Three-dimensional reconstruction and microanatomical analysis of large tissues with applications to the human pancreas

Abstract

A central challenge in the study of disease progression is obtaining high-resolution, high-content information conveying the structural and molecular microanatomy of normal and diseased tissues. Towards this, researchers utilize techniques capable of three-dimensional (3D) imaging of tissues via tissue clearing and serial sectioning. In clearing, intact samples of micron or mm-scale are rendered transparent, labelled with 1-5 stains, and imaged using confocal or light sheet microscopy. In serial sectioning, samples of mm or cm-scale are thinly sliced, labelled with histological stains, and computationally reconstructed. Previous clearing and sectioning approaches generally fail in reconstruction of large, cm3 tissues, require expensive antibody labelling, and/or create volume renderings which are notoriously difficult to quantify. This dissertation focuses on CODA, a method designed to improve on previous 3D reconstruction techniques. CODA is a serial sectioning method capable of reconstruction and analysis of cm3 scale samples using deep learning labelling of hematoxylin & eosin (H&E) sections. As H&E is markedly cheaper than the antibody labelling used in tissue clearing and previous serial sectioning approaches, CODA offers a means of quantitative assessment of normal and diseased samples in large volumes without the need for expensive staining techniques. As a testbed, I assess the microanatomy of the human pancreas during tumorigenesis within the hyperbranched pancreatic ductal system. CODA empowers identification of distinct precancer phenotypes from lesions that vary in volume, cellularity, and three-dimensional morphology. I show that pancreatic cancer tends to spread along collagen fibers that are highly aligned to the existing ductal structure, allowing distant extension from the bulk tumor. Through utilization of intervening unstained sections, I integrate CODA with immunohistochemistry, imaging mass cytometry, and DNA sequencing for more detailed analyses such as heterogeneity of the immune microenvironment and mutational profiles of pancreatic cancer precursors. CODA establishes a means to transform the structural study of human diseases, provide fundamental quantitative metrics for improved design of model biological systems, and is a useful as a tool for medical education