Leveraging open-top light-sheet microscopy for 3D pathology: building tools for clinical studies

Abstract

Cancer is a leading cause of death in the United States and represents a heterogeneous set of diseases with a wide variety of treatment approaches and patient outcomes. Biopsies are often used for both initial diagnosis and to grade disease aggressiveness, a key component in making appropriate treatment recommendations. Slide-based pathology is the current gold standard for microscopic analysis of biopsies and other tissue specimens. Despite widespread use, slide-based analysis carries a number of disadvantages. First, slide-based pathology inherently limits analysis to discrete 2D cross sections, which make it difficult to characterize complex 3D tissue structures like vasculature or glandular networks. Second, pathologists typically review only a few sections from each specimen due to the time and labor required to prepare and view each slide, often equating to less than 1% of the entire tissue volume. Third, physical sectioning destroys tissue, complicating downstream molecular assays and archiving. An emerging alternative to slide-based pathology is non-destructive 3D pathology, which provides comprehensive visualization of 3D tissue structure without destructive sectioning. A number of proof-of-concept studies have suggested that 3D pathology can provide clinically relevant information. However, large-scale clinical studies, which will be key for clinical adoption, have remained challenging. This is in part because existing methods for 3D pathology are not optimized for high-throughput imaging of hundreds to thousands of clinical specimens. To enable comprehensive clinical studies using 3D pathology, this dissertation presents a set of imaging technologies and workflows leveraging open- top light-sheet (OTLS) microscopy, a platform for 3D pathology that provides rapid volumetric imaging of large clinical specimens. The goal of this suite of methods is to offer a toolkit for 3D pathology research in the near term and serve as a step towards clinical adoption of 3D pathology in the long term.