3D imaging of human organs with micrometer resolution - applied to the endocrine pancreas

Illuminating the complete ß-cell mass of the human pancreas- signifying a new view on the islets of Langerhans

Pancreatic islets of Langerhans play a pivotal role in regulating blood glucose homeostasis, but critical information regarding their mass, distribution and composition is lacking within a whole organ context. Here, we apply a 3D imaging pipeline to generate a complete account of the insulin-producing islets throughout the human pancreas at a microscopic resolution and within a maintained spatial 3D context. These data show that human islets are far more heterogenous than previously accounted for with regards to their size distribution and cellular make up. By deep tissue 3D imaging, this in-depth study demonstrates that 50% of the human insulin-expressing islets are virtually devoid of glucagon-producing α-cells, an observation with significant implications for both experimental and clinical research.

Geometric and topological characterization of the cytoarchitecture of islets of Langerhans

The islets of Langerhans are critical endocrine micro-organs that secrete hormones regulating energy metabolism in animals. Insulin and glucagon, secreted by beta and alpha cells, respectively, are responsible for metabolic switching between fat and glucose utilization. Dysfunction in their secretion and/or counter-regulatory influence leads to diabetes. Debate in the field centers on the cytoarchitecture of islets, as the signaling that governs hormonal secretion depends on structural and functional factors, including electrical connectivity, innervation, vascularization, and physical proximity. Much effort has therefore been devoted to elucidating which architectural features are significant for function and how derangements in these features are correlated or causative for dysfunction, especially using quantitative network science or graph theory characterizations. Here, we ask if there are non-local features in islet cytoarchitecture, going beyond standard network statistics, that are relevant to islet function. An example is ring structures, or cycles, of α and δ cells surrounding β cell clusters or the opposite, β cells surrounding α and δ cells. These could appear in two-dimensional islet section images if a sphere consisting of one cell type surrounds a cluster of another cell type. To address these issues, we developed two independent computational approaches, geometric and topological, for such characterizations. For the latter, we introduce an application of topological data analysis to determine locations of topological features that are biologically significant. We show that both approaches, applied to a large collection of islet sections, are in complete agreement in the context both of developmental and diabetes-related changes in islet characteristics. The topological approach can be applied to three-dimensional imaging data for islets as well.

Three-dimensional analysis of human pancreatic cancer specimens by phase-contrast based X-ray tomography - the next dimension of diagnosis

BACKGROUND

The worldwide increase of pancreatic ductal adenocarcinoma (PDAC), which still has one of the lowest survival rates, requires novel imaging tools to improve early detection and to refine diagnosis. Therefore, the aim of this study was to assess the feasibility of propagation-based phase-contrast X-ray computed tomography of already paraffin-embedded and unlabeled human pancreatic tumor tissue to achieve a detailed three-dimensional (3D) view of the tumor sample in its entirety.

METHODS

Punch biopsies of areas of particular interest were taken from paraffin blocks after initial histological analysis of hematoxylin and eosin stained tumor sections. To cover the entire 3.5 mm diameter of the punch biopsy, nine individual tomograms with overlapping regions were acquired in a synchrotron parallel beam configuration and stitched together after data reconstruction. Due to the intrinsic contrast based on electron density differences of tissue components and a voxel size of 1.3 μm achieved PDAC and its precursors were clearly identified.

RESULTS

Characteristic tissue structures for PDAC and its precursors, such as dilated pancreatic ducts, altered ductal epithelium, diffuse immune cell infiltrations, increased occurrence of tumor stroma and perineural invasion were clearly identified. Certain structures of interest were visualized in three dimensions throughout the tissue punch. Pancreatic duct ectasia of different caliber and atypical shape as well as perineural infiltration could be contiguously traced by viewing serial tomographic slices and by applying semi-automatic segmentation. Histological validation of corresponding sections confirmed the former identified PDAC features.

CONCLUSION

In conclusion, virtual 3D histology via phase-contrast X-ray tomography visualizes diagnostically relevant tissue structures of PDAC in their entirety, preserving tissue integrity in label-free, paraffin embedded tissue biopsies. In the future, this will not only enable a more comprehensive diagnosis but also a possible identification of new 3D imaging tumor markers.

Type I interferon shapes brain distribution and tropism of tick-borne flavivirus

Viral tropism within the brain and the role(s) of vertebrate immune response to neurotropic flaviviruses infection is largely understudied. We combine multimodal imaging (cm-nm scale) with single nuclei RNA-sequencing to study Langat virus in wildtype and interferon alpha/beta receptor knockout (Ifnar^-/-) mice to visualize viral pathogenesis and define molecular mechanisms. Whole brain viral infection is imaged by Optical Projection Tomography coregistered to ex vivo MRI. Infection is limited to grey matter of sensory systems in wildtype mice, but extends into white matter, meninges and choroid plexus in Ifnar^-/- mice. Cells in wildtype display strong type I and II IFN responses, likely due to Ifnb expressing astrocytes, infiltration of macrophages and Ifng-expressing CD8+ NK cells, whereas in Ifnar^-/-, the absence of this response contributes to a shift in cellular tropism towards non-activated resident microglia. Multimodal imaging-transcriptomics exemplifies a powerful way to characterize mechanisms of viral pathogenesis and tropism.

Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer

Pancreatic cancer is currently the third leading cause of cancer death in the United States. The clinical hallmarks of this disease include abdominal pain that radiates to the back, the presence of a hypoenhancing intrapancreatic lesion on imaging, and widespread liver metastases. Technologies such as tissue clearing and three-dimensional (3D) reconstruction of digitized serially sectioned hematoxylin and eosin-stained slides can be used to visualize large (up to 2- to 3-centimeter cube) tissues at cellular resolution. When applied to human pancreatic cancers, these 3D visualization techniques have provided novel insights into the basis of a number of the clinical characteristics of this disease. Here, we describe the clinical features of pancreatic cancer, review techniques for clearing and the 3D reconstruction of digitized microscope slides, and provide examples that illustrate how 3D visualization of human pancreatic cancer at the microscopic level has revealed features not apparent in 2D microscopy and, in so doing, has closed the gap between bench and bedside. Compared with animal models and 2D microscopy, studies of human tissues in 3D can reveal the difference between what can happen and what does happen in human cancers.

Challenges and advances in optical 3D mesoscale imaging

Optical mesoscale imaging is a rapidly developing field that allows the visualisation of larger samples than is possible with standard light microscopy, and fills a gap between cell and organism resolution. It spans from advanced fluorescence imaging of micrometric cell clusters to centimetre-size complete organisms. However, with larger volume specimens, new problems arise. Imaging deeper into tissues at high resolution poses challenges ranging from optical distortions to shadowing from opaque structures. This manuscript discusses the latest developments in mesoscale imaging and highlights limitations, namely labelling, clearing, absorption, scattering, and also sample handling. We then focus on approaches that seek to turn mesoscale imaging into a more quantitative technique, analogous to quantitative tomography in medical imaging, highlighting a future role for digital and physical phantoms as well as artificial intelligence.

TISSUE CLEARING

Tissue clearing of gross anatomical samples was first described over a century ago and has only recently found widespread use in the field of microscopy. This renaissance has been driven by the application of modern knowledge of optical physics and chemical engineering to the development of robust and reproducible clearing techniques, the arrival of new microscopes that can image large samples at cellular resolution and computing infrastructure able to store and analyze large data volumes. Many biological relationships between structure and function require investigation in three dimensions and tissue clearing therefore has the potential to enable broad discoveries in the biological sciences. Unfortunately, the current literature is complex and could confuse researchers looking to begin a clearing project. The goal of this Primer is to outline a modular approach to tissue clearing that allows a novice researcher to develop a customized clearing pipeline tailored to their tissue of interest. Further, the Primer outlines the required imaging and computational infrastructure needed to perform tissue clearing at scale, gives an overview of current applications, discusses limitations and provides an outlook on future advances in the field.