Three-dimensional virtual histology enabled through cytoplasm-specific X-ray stain for microscopic and nanoscopic computed tomography.

Many histological methods require staining of the cytoplasm, which provides instrumental details for diagnosis. One major limitation is the production of 2D images obtained by destructive preparation of 3D tissue samples. X-ray absorption micro- and nanocomputed tomography (microCT and nanoCT) allows for a nondestructive investigation of a 3D tissue sample, and thus aids to determine regions of interest for further histological examinations. However, application of microCT and nanoCT to biological samples (e.g., biopsies) is limited by the missing contrast within soft tissue, which is important to visualize morphological details. We describe an eosin-based preparation overcoming the challenges of contrast enhancement and selectivity for certain tissues. The eosin-based staining protocol is suitable for whole-organ staining, which then enables high-resolution microCT imaging of whole organs and nanoCT imaging of smaller tissue pieces retrieved from the original sample. Our results demonstrate suitability of the eosin-based staining method for diagnostic screening of 3D tissue samples without impeding further diagnostics through histological methods.

Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography.

X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli, a representative of Onychophora-an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.

X-ray nanotomography using near-field ptychography.

Propagation-based imaging or inline holography in combination with computed tomography (holotomography) is a versatile tool to access a sample's three-dimensional (3D) micro or nano structure. However, the phase retrieval step needed prior to tomographic reconstruction can be challenging especially for strongly absorbing and refracting samples. Near-field ptychography is a recently developed phase imaging method that has been proven to overcome this hurdle in projection data. In this work we extend near-field ptychography to three dimensions and we show that, in combination with tomography, it can access the nano structure of a solid oxide fuel cell (SOFC). The quality of the resulting tomographic data and the structural properties of the anode extracted from this volume were compared to previous results obtained with holotomography. This work highlights the potential of 3D near-field ptychography for reliable and detailed investigations of samples at the nanometer scale, with important applications in materials and life sciences among others.

Regularized iterative integration combined with non-linear diffusion filtering for phase-contrast x-ray computed tomography.

Phase-contrast x-ray computed tomography has a high potential to become clinically implemented because of its complementarity to conventional absorption-contrast.In this study, we investigate noise-reducing but resolution-preserving analytical reconstruction methods to improve differential phase-contrast imaging. We apply the non-linear Perona-Malik filter on phase-contrast data prior or post filtered backprojected reconstruction. Secondly, the Hilbert kernel is replaced by regularized iterative integration followed by ramp filtered backprojection as used for absorption-contrast imaging. Combining the Perona-Malik filter with this integration algorithm allows to successfully reveal relevant sample features, quantitatively confirmed by significantly increased structural similarity indices and contrast-to-noise ratios. With this concept, phase-contrast imaging can be performed at considerably lower dose.

Quantifying wood decomposition by insects and fungi using computed tomography scanning and machine learning.

Wood decomposition is a central process contributing to global carbon and nutrient cycling. Quantifying the role of the major biotic agents of wood decomposition, i.e. insects and fungi, is thus important for a better understanding of this process. Methods to quantify wood decomposition, such as dry mass loss, suffer from several shortcomings, such as destructive sampling or subsampling. We developed and tested a new approach based on computed tomography (CT) scanning and semi-automatic image analysis of logs from a field experiment with manipulated beetle communities. We quantified the volume of beetle tunnels in wood and bark and the relative wood volume showing signs of fungal decay and compared both measures to classic approaches. The volume of beetle tunnels was correlated with dry mass loss and clearly reflected the differences between beetle functional groups. Fungal decay was identified with high accuracy and strongly correlated with ergosterol content. Our data show that this is a powerful approach to quantify wood decomposition by insects and fungi. In contrast to other methods, it is non-destructive, covers entire deadwood objects and provides spatially explicit information opening a wide range of research options. For the development of general models, we urge researchers to publish training data.

Nanoscopic X-ray tomography for correlative microscopy of a small meiofaunal sea-cucumber.

In the field of correlative microscopy, light and electron microscopy form a powerful combination for morphological analyses in zoology. Due to sample thickness limitations, these imaging techniques often require sectioning to investigate small animals and thereby suffer from various artefacts. A recently introduced nanoscopic X-ray computed tomography (NanoCT) setup has been used to image several biological objects, none that were, however, embedded into resin, which is prerequisite for a multitude of correlative applications. In this study, we assess the value of this NanoCT for correlative microscopy. For this purpose, we imaged a resin-embedded, meiofaunal sea cucumber with an approximate length of 1 mm, where microCT would yield only little information about the internal anatomy. The resulting NanoCT data exhibits isotropic 3D resolution, offers deeper insights into the 3D microstructure, and thereby allows for a complete morphological characterization. For comparative purposes, the specimen was sectioned subsequently to evaluate the NanoCT data versus serial sectioning light microscopy (ss-LM). To correct for mechanical instabilities and drift artefacts, we applied an alternative alignment procedure for CT reconstruction. We thereby achieve a level of detail on the subcellular scale comparable to ss-LM images in the sectioning plane.

Metric-guided regularisation parameter selection for statistical iterative reconstruction in computed tomography.

As iterative reconstruction in Computed Tomography (CT) is an ill-posed problem, additional prior information has to be used to get a physically meaningful result (close to ground truth if available). However, the amount of influence of the regularisation prior is crucial to the outcome of the reconstruction. Therefore, we propose a scheme for tuning the strength of the prior via a certain image metric. In this work, the parameter is tuned for minimal histogram entropy in selected regions of the reconstruction as histogram entropy is a very basic approach to characterise the information content of data. We performed a sweep over different regularisation parameters showing that the histogram entropy is a suitable metric as it is well behaved over a wide range of parameters. The parameter determination is a feedback loop approach we applied to numerically simulated FORBILD phantom data and verified with an experimental measurement of a micro-CT device. The outcome is evaluated visually and quantitatively by means of root mean squared error (RMSE) and structural similarity (SSIM) for the simulation and visually for the measured sample (no ground truth available). The final reconstructed images exhibit noise-suppressed iterative reconstruction. For both datasets, the optimisation is robust where its initial value is concerned. The parameter tuning approach shows that the proposed metric-driven feedback loop is a promising tool for finding a suitable regularisation parameter in statistical iterative reconstruction.

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography.

We demonstrate a laboratory-based method combining X-ray microCT and nanoCT with a specific X-ray stain, which targets the cell cytoplasm. The described protocol is easy to apply, fast and suitable for larger soft-tissue samples. The presented methodology enables the characterization of crucial tissue structures in three dimensions and is demonstrated on a whole mouse kidney. The multiscale approach allows to image the entire mouse kidney and supports the selection of further volumes of interest, which are acquired with higher resolutions ranging into the nanometer range. Thereby, soft-tissue morphology with a similar detail level as the corresponding histological light microscopy images is reproduced. Deeper insights into the 3D configuration of tissue structures are achieved without impeding further investigations through histological methods.

Author Correction: Nucleus-specific X-ray stain for 3D virtual histology.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

X-ray imaging of a water bear offers a new look at tardigrade internal anatomy.

BACKGROUND: Tardigrades (water bears) are microscopic invertebrates of which the anatomy has been well studied using traditional techniques, but a comprehensive three-dimensional reconstruction has never been performed. In order to close this gap, we employed X-ray computed tomography (CT), a technique that is becoming increasingly popular in zoology for producing high-resolution, three-dimensional (3D) scans of whole specimens. While CT has long been used to scan larger samples, its use in some microscopic animals can be problematic, as they are often too small for conventional CT yet too large for high-resolution, optics-based soft X-ray microscopy. This size gap continues to be narrowed with advancements in technology, with high-resolution imaging now being possible using both large synchrotron devices and, more recently, laboratory-based instruments. RESULTS: Here we use a recently developed prototype lab-based nano-computed tomography device to image a 152 µm-long tardigrade at high resolution (200-270 nm pixel size). The resulting dataset allowed us to visualize the anatomy of the tardigrade in 3D and analyze the spatial relationships of the internal structures. Segmentation of the major structures of the body enabled the direct measurement of their respective volumes. Furthermore, we segmented every storage cell individually and quantified their volume distribution. We compare our measurements to those from published studies in which other techniques were used. CONCLUSIONS: The data presented herein demonstrate the utility of CT imaging as a powerful supplementary tool for studies of tardigrade anatomy, especially for quantitative volume measurements. This nanoCT study represents the smallest complete animal ever imaged using CT, and offers new 3D insights into the spatial relationships of the internal organs of water bears.

Publisher Correction: Direct quantitative material decomposition employing grating-based X-ray phase-contrast CT.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Nucleus-specific X-ray stain for 3D virtual histology.

Histological investigations are indispensable with regards to the identification of structural tissue details but are limited to two-dimensional images, which are often visualized in one and the same plane for comparison reasons. Nondestructive three-dimensional technologies such as X-ray micro- and nanoCT have proven to provide valuable benefits for the understanding of anatomical structures as they allow visualization of structural details in 3D and from arbitrary viewing angles. Nevertheless, low attenuation of soft tissue has hampered their application in the field of 3D virtual histology. We present a hematein-based X-ray staining method that specifically targets the cell nuclei of cells, as demonstrated for a whole liver lobule of a mouse. Combining the novel staining protocol with the high resolving power of a recently developed nanoCT system enables the 3D visualization of tissue architecture in the nanometer range, thereby revealing the real 3D morphology and spatial distribution of the cell nuclei. Furthermore, our technique is compatible with conventional histology, as microscopic slides can be derived from the very same stained soft-tissue sample and further counter staining is possible. Thus, our methodology demonstrates future applicability for modern histopathology using laboratory X-ray CT devices.

Direct quantitative material decomposition employing grating-based X-ray phase-contrast CT.

Dual-energy CT has opened up a new level of quantitative X-ray imaging for many diagnostic applications. The energy dependence of the X-ray attenuation is the key to quantitative material decomposition of the volume under investigation. This material decomposition allows the calculation of virtual native images in contrast enhanced angiography, virtual monoenergetic images for beam-hardening artifact reduction and quantitative material maps, among others. These visualizations have been proven beneficial for various diagnostic questions. Here, we demonstrate a new method of 'virtual dual-energy CT' employing grating-based phase-contrast for quantitative material decomposition. Analogue to the measurement at two different energies, the applied phase-contrast measurement approach yields dual information in form of a phase-shift and an attenuation image. Based on these two image channels, all known dual-energy applications can be demonstrated with our technique. While still in a preclinical state, the method features the important advantages of direct access to the electron density via the phase image, simultaneous availability of the conventional attenuation image at the full energy spectrum and therefore inherently registered image channels. The transfer of this signal extraction approach to phase-contrast data multiplies the diagnostic information gained within a single CT acquisition. The method is demonstrated with a phantom consisting of exemplary solid and fluid materials as well as a chicken heart with an iodine filled tube simulating a vessel. For this first demonstration all measurements have been conducted at a compact laser-undulator synchrotron X-ray source with a tunable X-ray energy and a narrow spectral bandwidth, to validate the quantitativeness of the processing approach.

Propagation-based phase-contrast tomography of a guinea pig inner ear with cochlear implant using a model-based iterative reconstruction algorithm.

Propagation-based phase-contrast computed tomography has become a valuable tool for visualization of three-dimensional biological samples, due to its high contrast between materials with similar attenuation properties. However, one of the most-widely used phase-retrieval algorithms imposes a homogeneity assumption onto the sample, which leads to artifacts for numerous applications where this assumption is violated. Prominent examples are biological samples with highly-absorbing implants. Using synchrotron radiation, we demonstrate by the example of a guinea pig inner ear with a cochlear implant electrode, how a recently developed model-based iterative algorithm for propagation-based phase-contrast computed tomography yields distinct benefits for such a task. We find that the model-based approach improves the overall image quality, removes the detrimental influence of the implant and accurately visualizes the cochlea.

Tilted grating phase-contrast computed tomography using statistical iterative reconstruction.

Grating-based phase-contrast computed tomography (GBPC-CT) enables increased soft tissue differentiation, but often suffers from streak artifacts when performing high-sensitivity GBPC-CT of biomedical samples. Current GBPC-CT setups consist of one-dimensional gratings and hence allow to measure only the differential phase-contrast (DPC) signal perpendicular to the direction of the grating lines. Having access to the full two-dimensional DPC signal can strongly reduce streak artefacts showing up as characteristic horizontal lines in the reconstructed images. GBPC-CT with gratings tilted by 45° around the optical axis, combining opposed projections, and reconstructing with filtered backprojection is one method to retrieve the full three-dimensional DPC signal. This approach improves the quality of the tomographic data as already demonstrated at a synchrotron facility. However, additional processing and interpolation is necessary, and the approach fails when dealing with cone-beam geometry setups. In this work, we employ the tilted grating configuration with a laboratory GBPC-CT setup with cone-beam geometry and use statistical iterative reconstruction (SIR) with a forward model accounting for diagonal grating alignment. Our results show a strong reduction of streak artefacts and significant increase in image quality. In contrast to the prior approach our proposed method can be used in a laboratory environment due to its cone-beam compatibility.

Dual-energy micro-CT for quantifying the time-course and staining characteristics of ex-vivo animal organs treated with iodine- and gadolinium-based contrast agents.

Chemical staining of soft-tissues can be used as a strategy to increase their low inherent contrast in X-ray absorption micro-computed tomography (micro-CT), allowing to obtain fast three-dimensional structural information of animal organs. Though some staining agents are commonly used in this context, little is known about the staining agents' ability to stain specific types of tissues; the times necessary to provide a sufficient contrast; and the effect of staining solution in distorting the tissue. Here we contribute to studies of animal organs (mouse heart and lungs) using staining combined with dual-energy micro-CT (DECT). DECT was used in order to obtain an additional quantitative measure for the amount of staining agents within the sample in 3D maps. Our results show that the two staining solutions used in this work diffuse differently in the tissues studied, the staining times of some tens of minutes already produce high-quality micro-CT images and, at the concentrations applied in this work, the staining solutions tested do not cause relevant tissue distortions. While one staining solution provides images of the general morphology of the organs, the other reveals organs' features in the order of a hundred micrometers.