ImmunoMembrane: a publicly available web application for digital image analysis of HER2 immunohistochemistry

Aims: Assessment of the human epidermal growth factor receptor 2 (HER2) with immunohistochemistry (IHC) is routine practice in clinical pathology laboratories. Visual classification of the staining reaction (usually into 0/1+, 2+ or 3+) is subjective and prone to significant inter-and intra-observer variation. In this study, we describe ImmunoMembrane, an easy-to-use HER2 IHC analysis software, which is freely available as a web application, requiring no download or installation. Methods and results: ImmunoMembrane uses colour deconvolution for stain separation and a customized algorithm for cell membrane segmentation. A quantitative score (IM-score, 0-20 points) is generated according to the membrane staining intensity and completeness. Specimens are classified into 0/1+, 2+ or 3+ based on IM-score cut-offs defined using a training set. The classification and membrane segmentation are presented as a pseudo-coloured overlay image. With a validation set (144 HercepTest (R)-stained whole tissue sections), ImmunoMembrane matched well with the pathologist's visual classification (weighted kappa kappa(w) = 0.80), as well as fluorescence in-situ hybridization (FISH) (IHC disagreement 3.5%, n = 144) and chromogenic in-situ hybridization (CISH) (IHC disagreement 2.8%, n = 144). Conclusions: We anticipate that publicly available web applications, such as ImmunoMembrane, will accelerate the adoption of automated image analysis in clinical diagnostics of HER2 IHC. ImmunoMembrane is freely accessible at: http://jvsmicroscope.uta.fi/immunomembrane/.