Digital Pathology Meets Spatial Omics: Emerging Problems in Data Integration, Solutions, and New Opportunities

Music City Center 

This talk will introduce parallel advancements of two emerging fields, computational pathology and spatial –omics, in the modern era of biomedical sciences. Accordingly, my team leverages computational image analysis tools and best engineering practices to integrate spatial –omics datasets with their associated histology images, to draw meaningful conclusions. We work to fundamentally understand cell type and cell state compositions and underlying quantitative morphometric features at various scales from transcripts to tissue microanatomy. Additionally, I will highlight our ongoing efforts within the Human Biomolecular Atlas Project (HuBMAP), a consortium spanning 42 sites, focused on creating an atlas of the human body at the cellular level using spatial technologies. Moreover, I will discuss the detection and segmentation of multiple cell types and cell states as well as tissue microanatomy exclusively from brightfield histology images. Furthermore, I'll explore several use-case studies of these tools including use in kidney disease trajectory prediction, relevant to the NIH Kidney Precision Medicine Project (KPMP) consortium, and distinguishing glomeruli with chronic and acute injury. Additionally, I will demonstrate our cloud-based open-source distributed software systems (FUSION Functional Unit State IdentificatiON in Whole Slide Images, accessible at http://fusion.hubmapconsortium.org/, and CompRePS Computational Renal Pathology Suite, accessible at https://athena.rc.ufl.edu/). These systems are designed to conduct various computational image analysis tasks related to digital pathology, starting with the analysis of brightfield histology images and extending to the integration of histology with spatial omics data. We'll conclude by discussing new opportunities and potential directions for collective contributions in the field of computational pathology.

Computational Pathology