In addition to the variety created by the mechanics of acquiring a tissue slice, tissue also contains more natural variety than cell lines. The positioning artifacts of nuclei described above are a complication to the analysis of a tissue image because most image analysis pipelines rely upon clear nucleus signal for seeding the segmentation of cytoplasmic regions. Cytoplasmic regions of cells whose nuclei were not captured in the tissue slice can reside above or below fully captured nuclei this increases the chance of mis-classifying cells. This increases the variety of nucleus size and intensity as some nuclei are only partially captured. their nuclei are not entirely captured within the slice. There are many cells that are not centered in this plane, i.e. This overlapping stems from the fact that tissue slices reveal a plane from a 3D volume of cells from an excised portion of tissue. The density of the cells makes segmentation complicated as there is extensive overlapping between cell types, which is much greater than that seen even in dense monolayers of cultured cells. The greatest challenge in quantifying the spatial relationships among these cells, and the others surrounding them, is the identification of individual cell boundaries – a process known as segmentation. Two cell types have been stained that are of particular interest in Hodgkin’s Lymphoma: Reed-Sternberg cells (aka RS in green), and tumor-associated macrophages (aka TAM in red). The nuclei of all cells are stained (blue). Consider the image of a representative tissue slice (below), which reveals a field of view with a high cell density. In collaboration with the Margaret Shipp and Scott Rodig labs, we developed a pipeline in CellProfiler that addresses unique challenges presented by imaging tissue slices. Ultimately the aim is to define various configurations of this interaction that are predictive of patient outcome or the likelihood of success for a given treatment, such as immunotherapy. The ability to precisely measure this relationship will give a deeper understanding of the progression of cancer and might yield new insight into when and how the immune system is involved. Quantifying the cell locations provides the ability to gauge the degree to which the cancer has invaded a tissue and how the immune system is interacting with the leading edge of a tumor. In lymph node sections, cells have representatives from the immune system, epithelial tissue, connective tissue, and cancer. Quantifying the spatial relationship among cells in the crowded environment of a tissue requires reliable segmentation of several cell types. The strength of the inflammatory response has been linked to the prognosis of certain cancers such as lymphoma. Interactions among cells within a tissue are crucial to understanding the role of the inflammation that is triggered by the invasion of cancerous cells. Imaging tissue slices provides a wealth of data about the spatial composition and number of the various cell types that make up a tissue.
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