Characterization of transient and progressive pulmonary fibrosis by spatially correlated phase contrast microCT, classical histopathology and atomic force microscopy.

Pulmonary fibrosis (PF) is a severe and progressive condition in which the lung becomes scarred over time resulting in pulmonary function impairment. Classical histopathology remains an important tool for micro-structural tissue assessment in the diagnosis of PF. A novel workflow based on spatial correlated propagation-based phase-contrast micro computed tomography (PBI-microCT), atomic force microscopy (AFM) and histopathology was developed and applied to two different preclinical mouse models of PF - the commonly used and well characterized Bleomycin-induced PF and a novel mouse model for progressive PF caused by conditional Nedd4-2 KO. The aim was to integrate structural and mechanical features from hallmarks of fibrotic lung tissue remodeling. PBI-microCT was used to assess structural alteration in whole fixed and paraffin embedded lungs, allowing for identification of fibrotic foci within the 3D context of the entire organ and facilitating targeted microtome sectioning of planes of interest for subsequent histopathology. Subsequently, these sections of interest were subjected to AFM to assess changes in the local tissue stiffness of previously identified structures of interest. 3D whole organ analysis showed clear morphological differences in 3D tissue porosity between transient and progressive PF and control lungs. By integrating the results obtained from targeted AFM analysis, it was possible to discriminate between the Bleomycin model and the novel conditional Nedd4-2 KO model using agglomerative cluster analysis. As our workflow for 3D spatial correlation of PBI, targeted histopathology and subsequent AFM is tailored around the standard procedure of formalin-fixed paraffin-embedded (FFPE) tissue specimens, it may be a powerful tool for the comprehensive tissue assessment beyond the scope of PF and preclinical research.

Spatial correlation of 2D hard-tissue histology with 3D microCT scans through 3D printed phantoms.

Hard-tissue histology-the analysis of thin two-dimensional (2D) sections-is hampered by the opaque nature of most biological specimens, especially bone. Therefore, the cutting process cannot be assigned to regions of interest. In addition, the applied cutting-grinding method is characterized by significant material loss. As a result, relevant structures might be missed or destroyed, and 3D features can hardly be evaluated. Here, we present a novel workflow, based on conventual microCT scans of the specimen prior to the cutting process, to be used for the analysis of 3D structural features and for directing the sectioning process to the regions of interest. 3D printed fiducial markers, embedded together with the specimen in resin, are utilized to retrospectively register the obtained 2D histological images into the 3D anatomical context. This not only allows to identify the cutting position, but also enables the co-registration of the cell and extracellular matrix morphological analysis to local 3D information obtained from the microCT data. We have successfully applied our new approach to assess hard-tissue specimens of different species. After matching the predicted microCT cut plane with the histology image, we validated a high accuracy of the registration process by computing quality measures namely Jaccard and Dice similarity coefficients achieving an average score of 0.90 ± 0.04 and 0.95 ± 0.02, respectively. Thus, we believe that the novel, easy to implement correlative imaging approach holds great potential for improving the reliability and diagnostic power of classical hard-tissue histology.

Current Approaches for Image Fusion of Histological Data with Computed Tomography and Magnetic Resonance Imaging.

Classical analysis of biological samples requires the destruction of the tissue's integrity by cutting or grinding it down to thin slices for (Immuno)-histochemical staining and microscopic analysis. Despite high specificity, encoded in the stained 2D section of the whole tissue, the structural information, especially 3D information, is limited. Computed tomography (CT) or magnetic resonance imaging (MRI) scans performed prior to sectioning in combination with image registration algorithms provide an opportunity to regain access to morphological characteristics as well as to relate histological findings to the 3D structure of the local tissue environment. This review provides a summary of prevalent literature addressing the problem of multimodal coregistration of hard- and soft-tissue in microscopy and tomography. Grouped according to the complexity of the dimensions, including image-to-volume (2D ⟶ 3D), image-to-image (2D ⟶ 2D), and volume-to-volume (3D ⟶ 3D), selected currently applied approaches are investigated by comparing the method accuracy with respect to the limiting resolution of the tomography. Correlation of multimodal imaging could position itself as a useful tool allowing for precise histological diagnostic and allow the a priori planning of tissue extraction like biopsies.

Reversible shape changes of Pd nanoparticles on MgO(100).

We studied the interaction of oxygen with MgO(100) supported Pd nanoparticles at 10(-5) mbar oxygen pressure and a sample temperature of 570 K. We employed high-resolution X-ray reciprocal space mapping, which allows us to resolve the average particle shape from the quantitative analysis of intensity diffraction rods running perpendicular to corresponding facet surfaces. We identified the oxygen induced formation of nanosized (112) facets which is reversible in a CO atmosphere. Our results give direct evidence for the microscopic evolution of the nanoparticle shape under reactant exposure, which is essential for an atomistic understanding of catalytic reactions on nanoparticles.