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1.
Toxicol Pathol ; 49(4): 755-772, 2021 06.
Article in English | MEDLINE | ID: mdl-33251977

ABSTRACT

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. We tested these propositions by using 1 hematoxylin and eosin stainer to process 13 formalin-fixed, paraffin-embedded (FFPE) mouse tissues and by using 3 identically programmed and loaded immunostainers to process 5 FFPE mouse tissues for 4 cell biomarkers. Digital images of stained sections acquired with a commercial whole slide scanner were analyzed by customizable algorithms incorporated into commercially available DIA software. Staining intensity as viewed qualitatively by an observer and/or quantitatively by DIA was affected by staining conditions and tissue attributes. Intrarun and inter-run IHC staining intensities were equivalent for each tissue when processed on a given stainer but varied measurably across stainers. Our data indicate that staining quality must be monitored for each method and stainer to ensure that preanalytical factors do not impact digital pathology data quality.


Subject(s)
Biomarkers, Tumor , Image Processing, Computer-Assisted , Algorithms , Animals , Immunohistochemistry , Mice , Software
2.
J Histotechnol ; 43(1): 29-37, 2020 03.
Article in English | MEDLINE | ID: mdl-31969082

ABSTRACT

Staining 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. Results from image analysis are more sensitive to variations in staining than microscopic evaluation by a pathologist. There are two goals with this study. The first was to track the precision of hematoxylin and eosin (H&E) staining, in both nuclear and cytoplasmic components by OD. The second was to determine the impact of different pre-analytical and analytical variables on the OD results. Specifically, the endpoints investigated were quality parameters including impacts of section thickness, protocol manipulation, expired hematoxylin on staining precision and reproducibility of staining over time. Our results show that image analysis of H&E-stained tissue sections is a viable tool for assessing and verifying staining quality. We also show that OD analysis results for H&E-stained sections are affected by changing pre-analytical and/or reagent variables. These authors chose a graphical rather than fully statistical analysis of the results to highlight the utility of visual aids in demonstrating H&E staining reproducibility.


Subject(s)
Hematoxylin/pharmacology , Image Processing, Computer-Assisted , Laboratories , Staining and Labeling , Biopsy , Coloring Agents/pharmacology , Eosine Yellowish-(YS)/pharmacology , Humans , Image Processing, Computer-Assisted/methods , Laboratories/standards , Reproducibility of Results , Staining and Labeling/methods , Staining and Labeling/standards
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