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Imaging intact human organs from the organ to the cellular scale in three dimensions is a goal of biomedical imaging. To meet this challenge, we developed hierarchical phase-contrast tomography (HiP-CT), an X-ray phase propagation technique using the European Synchrotron Radiation Facility (ESRF)’s Extremely Brilliant Source (EBS). The spatial coherence of the ESRF-EBS combined with our beamline equipment, sample preparation and scanning developments enabled us to perform non-destructive, three-dimensional (3D) scans with hierarchically increasing resolution at any location in whole human organs. We applied HiP-CT to image five intact human organ types: brain, lung, heart, kidney and spleen. HiP-CT provided a structural overview of each whole organ followed by multiple higher-resolution volumes of interest, capturing organotypic functional units and certain individual specialized cells within intact human organs. We demonstrate the potential applications of HiP-CT through quantification and morphometry of glomeruli in an intact human kidney and identification of regional changes in the tissue architecture in a lung from a deceased donor with coronavirus disease 2019 (COVID-19).Hierarchical phase-contrast tomography (HiP-CT) enables multiscale imaging of any region within an intact human organ down to cellular resolution. HiP-CT of five organ types revealed 3D morphological features in healthy and diseased tissue.

Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844 bounding boxes. On the basis of this dataset, a deep-learning-based framework was developed to identify and localize 14 common abnormalities and calculate the cardiothoracic ratio (CTR) simultaneously. The mean average precision values obtained by the model for 14 abnormalities reached 0.572-0.631 with an intersection-over-union threshold of 0.5, and the intraclass correlation coefficient of the CTR algorithm exceeded 0.95 on the held-out, multicentre and prospective test datasets. This framework shows an excellent performance, good generalization ability and strong clinical applicability, which is superior to senior radiologists and suitable for routine clinical settings. Accurate localization of abnormalities is crucial in the interpretation of chest X-rays. Here the authors present a deep learning framework for simultaneous localization of 14 thoracic abnormalities and calculation of cardiothoracic ratio, based on large X-ray dataset with bounding boxes created via a human-in-the-loop approach.

To advance microfluidic integration, we present the use of two-photon additive manufacturing to fold 2D channel layouts into compact free-form 3D fluidic circuits with nanometer precision. We demonstrate this technique by tailoring microfluidic nozzles and mixers for time-resolved structural biology at X-ray free-electron lasers (XFELs). We achieve submicron jets with speeds exceeding 160 m s −1 , which allows for the use of megahertz XFEL repetition rates. By integrating an additional orifice, we implement a low consumption flow-focusing nozzle, which is validated by solving a hemoglobin structure. Also, aberration-free in operando X-ray microtomography is introduced to study efficient equivolumetric millisecond mixing in channels with 3D features integrated into the nozzle. Such devices can be printed in minutes by locally adjusting print resolution during fabrication. This technology has the potential to permit ultracompact devices and performance improvements through 3D flow optimization in all fields of microfluidic engineering. There is a need for more robust sample delivery methods for serial crystallography. Here the authors present the design and characterization of ultracompact 3D microfluidic devices that can be printed, which require less sample, have a lower background signal and allow 3D mixing for time resolved experiments.

A small-angle X-ray scattering computed tomography method that reduces the amount of data that needs to be collected and analysed to reconstruct the three-dimensional scattering distribution in reciprocal space of a three-dimensional sample in real space is demonstrated by measuring the orientation of collagen fibres within a human tooth. SAXS-CT techniques probe hard tissues Small-angle X-ray scattering (SAXS) can, in principle, probe structural ordering across a wide range of length scales, from nanoscale to the macroscopic. However, an experimental method and analysis scheme to obtain three-dimensional images while preserving nanostructure orientation information remained out of reach. Two papers in this issue of Nature combine different tomographic principles with SAXS to yield this information. Marianne Liebi et al . introduce a generally applicable model that can describe the SAXS data and show how taking account of the symmetries intrinsic to many samples of interest — such as the preferred orientation of collagen fibrils in the human trabecular bone that they have studied — can make the process more manageable. The procedure demonstrated by Florian Schaff et al . introduces the concept of virtual tomography axes, which allows arrangement of the vast amount of data to enable a direct independent reconstruction of each reciprocal space component. For their example, they show the orientation and scattering strength of mineralized collagen in a human tooth, spatially resolved over several millimetres. When used in combination with raster scanning, small-angle X-ray scattering (SAXS) has proven to be a valuable imaging technique of the nanoscale 1 , for example of bone, teeth and brain matter 2 , 3 , 4 , 5 . Although two-dimensional projection imaging has been used to characterize various materials successfully, its three-dimensional extension, SAXS computed tomography, poses substantial challenges, which have yet to be overcome. Previous work 6 , 7 , 8 , 9 , 10 , 11 using SAXS computed tomography was unable to preserve oriented SAXS signals during reconstruction. Here we present a solution to this problem and obtain a complete SAXS computed tomography, which preserves oriented scattering information. By introducing virtual tomography axes, we take advantage of the two-dimensional SAXS information recorded on an area detector and use it to reconstruct the full three-dimensional scattering distribution in reciprocal space for each voxel of the three-dimensional object in real space. The presented method could be of interest for a combined six-dimensional real and reciprocal space characterization of mesoscopic materials with hierarchically structured features with length scales ranging from a few nanometres to a few millimetres—for example, biomaterials such as bone or teeth, or functional materials such as fuel-cell or battery components.

Biological tissues comprise a spatially complex structure, composition and organization at the microscale, named the microstructure. Given the close structure-function relationships in tissues, structural characterization is essential to fully understand the functioning of healthy and pathological tissues, as well as the impact of possible treatments. Here, we present a nondestructive imaging approach to perform quantitative 3D histo(patho)logy of biological tissues, termed Cryogenic Contrast-Enhanced MicroCT (cryo-CECT). By combining sample staining, using an X-ray contrast-enhancing staining agent, with freezing the sample at the optimal freezing rate, cryo-CECT enables 3D visualization and structural analysis of individual tissue constituents, such as muscle and collagen fibers. We applied cryo-CECT on murine hearts subjected to pressure overload following transverse aortic constriction surgery. Cryo-CECT allowed to analyze, in an unprecedented manner, the orientation and diameter of the individual muscle fibers in the entire heart, as well as the 3D localization of fibrotic regions within the myocardial layers. We foresee further applications of cryo-CECT in the optimization of tissue/food preservation and donor banking, showing that cryo-CECT also has clinical and industrial potential. The authors present cryogenic contrast-enhanced MicroCT (cryo-CECT), which by freezing stained samples at optimal freezing rates improves the visualization of the tissue microstructure. They demonstrate quantitative 3D analysis of individual tissue constituents, such as muscle and collagen fibers.

Automatic vertebrae localization and segmentation in computed tomography (CT) are fundamental for spinal image analysis and spine surgery with computer-assisted surgery systems. But they remain challenging due to high variation in spinal anatomy among patients. In this paper, we proposed a deep-learning approach for automatic CT vertebrae localization and segmentation with a two-stage Dense-U-Net. The first stage used a 2D-Dense-U-Net to localize vertebrae by detecting the vertebrae centroids with dense labels and 2D slices. The second stage segmented the specific vertebra within a region-of-interest identified based on the centroid using 3D-Dense-U-Net. Finally, each segmented vertebra was merged into a complete spine and resampled to original resolution. We evaluated our method on the dataset from the CSI 2014 Workshop with 6 metrics: location error (1.69 ± 0.78 mm), detection rate (100%) for vertebrae localization; the dice coefficient (0.953 ± 0.014), intersection over union (0.911 ± 0.025), Hausdorff distance (4.013 ± 2.128 mm), pixel accuracy (0.998 ± 0.001) for vertebrae segmentation. The experimental results demonstrated the efficiency of the proposed method. Furthermore, evaluation on the dataset from the xVertSeg challenge with location error (4.12 ± 2.31), detection rate (100%), dice coefficient (0.877 ± 0.035) shows the generalizability of our method. In summary, our solution localized the vertebrae successfully by detecting the centroids of vertebrae and implemented instance segmentation of vertebrae in the whole spine.

The performance of an X-ray grating interferometry system depends on the geometry and quality of the gratings. Fabrication of micrometer-pitch high-aspect-ratio gold gratings, which are essential for measuring small refraction angles at higher energies, is challenging. The two widely used technologies for manufacturing gratings are based on gold electroplating in polymeric or silicon templates. Here, gratings manufactured by both approaches were inspected using conventional microscopy, X-ray synchrotron radiography, and computed laminography to extract characteristic features of the gratings profile to be modeled accurately. These models were used in a wave-propagation simulation to predict the effects of the gratings’ geometry and defects on the quality of a Talbot-Lau interferometer in terms of visibility and absorption capabilities. The simulated outcomes of grating features produced with both techniques could eventually be observed and evaluated in a table-top Talbot-Lau-Interferometer.

The formation of new blood vessels and the establishment of vascular networks are crucial during brain development, in the adult healthy brain, as well as in various diseases of the central nervous system. Here, we describe a step-by-step protocol for our recently developed method that enables hierarchical imaging and computational analysis of vascular networks in postnatal and adult mouse brains. The different stages of the procedure include resin-based vascular corrosion casting, scanning electron microscopy, synchrotron radiation and desktop microcomputed tomography imaging, and computational network analysis. Combining these methods enables detailed visualization and quantification of the 3D brain vasculature. Network features such as vascular volume fraction, branch point density, vessel diameter, length, tortuosity and directionality as well as extravascular distance can be obtained at any developmental stage from the early postnatal to the adult brain. This approach can be used to provide a detailed morphological atlas of the entire mouse brain vasculature at both the postnatal and the adult stage of development. Our protocol allows the characterization of brain vascular networks separately for capillaries and noncapillaries. The entire protocol, from mouse perfusion to vessel network analysis, takes ~10 d. This protocol uses vascular corrosion casting, hierarchical synchrotron radiation microcomputed tomography imaging and computational image analysis to assess the 3D vascular network architecture in the entire postnatal and adult mouse brain.

X-ray fluorescence computed tomography (XFCT) is a technique that can identify, quantify and locate elements within objects by detecting x-ray fluorescence (characteristic x-rays) stimulated by an excitation source, typically derived from a synchrotron. However, the use of a synchrotron limits practicality and accessibility of XFCT for routine biomedical imaging applications. Therefore, we have developed the ability to perform XFCT on a benchtop setting with ordinary polychromatic x-ray sources. Here, we report our postmortem study that demonstrates the use of benchtop XFCT to accurately image the distribution of gold nanoparticles (GNPs) injected into a tumor-bearing mouse. The distribution of GNPs as determined by benchtop XFCT was validated using inductively coupled plasma mass spectrometry. This investigation shows drastically enhanced sensitivity and specificity of GNP detection and quantification with benchtop XFCT, up to two orders of magnitude better than conventional x-ray CT. The results also reaffirm the unique capabilities of benchtop XFCT for simultaneous determination of the spatial distribution and concentration of nonradioactive metallic probes, such as GNPs, within the context of small animal imaging. Overall, this investigation identifies a clear path toward in vivo molecular imaging using benchtop XFCT techniques in conjunction with GNPs and other metallic probes.