Abstract #4386

Estimation of prostate cancer distribution on pathology slides via image analysis of IHC-stained slides.

Ethan Leng¹, Jonathan C. Hendriksen², Jin Jin³, Stephen C. Schmechel², and Gregory J. Metzger¹

¹Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, ²Department of Pathology, University of Washington, Seattle, WA, United States, ³Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, United States

For the development of CAD systems of prostate cancer, manual annotation of cancer by experienced pathologists is the gold standard for establishing the ground truth. However, the process is tedious and has finite precision. Here, we describe a framework that uses quantitative analysis of IHC-stained slides to derive parameters, which in turn are used by a trained predictive model to estimate the spatial distribution of malignant epithelium. Thresholding of the results provides a reasonable map of cancer that is comparable to manual annotation.

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