Impact of automated methods for quantitative evaluation of immunostaining: Towards digital pathology

• DOI: 10.3389/fonc.2022.931035
• Publication Date: 2022-10-11T06:58:14Z
• Authors: Nicolas Elie; Florence Giffard; Cécile Blanc-Four...; Pierre-Marie Morice; Pierre-Emmanuel B...; Soizic Dutoit; Benoît Plancoulaine; Laurent Poulain
• Keywords: Immunostaining; Stereology; Digital Pathology; Ex vivo; Imaging biomarker

Introduction We sought to develop a novel method for fully automated, robust quantification of protein biomarker expression within the epithelial component high-grade serous ovarian tumors (HGSOC). Rather than defining thresholds given biomarker, objective this study in small cohort patients was applicable many clinical situations which immunomarkers need be quantified. aimed quantify by correlating it with heterogeneity staining, using non-subjective choice scoring based on classical mathematical approaches. This could lead universal quantifying other immunohistochemical markers guide pathologists therapeutic decision-making. Methods studied 25 cases HGSOC three biomarkers predictive response observed ex vivo BH3 mimetic molecule ABT-737 had been previously validated pathologist. calibrated our algorithms Stereology analyses performed two experts detect staining and epithelial/stromal compartments. Immunostaining grids hexagons then each histological slice. To define from distribution histograms classify hexagon as low, medium, or high, we used Gaussian Mixture Model (GMM). Results analysis calibration process produced good correlation between both epithelium immunostaining detection. There also image processing. Image processing clearly revealed respective proportions high areas single tumor showed that parameter included composite score, thus decreasing level discrepancy. Therefore, agreement pathologist increased taking into account. Conclusion discussion simple, robust, basic tools known parameters can characterize different It is takes intratumoral Although some discrepancies diminished, pathologist’s classification satisfactory. The replicable analyze biological medical issues. technique assessing uses automated (GMM) defined scores take intra-tumor help avoid misclassification its subsequent negative impact care.