Digital image analysis (DIA) is impacted by the quality of tissue staining. This study examined the influence of preanalytical variables-staining protocol design, reagent quality, section attributes, and instrumentation-on the performance of automated DIA software. Our hypotheses were that (1) staining intensity is impacted by subtle differences in protocol design, reagent quality, and section composition and that (2) identically programmed and loaded stainers will produce equivalent immunohistochemical (IHC) staining.
View Article and Find Full Text PDFStaining quality and reproducibility are essential factors to monitor laboratory quality assurance. In the last decade, there has been an increase in the use of digital pathology and image analysis. While the adoption of these tools provides a potential means to track staining precision by optical density (OD), it also presents challenges.
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