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.
Significance X-ray computed tomography (CT) imaging has become popular for investigating, nondestructively and three-dimensionally, both external and internal structures of various specimens. However, the limited resolution of conventional laboratory-based CT systems (≥500 nm) still hampers the detailed visualization of features on the low nanometer level. We present a laboratory CT device and data processing pipeline to routinely and efficiently generate high-resolution 3D data (≈100 nm) without requiring synchrotron radiation facilities. Our setup is especially relevant for conducting detailed analysis of very small biological samples, as demonstrated for a walking appendage of a velvet worm. Comparative analyses of our CT data with those obtained from other popular imaging methods highlight the advantages and future applicability of the nanoCT setup.
Abstract 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.
Significance Three-dimensional histology of soft-tissue samples has proven to provide crucial benefits for the understanding of tissue structure. Nevertheless, the low attenuation of soft tissue has impaired the use of computed tomography (CT) as a tool for the nondestructive and 3D visualization of external and internal structural details. We present a cytoplasm-specific staining method tailored for X-ray CT that enables a routine and efficient 3D volume screening at high resolutions. Our technique is fully compatible with conventional histology and allows further histological investigations, as demonstrated for a mouse kidney. The comparative analysis of our CT data with conventional 2D histology highlights the future applicability of the cytoplasm-specific X-ray staining method for modern histological and histopathological investigations using laboratory X-ray CT devices.
Abstract 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.
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.
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.
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.
