Analyzing Immunohistochemically Stained Whole-Slide Images of Ovarian Carcinoma

Abstract

Digital pathology, driven by the increasing capabilities of modern computers, is an emerging field within medical research and diagnostics. A re-occurring task in pathology is the analysis of immunohistochemical (IHC) stains, i.e. stains in which a specific type of immune cell is highlighted using corresponding antibodies. Automatic quantification of these images is a challenge due to large image sizes of up to 10 gigapixels, but provides a more objective and reproducible evaluation than the exhaustive task of manual analysis. In this context, we compare counting measures against area-based measures in the case of cytoplasmic and membrane-bound IHC stains. Our evaluation indicates a superior performance of the area-based method which reaches a Jaccard index of approximately 80%, while cell nuclei count-based approaches can be severely affected by variance due to masking effects when the cytoplasmic chromogenic staining covers the blue nuclear counterstain