Abstract: The human vision is limited in terms of perception of color hues and intensities. Moreover, the individual's ability in this context varies greatly from person to person. Herein are described methods to quantify staining of tissue samples via digital tissue image analysis, when staining of a certain biomarker is below or at the threshold of human visual perception, in terms of saturation. This enables for consistent detection of these staining characteristics, which allows for more reproducible data generation through minimizing inter- and intra-observer variability.

Abstract: The disclosure concerns a method for extracting geographic distribution statistics from patient tissue samples assayed with a tissue-based test for the purpose of scoring the patient tissue samples and guiding treatment based on the score(s). The method described herein utilizes digital image analysis of an image of one or more tissue sections to extract object-based (e.g., cells) features to generate a data array representing said tissue numerically in image analysis feature space. The numerical representation of the image of the tissue section in image analysis feature space is further processed using one or more algorithm processes to extract sophisticated geographical distribution features of one or more object type or sub-type in the tissue. Statistics describing the geographic distribution features are summarized to generate a patient-specific diagnostic score, and this score can be evaluated to guide patient treatment decisions.

Abstract: This disclosure concerns methods for evaluating inflammatory cells and modulators of the inflammatory response in tumor tissue and other relevant tissue types. The methods entail: obtaining a tissue sample and processing said tissue sample to produce histologic slides of tissue sections; staining of the tissue sections to identify inflammatory cells and modulators of the inflammatory response; digitizing slides to produce an image of the stained tissue sections; digitally stratifying the tissue sample into tumor and other relevant tissue compartments; and using digital image analysis to quantify cell-based and cell population-based features. The quantification of cell-based and cell population-based features within a tissue compartment of interest is used to develop a summary score of the immune system-tissue compartment of interest interaction. Patient stratification and selection as candidates for a therapeutic approach is ultimately based on the summary score value.