Project Summary/Abstract: For the last 150 years, pathologic interpretation of tissues has relied primarily on qualitative descriptive and semi-quantitative ordinal histopathologic scoring systems. This analysis workflow is laborious given its manual nature and can be subjective at times, making the process susceptible to observer bias and variability that leads to reproducibility issues. Additionally, the phenomena intended to be quantified may be too complex or too subtle to be reliably assessed by eye and/or interpreted by a human brain (e.g., exact measurement of affected area, enumeration of cellular phenotypes, spatial relationships of different cell types or biological processes). In this proposal, we request funds to acquire a Vectra Polaris Quantitative Pathology Imaging System, which would allow us to generate continuous quantitative morphomolecular pathomics datasets that will accelerate research discoveries on the Boston University School of Medicine Campus (BUSM). The instrument would be managed by the Integrated Biological Imaging Service (IBIS), which currently provides a diverse array of digital imaging microscopy systems, including confocal and transmission electron microscopy, for studying biological samples such as cells and tissues. IBIS currently lacks a high-throughput whole slide scanner, putting our researchers who rely on characterizing temporospatial signatures of tissue-based assays at a disadvantage. Because of the absence of a designated whole slide scanner, BUSM researchers primarily conduct their microscopic analyses on user-defined regions of interest (ROI), which is a time-intensive process that is confounded by selection biases. The limited throughput of ROI acquisition also hampers the generation of enough data to achieve statistical significance. The Vectra Polaris Quantitative Pathology Imaging System affords the flexibility of high throughput brightfield and fluorescent image acquisition demanded by our researchers. Furthermore, through its unique combination of filter sets and multispectral linear unmixing, this system generates high-plex fluorescent images with optimal analytical sensitivity by removing tissue autofluorescence. Together these features are critical in maximizing the amount of biological data we can generate from precious biological specimens and ensure we can meet the high image acquisition demands anticipated by our users. The Vectra Polaris image acquisition hardware seamlessly integrates with the user-friendly image analysis software inFORM, which allows characterization of meaningful quantitative pathomics datasets and integration/correlation with other continuous datasets to illuminate clinicopathologic correlates of disease. If awarded, and with institutional support to develop a dedicated computer laboratory and data storage infrastructure (see Dean Antman's LOS), this proposal will serve to empower our researchers with the necessary tools to explore biomedical hypotheses not feasible with traditional legacy pathology workflows, empowering research discovery with the ultimate goal of enhancing human health across a diverse portfolio of initiatives being actively studied across the BUSM campus.

Project Narrative: Generation of high-resolution whole slide images of tissues/cells opens new possibilities for high throughput and unbiased downstream quantitative temporospatial characterization of morphomolecular (i.e., proteins and nucleic acids) signatures not feasible with other region of interest-based imaging systems. Furthermore, these techniques provide crucial information about anatomical structure, localization, and interaction of biological processes that is often lacking from other commonly used assays such as flow cytometry, mass spectrometry, and protein and gene expression analysis. This proposal can be adapted to a wide range of currently funded research projects ongoing within BUSM laboratories including the Departments of Anatomy and Neurobiology, Medicine, Microbiology, Molecular and Cell Biology, Pathology and Laboratory Medicine, Pharmacology, and Psychiatry.