Membrane connectivity estimated by digital image analysis of HER2 immunohistochemistry is concordant with visual scoring and fluorescence in situ hybridization results: algorithm evaluation on breast cancer tissue microarrays

IntroductionThe human epidermal growth factor receptor 2 (HER2) is an established biomarker for management of patients with breast cancer. While conventional testing of HER2 protein expression is based on semi-quantitative visual scoring of the immunohistochemistry (IHC) result, efforts to reduce inter-observer variation and to produce continuous estimates of the IHC data are potentiated by digital image analysis technologies.MethodsHER2 IHC was performed on the tissue microarrays (TMAs) of 195 patients with an early ductal carcinoma of the breast. Digital images of the IHC slides were obtained by Aperio ScanScope GL Slide Scanner. Membrane connectivity algorithm (HER2-CONNECT™, Visiopharm) was used for digital image analysis (DA). A pathologist evaluated the images on the screen twice (visual evaluations: VE1 and VE2). HER2 fluorescence in situ hybridization (FISH) was performed on the corresponding sections of the TMAs. The agreement between the IHC HER2 scores, obtained by VE1, VE2, and DA was tested for individual TMA spots and patient's maximum TMA spot values (VE1max, VE2max, DAmax). The latter were compared with the FISH data. Correlation of the continuous variable of the membrane connectivity estimate with the FISH data was tested.ResultsThe pathologist intra-observer agreement (VE1 and VE2) on HER2 IHC score was almost perfect: kappa 0.91 (by spot) and 0.88 (by patient). The agreement between visual evaluation and digital image analysis was almost perfect at the spot level (kappa 0.86 and 0.87, with VE1 and VE2 respectively) and at the patient level (kappa 0.80 and 0.86, with VE1max and VE2max, respectively). The DA was more accurate than VE in detection of FISH-positive patients by recruiting 3 or 2 additional FISH-positive patients to the IHC score 2+ category from the IHC 0/1+ category by VE1max or VE2max, respectively. The DA continuous variable of the membrane connectivity correlated with the FISH data (HER2 and CEP17 copy numbers, and HER2/CEP17 ratio).ConclusionHER2 IHC digital image analysis based on membrane connectivity estimate was in almost perfect agreement with the visual evaluation of the pathologist and more accurate in detection of HER2 FISH-positive patients. Most immediate benefit of integrating the DA algorithm into the routine pathology HER2 testing may be obtained by alerting/reassuring pathologists of potentially misinterpreted IHC 0/1+ versus 2+ cases.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1973465132560208.

[1]  Jinha M. Park,et al.  Diagnostic Evaluation of HER-2 as a Molecular Target: An Assessment of Accuracy and Reproducibility of Laboratory Testing in Large, Prospective, Randomized Clinical Trials , 2005, Clinical Cancer Research.

[2]  Laoighse Mulrane,et al.  Automated image analysis in histopathology: a valuable tool in medical diagnostics , 2008, Expert review of molecular diagnostics.

[3]  Janina Słodkowska,et al.  Study on breast carcinoma Her2/neu and hormonal receptors status assessed by automated images analysis systems: ACIS III (Dako) and ScanScope (Aperio). , 2010, Folia histochemica et cytobiologica.

[4]  U. Vogel Confirmation of a low HER2 positivity rate of breast carcinomas - limitations of immunohistochemistry and in situ hybridization , 2010, Diagnostic pathology.

[5]  Klaus Kayser,et al.  Quantification of virtual slides: Approaches to analysis of content-based image information , 2011, Journal of pathology informatics.

[6]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[7]  Jan P. A. Baak,et al.  Digital Image Analysis Improves the Quality of Subjective HER-2 Expression Scoring in Breast Cancer , 2008, Applied immunohistochemistry & molecular morphology : AIMM.

[8]  P. Klein,et al.  Concordance between central and local laboratory HER2 testing from a community-based clinical study. , 2006, Clinical breast cancer.

[9]  D. Faratian,et al.  Tissue microarray technology in the routine assessment of HER‐2 status in invasive breast cancer: a prospective study of the use of immunohistochemistry and fluorescence in situ hybridization , 2008, Histopathology.

[10]  Aldo Badano,et al.  Observer variability in the interpretation of HER2/neu immunohistochemical expression with unaided and computer-aided digital microscopy. , 2011, Archives of pathology & laboratory medicine.

[11]  D. Slamon,et al.  Assessment of methods for tissue-based detection of the HER-2/neu alteration in human breast cancer: a direct comparison of fluorescence in situ hybridization and immunohistochemistry. , 2000, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[12]  Søren Nielsen,et al.  Digital image analysis of membrane connectivity is a robust measure of HER2 immunostains , 2012, Breast Cancer Research and Treatment.

[13]  David J. Foran,et al.  Computer-assisted assessment of the Human Epidermal Growth Factor Receptor 2 immunohistochemical assay in imaged histologic sections using a membrane isolation algorithm and quantitative analysis of positive controls , 2008, BMC Medical Imaging.

[14]  M. Henry,et al.  Automated cellular imaging system III for assessing HER2 status in breast cancer specimens: development of a standardized scoring method that correlates with FISH. , 2009, American journal of clinical pathology.

[15]  Kyle J. Myers,et al.  Automated Quantitative Assessment of HER-2/neu Immunohistochemical Expression in Breast Cancer , 2009, IEEE Transactions on Medical Imaging.

[16]  G. Viale,et al.  Pathological definition of triple negative breast cancer. , 2009, European journal of cancer.

[17]  P. Pauwels,et al.  Relationship between pathological features, HER2 protein expression and HER2 and CEP17 copy number in breast cancer: biological and methodological considerations , 2010, Journal of Clinical Pathology.

[18]  E. Perez,et al.  HER2 and chromosome 17 effect on patient outcome in the N9831 adjuvant trastuzumab trial. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[19]  Sean Davis,et al.  Assessment of Automated Image Analysis of Breast Cancer Tissue Microarrays for Epidemiologic Studies , 2010, Cancer Epidemiology, Biomarkers & Prevention.

[20]  Peter A Kaufman,et al.  Concordance between local and central laboratory HER2 testing in the breast intergroup trial N9831. , 2002, Journal of the National Cancer Institute.

[21]  Determination of HER-2 status and chromosome 17 polysomy in breast carcinomas comparing HercepTest and PathVysion FISH assay. , 2004, American journal of clinical pathology.

[22]  Kelli Montgomery,et al.  Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situ hybridization (FISH): pathologist assessment compared to quantitative image analysis , 2009, BMC Cancer.

[23]  J. Ross,et al.  Human epidermal growth factor receptor 2 testing in 2010: does chromosome 17 centromere copy number make any difference? , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[24]  S. Nofech-Mozes,et al.  Intratumoral Heterogeneity of HER2/neu in Breast Cancer—A Rare Event , 2007, The breast journal.

[25]  Anthony Rhodes,et al.  American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. , 2006, Archives of pathology & laboratory medicine.

[26]  Dylan Reilly,et al.  Standardization of HER2 immunohistochemistry in breast cancer by automated quantitative analysis. , 2009, Archives of pathology & laboratory medicine.

[27]  Kyle Porter,et al.  Semi‐automated imaging system to quantitate Her‐2/neu membrane receptor immunoreactivity in human breast cancer , 2007, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[28]  Marilyn M. Bui,et al.  Using image analysis as a tool for assessment of prognostic and predictive biomarkers for breast cancer: How reliable is it? , 2010, Journal of pathology informatics.

[29]  J. Baak,et al.  Comparing subjective and digital image analysis HER2/neu expression scores with conventional and modified FISH scores in breast cancer , 2007, Journal of Clinical Pathology.

[30]  Lynne Dobson,et al.  Image analysis as an adjunct to manual HER-2 immunohistochemical review: a diagnostic tool to standardize interpretation , 2010, Histopathology.

[31]  Paul J Tadrous,et al.  On the concept of objectivity in digital image analysis in pathology , 2010, Pathology.

[32]  D. Rimm,et al.  Immunohistochemistry and quantitative analysis of protein expression. , 2009, Archives of pathology & laboratory medicine.

[33]  Z. Gatalica,et al.  Assessment of HER2 gene status in breast carcinomas with polysomy of chromosome 17 , 2011, Cancer.

[34]  D. Soenksen Digital pathology at the crossroads of major health care trends: corporate innovation as an engine for change. , 2009, Archives of pathology & laboratory medicine.