title: Optimizing HER2 assessment in breast cancer: application of automated image analysis.
abstract: In breast cancer, analysis of HER2 expression is pivotal for treatment decision. This study aimed at comparing digital, automated image analysis with manual reading using the HER2-CONNECT algorithm (Visiopharm) in order to minimize the number of equivocal 2+ scores and the need for reflex fluorescence in situ hybridization (FISH) analysis. Consecutive samples from 462 patients were included. Tissue micro arrays (TMAs) were routinely manufactured including two 2 mm cores from each patient, and each core was assessed in order to ensure the presence of invasive carcinoma. Immunohistochemical staining (IHC) was performed with Roche/Ventana's HER2 ready-to-use kit. TMAs were scanned in a Zeiss Axio Z1 scanner, and one batch analysis of the HER2-CONNECT algorithm including all core samples was run using Visiopharm's cloud-based software. The automated reading was compared to conventional manual assessment of HER2 protein expression, together with FISH analysis of HER2 gene amplification for borderline (2+) protein expression samples. Compared to FISH analysis, manual assessment of the HER2 protein expression demonstrated a sensitivity of 85.8% and a specificity of 86.0% with 14.0% equivocal samples. With HER2-CONNECT, sensitivity increased to 100 % and specificity to 95.5% with less than 4.5% equivocal. Total agreement when comparing HER2-CONNECT with manual IHC assessment supplemented by FISH for borderline (2+) cases was 93.6%. Application of automated image analysis for HER2 protein expression instead of manual assessment decreases the need for supplementary FISH testing by 68%. In the routine diagnostic setting, this would have significant impact on cost reduction and turn-around time.
authors.affiliation: Department of Pathology, Rigshospitalet, University of Copenhagen, Frederik V's Vej 11, 2100, Copenhagen, Denmark, henrik.holm.rossing@regionh.dk.
authors.forename: Henrik
authors.initials: H
authors.lastname: Holten-Rossing
authors.forename: Maj-Lis
authors.initials: ML
authors.lastname: Møller Talman
authors.forename: Martin
authors.initials: M
authors.lastname: Kristensson
authors.forename: Ben
authors.initials: B
authors.lastname: Vainer
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007150:Immunohistochemistry / Q000379:methods; D017404:In Situ Hybridization, Fluorescence / Q000379:methods; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000235:genetics* / Q000378:metabolism; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases