title: Digital image analysis of membrane connectivity is a robust measure of HER2 immunostains.
abstract: The purpose of this study was to develop and validate a new software, HER2-CONNECT(TM), for digital image analysis of the human epidermal growth factor receptor 2 (HER2) in breast cancer specimens. The software assesses immunohistochemical (IHC) staining reactions of HER2 based on an algorithm evaluating the cell membrane connectivity. The HER2-CONNECT algorithm was aligned to match digital image scorings of HER2 performed by 5 experienced assessors in a training set and confirmed in a separate validation set. The training set consisted of 167 breast carcinoma tissue core images in which the assessors individually and blinded outlined regions of interest and gave their HER2 score 0/1+/2+/3+ to the specific tumor region. The validation set consisted of 86 core images where the result of the automated image analysis software was correlated to the scores provided by the 5 assessors. HER2 fluorescence in situ hybridization (FISH) was performed on all cores and used as a reference standard. The overall agreement between the image analysis software and the digital scorings of the 5 assessors was 92.1% (Cohen's Kappa: 0.859) in the training set and 92.3% (Cohen's Kappa: 0.864) in the validation set. The image analysis sensitivity was 99.2% and specificity 100% when correlated to FISH. In conclusion, the Visiopharm HER2 IHC algorithm HER2-CONNECT(TM) can discriminate between amplified and non-amplified cases with high accuracy and diminish the equivocal category and thereby provides a promising supplementary diagnostic tool to increase consistency in HER2 assessment.
authors.affiliation: Institute of Pathology, Aalborg Hospital, Aarhus University Hospital, Ladegaardsgade 3, 9100 Aalborg, Denmark. ahb@rn.dk
authors.forename: Anja
authors.initials: A
authors.lastname: Brügmann
authors.forename: Mikkel
authors.initials: M
authors.lastname: Eld
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: Grunkin
authors.forename: Johan D
authors.initials: JD
authors.lastname: Hansen
authors.forename: Niels T
authors.initials: NT
authors.lastname: Foged
authors.forename: Mogens
authors.initials: M
authors.lastname: Vyberg
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000378:metabolism; D018270:Carcinoma, Ductal, Breast / Q000175:diagnosis* / Q000378:metabolism; D002462:Cell Membrane / Q000378:metabolism*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007150:Immunohistochemistry; D017404:In Situ Hybridization, Fluorescence; D015588:Observer Variation; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism*; D012680:Sensitivity and Specificity; D012984:Software; D046888:Tissue Array Analysis
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human