which can lead to inconsistent results. An accurate way to separately retrieve the quantitative information intrinsic to the object is proposed. It is based on a statistical analysis of the local rocking curve, and allows one to overcome the problems encountered using the previous approaches. (C) 2003 American Institute of Physics.

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 CT imaging (PCI-CT) was shown to allow direct examination of chondrocyte cell 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 both gray-level co-occurrence matrix (GLCM) derived texture features as well as Minkowski Functionals (MF). Thirteen GLCM and three MF texture features 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 ROC curve (AUC). The best classification performance was observed with the MF features 'perimeter' and 'Euler characteristic' and with GLCM correlation features (f3 and f13). With the experimental conditions used in this study, both Minkowski Functionals and GLCM achieved a high classification performance (AUC value of 0.97) in the task of distinguishing between health 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.

At Munich centre for Advance Photonics, one of the main aims of the project is the development and application of phase contrast imaging techniques for medical diagnostics to be performed with a new compact high brilliant and energetic X-ray source. High resolution phase contrast tomography of breast and cartilage tissues with characteristics of clinical interest have been performed producing outstanding results. Accurate visualization of fine structures and tissue degeneration in the imaged samples was obtained representing a real step forward in the direction of clinical applications of the high sensitive phase contrast X-ray imaging. © 2009 Springer-Verlag.

X-ray radiography is a common tool in the study of old master paintings. Transmission imaging can visualize hidden paint layers as well as the structure of the panel or canvas. In some medieval altarpieces, relics seem to have been imbedded in the wooden carrier of paintings. These are most probably thin organic fibrous materials such as paper or textile, which in traditional radiography are shadowed by the more absorbing surrounding material. This paper studies the application potential of synchrotron-based tomographic and laminographic imaging complemented with phase-contrast imaging for detection of such relics. The techniques are applied to a dummy painting. The results demonstrate that by using these imaging methods it is possible to three-dimensionally visualize hidden cavities in panels and detect thin fibrous low-Z materials sandwiched between a high-Z paint layer and a thick wooden panel.

Using rigorous wave-optical formalism, a general expression is obtained for the image intensity distribution in combined analyser-based/propagation-based phase-contrast imaging. This expression takes into account partial coherence of the wave incident on the object as well as the finite resolution of the detector system. Using this general expression, two approaches based on the geometrical optics and weak-object approximations are applied to derive simple solutions to the inverse problem of reconstruction of the phase and amplitude of the object wave. With the help of numerical experiments, the two approaches are compared in terms of their validity conditions and are shown to impose certain restrictions on the properties of the object wave. In particular, it is shown that violation of the validity conditions of the geometrical optics or weak-object approximations results in the appearance of strong reconstruction artefacts in the transmitted intensity near the edges of the objects. The effect of the incident wavefront non-uniformity due to imperfections of the imaging set-up on image formation and phase/amplitude reconstruction is also discussed. A solution to this problem is proposed in the form of a multi-image phase/amplitude reconstruction algorithm based on the geometrical optics approximation. This algorithm and an algorithm based on the weak-object approximation are applied to simulated and experimental images of fibres.

The purpose of this work was to assess the imaging performance of an indirect conversion detector (taper optics CCD; FReLoN' camera) in terms of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE). Measurements were made with a synchrotron radiation laminar beam at various monochromatic energies in the 20-51.5 keV range for a gadolinium-based fluorescent screen varying in thickness; data acquisition and analysis were made by adapting to this beam geometry protocols used for conventional cone beams. The pre-sampled MTFs of the systems were measured using an edge method. The NNPS of the systems were determined for a range of exposure levels by two-dimensional Fourier analysis of uniformly exposed radiographs. The DQEs were assessed from the measured MTF, NNPS, exposure and incoming number of photons. The MTF, for a given screen, was found to be almost energy independent and, for a given energy, higher for the thinnest screen. At 33 keV and for the 40 (100) microm screen, at 10% the MTF is 9.2 (8.6) line-pairs mm(-1). The NNPS was found to be different in the two analyzed directions in relation to frequency. Highest DQE values were found for the combination 100 microm and 25 keV (0.5); it was still equal to 0.4 at 51.5 keV (above the gadolinium K-edge). The DQE is limited by the phosphor screen conversion yield and by the CCD efficiency. At the end of the manuscript the results of the FReLoN characterization and those from a selected number of detectors presented in the literature are compared.

Description of purpose: Treatment of osteoarthritis in stages of reversible disease requires high resolution visualization of early cartilage damage and of subchondral bone. Here, DEI (Diffraction Enhanced Imaging) is compared to MRI, computed X-ray tomography (CT) and ultrasound (UI) in its ability to detect early degeneration of articular cartilage. In contrast to conventional absorptive X-ray examination where cartilage is poorly visible DEI captures cartilage by detection of selected refraction. Methods: Human femoral heads were investigated by macroscopic inspection, conventional X-ray examination, DEI, MRI, CT, UI and histology. DEI is an imaging technique applying a monochromatic parallel synchrotron X-ray beam. Image features were verified by histology. Results: DEI, MRI and ultrasound lead to interpretable images of cartilage. Of all techniques, DEI provided highest image resolution revealing the structural tissue architecture. MRI needs a very long exposure time (more than 5 hours) to achieve comparable quality. Application of ultrasound is limited because of joint geometry and, at high sound frequency, the necessity of close contact between cartilage and transducer. DEI is an experimental technique which needs synchrotron radiation. Conclusion: DEI is a very promising imaging technique for visualization of cartilage and bone. It may serve as an excellent analytical tool for experimental studies. Our pictures show a part of future of optimised techniques for imaging. Synchrotron based DEI may lead the way towards optimisation of improved techniques for imaging. Upon development of adequate small scale X-ray sources, DEI will also be an important supplementation for medical imaging.

Purpose: Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. Methods: The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer based phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure’s possible applications. Results: A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. Conclusions: The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.

Several x-ray phase contrast extraction algorithms use a set of images acquired along the rocking curve of a perfect flat analyzer crystal to study the internal structure of objects. By measuring the angular shift of the rocking curve peak, one can determine the local deflections of the x-ray beam propagated through a sample. Additionally, some objects determine a broadening of the crystal rocking curve, which can be explained in terms of multiple refraction of x rays by many subpixel-size inhomogeneities contained in the sample. This fact may allow us to differentiate between materials and features characterized by different refraction properties. In the present work we derive an expression for the beam broadening in the form of a linear integral of the quantity related to statistical properties of the dielectric susceptibility distribution function of the object.

Purpose: In mammography, while maintaining the image quality, it is necessary to keep the delivered dose as low as possible since breast is a highly radiosensitive organ. Monochromatic phase contrast X‐ray mammography has shown its potential at higher sensitivity and lower impact in terms of dose delivery compared to absorption based diagnostic X‐ray mammography. An exact Fourier‐based iterative technique termed Equally Sloped Tomography(EST) has been newly developed and implemented on it. Using this technique, we conducted a series of comparative experiments to explore the further more radiation dose reduction in phase contrastmammography through reduction of projection numbers. Methods: Experiment took place at the biomedical beamline at ESRF(ID17). Full Human breasts samples were fixed in 4% formalin solution. Planar imaging and Computed Tomography(CT) modalities were combined to PCI techniques at 60KeV and using a 2kx2k taper optics CCD detector(45 micron pixel). The number of projections scanned was 2000 and digitally removed to 512 for reconstructions. Comparison reconstructions were produced by Filtered‐Back Projection(FBP) with a standard uncropped‐ramp filter. To optimize the result, Non‐local‐means regularization was applied for post‐processing in both cases. Results: Compared to the FBP reconstruction using 2000 projections, EST using 512 projections has comparable SNRs and CNRs, no obvious contrast degradation is observed between tumor and normal glandular tissue. In addition, the collagen exhibit similar visibility. Conclusions: Our results indicate that in the phase contrastmammography, EST technique can reduce the dose up to 50%∼75% by reducing number of projections, while images have comparable quality as the full dose FBP reconstruction. Furthermore, it makes the acquisition time 2∼4 times faster, which is important in in‐vivo imaging. The main reason for this is that EST is an exact Fourier‐based iterative algorithm that can incorporate different physical and mathematical constraints. It is always guided towards a lowest‐possible noisy state while keeping strictly consistent with measurements. Research sponsored by UC Discovery / TomoSoft Technologies Grant #ITL07‐10166.

Many mathematical methods have been so far proposed in order to separate absorption, refraction and ultra-small angle scattering information in phase-contrast analyzer-based images. These algorithms all combine a given number of images acquired at different positions of the crystal analyzer along its rocking curve. In this paper a comprehensive quantitative comparison between five of the most widely used phase extraction algorithms based on the geometrical optics approximation is presented: the diffraction-enhanced imaging (DEI), the extended diffraction-enhanced imaging (E-DEI), the generalized diffraction-enhanced (G-DEI), the multiple-image radiography (MIR) and the Gaussian curve fitting (GCF). The algorithms are theoretically analyzed in terms of their validity conditions and experimentally compared by using geometrical phantoms providing various amounts of absorption, refraction and scattering. The presented work shows that, due to their specific validity conditions, the considered algorithms produce results that may greatly differ, especially in the case of highly refracting and/or highly scattering materials. The various extraction algorithms are also applied to images of a human bone-cartilage sample. The aim is to validate the results obtained on geometrical phantoms and prove the efficiency of the different algorithms for applications on biological samples.

A nontomography approach for the measurement of angular-dependent coherent-scatter cross section of x rays (E≃40-80 keV) is described. It is shown that an analyzer crystal, which is proposed to be used for the sampling of the cross section, simultaneously provides information about the location of the scattering volume inside the object. A numerical simulation demonstrates that this method can be applied for nondestructive analysis of an object's internal structure.