title: Virtual Double Staining: A Digital Approach to Immunohistochemical Quantification of Estrogen Receptor Protein in Breast Carcinoma Specimens.
abstract: Visual assessment of immunohistochemically detected estrogen receptor protein is prone to interobserver and intraobserver variation due to its subjective evaluation. The aim of this study was to validate a new image analysis system based on virtual double staining (VDS) by comparing visual and automated scorings of ER in tissue microarrays of breast carcinomas. Tissue microarrays were constructed of 112 consecutive resection specimens of breast carcinomas. Immunohistochemistry assays for ER and pancytokeratin was applied on separate serial sections. ER scoring was visually performed by 5 observers using the histoscore (H-score) method. The Visiopharm ER image analysis protocol (APP) software application using VDS technique was applied separating stromal cells from carcinoma and other epithelial cells based on the pancytokeratin reaction. Using color deconvolution, polynomial filters, and nuclear segmentation the APP determined the percentage of positive cells and their intensity, and calculated the resulting H-score. On the basis of 1% cutoff VDS was perfectly correlated with visual assessment (κ=1). Using H-score, a very high agreement between VDS and visual ER assessment was seen (R=0.950). Image analysis has the attributes to eliminate the shortcomings of visual ER evaluation by generating automated, reproducible, and objective results of ER assessment.
authors.affiliation: Institute of Pathology, Aalborg University Hospital, Aalborg, Denmark.
authors.forename: Nina
authors.initials: N
authors.lastname: Lykkegaard Andersen
authors.forename: Anja
authors.initials: A
authors.lastname: Brügmann
authors.forename: Giedrius
authors.initials: G
authors.lastname: Lelkaitis
authors.forename: Søren
authors.initials: S
authors.lastname: Nielsen
authors.forename: Michael
authors.initials: M
authors.lastname: Friis Lippert
authors.forename: Mogens
authors.initials: M
authors.lastname: Vyberg
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001943:Breast Neoplasms / Q000378:metabolism / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000378:metabolism*; D015588:Observer Variation; D011960:Receptors, Estrogen / Q000378:metabolism*; D012984:Software; D013194:Staining and Labeling
chemical_list: D009363:Neoplasm Proteins; D011960:Receptors, Estrogen