INTRODUCTION: As we move into the era of next-generation digital pathology, also referred to as computational pathology, current challenges in pathobiology comprise (i) automation of biomarker profiling in histological samples, (ii) quantitative integration of protein expression profiles and genetic information, as well as (iii) correlation analysis and data mining of high-plex data in-situ.
METHODS: Our research teams at TissueGnostics and Queensland University of Technology have joined forces to combine TissueGnostics’ existing tissue cytometry technology platform and established knowhow with innovative AI solutions to establish The Virtual Histopathologist1.
RESULTS: Tissue Cytometry permits to determine the in-situ phenotype of cells as well as histological entities, like glands, vessels or tumor foci. Applications include but are not limited to the exploration of the tumor microenvironment and/or the spatial organization of cellular subpopulations, assessment of different bone structures, quantification of blood vessels and neovascularization as well as analysis of samples in multiplexing or multispectral mode.
To better understand the function of inflammatory cells in tumor development, type and number of inflammatory cells and their proximity to glandular/tumor structures have to be analyzed in-situ and correlated with disease state. Using TissueFAXS™ Cytometry the time-consuming and error-prone human evaluation of stained histological sections can be approached with an observer-independent and reproducible technology platform, offering a high degree of automation, paired with user interaction at relevant points of the analytical workflow.
DISCUSSION & CONCLUSIONS: The TissueFAXS Cytometry platform incorporates Machine & Deep Learning algorithms. It can do end-point assays as well as live-cell imaging and time-kinetic experiments to measure enzyme activity. It also promotes tissue cytometry to a new level of quality, where complex cellular interactions, intracellular expression profiles and signal transduction cascades can be addressed on the single-cell level but still in histological context, empowering precision diagnostics.