Breast Cancer Research and Treatment

, Volume 152, Issue 2, pp 367–375 | Cite as

Optimizing HER2 assessment in breast cancer: application of automated image analysis

  • Henrik Holten-Rossing
  • Maj-Lis Møller Talman
  • Martin Kristensson
  • Ben Vainer
Clinical trial


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.


Breast cancer Invasive ductal carcinoma HER2 FISH HER2-CONNECT Image analysis Digital Automated 



Chromogenic in situ hybridization


Fluorescence in situ hybridization


Human epidermal growth factor receptor 2


Digital image analysis




Tissue microarray


Conflict of interest

Martin Kristensson is employee at Visiopharm, Denmark.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Henrik Holten-Rossing
    • 1
  • Maj-Lis Møller Talman
    • 1
  • Martin Kristensson
    • 2
  • Ben Vainer
    • 1
  1. 1.Department of Pathology, RigshospitaletUniversity of CopenhagenCopenhagenDenmark
  2. 2.VisiopharmHørsholmDenmark

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