Evaluation of cytokeratin-19 in breast cancer tissue samples: a comparison of automatic and manual evaluations of scanned tissue microarray cylinders

BackgroundDigital image (DI) analysis avoids visual subjectivity in interpreting immunohistochemical stains and provides more reproducible results. An automated procedure consisting of two variant methods for quantifying the cytokeratin-19 (CK19) marker in breast cancer tissues is presented.MethodsThe first method (A) excludes the holes inside selected CK19 stained areas, and the second (B) includes them. 93 DIs scanned from complete cylinders of tissue microarrays were evaluated visually by two pathologists and by the automated procedures.Results and conclusionsThere was good concordance between the two automated methods, both of which tended to identify a smaller CK19-positive area than did the pathologists. The results obtained with method B were more similar to those of the pathologists; probably because it takes into account the entire positive tumoural area, including the holes. However, the pathologists overestimated the positive area of CK19. Further studies are needed to confirm the utility of this automated procedure in prognostic studies.

[1]  Heather Dawson,et al.  Next-generation tissue microarray (ngTMA) increases the quality of biomarker studies: an example using CD3, CD8, and CD45RO in the tumor microenvironment of six different solid tumor types , 2013, Journal of Translational Medicine.

[2]  Zygmunt Wróbel,et al.  Automatic analysis of selected choroidal diseases in OCT images of the eye fundus , 2013, Biomedical engineering online.

[3]  Stanislaw Osowski,et al.  Comparative analysis of methods for accurate recognition of cells through nuclei staining of Ki-67 in neuroblastoma and estrogen/progesterone status staining in breast cancer. , 2009, Analytical and quantitative cytology and histology.

[4]  O. Kallioniemi,et al.  Tissue microarray technology for high-throughput molecular profiling of cancer. , 2001, Human molecular genetics.

[5]  Gloria Bueno,et al.  Review of imaging solutions for integrated quantitative immunohistochemistry in the Pathology daily practice. , 2010, Folia histochemica et cytobiologica.

[6]  S. Osowski,et al.  New automated image analysis method for the assessment of Ki-67 labeling index in meningiomas. , 2010, Folia histochemica et cytobiologica.

[7]  John McCafferty,et al.  Expression profiling by high-throughput immunohistochemistry. , 2004, Journal of immunological methods.

[8]  Marylène Lejeune,et al.  Automated quantification of nuclear immunohistochemical markers with different complexity , 2008, Histochemistry and Cell Biology.

[9]  Ruifrok Ac.  QUANTIFICATION OF IMMUNOHISTOCHEMICAL STAINING BY COLOR TRANSLATION AND AUTOMATED THRESHOLDING , 1997 .

[10]  Katja Fall,et al.  Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry , 2012, Journal of Clinical Pathology.

[11]  S M Hewitt,et al.  Tissue microarray: a simple technology that has revolutionized research in pathology. , 2008, Journal of postgraduate medicine.

[12]  P. Chu,et al.  Keratin expression in human tissues and neoplasms , 2002, Histopathology.

[13]  A. Ruifrok,et al.  Quantification of immunohistochemical staining by color translation and automated thresholding. , 1997, Analytical and quantitative cytology and histology.

[14]  P. Tan,et al.  Keratin expression in breast cancers , 2012, Virchows Archiv.

[15]  Valerie Speirs,et al.  The manufacture and assessment of tissue microarrays: suggestions and criteria for analysis, with breast cancer as an example , 2012, Journal of Clinical Pathology.

[16]  I. Ellis,et al.  Expression of luminal and basal cytokeratins in human breast carcinoma , 2004, The Journal of pathology.

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

[18]  Alexander E Kalyuzhny,et al.  The Dark Side of the Immunohistochemical Moon: Industry , 2009, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

[19]  Helen Boyle,et al.  Intra- and interobserver reproducibility of interpretation of immunohistochemical stains of prostate cancer , 2009, Virchows Archiv.

[20]  Elaine Kay,et al.  Virtual microscopy as an enabler of automated/quantitative assessment of protein expression in TMAs , 2008, Histochemistry and Cell Biology.

[21]  M. Heatley,et al.  Keratin expression in human tissues and neoplasms , 2002, Histopathology.

[22]  Savitri Krishnamurthy,et al.  Multi-institutional comparison of whole slide digital imaging and optical microscopy for interpretation of hematoxylin-eosin-stained breast tissue sections. , 2013, Archives of pathology & laboratory medicine.

[23]  J. Kononen,et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens , 1998, Nature Medicine.

[24]  Marylène Lejeune,et al.  Quantification of diverse subcellular immunohistochemical markers with clinicobiological relevancies: validation of a new computer‐assisted image analysis procedure , 2008, Journal of anatomy.

[25]  G. Barkan,et al.  A practical application of quantitative vascular image analysis in breast pathology. , 2013, Pathology, research and practice.

[26]  A. Korzyńska,et al.  Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3’-Diaminobenzidine&Haematoxylin , 2013, Diagnostic Pathology.

[27]  J. Kononen,et al.  A high‐throughput strategy for protein profiling in cell microarrays using automated image analysis , 2007, Proteomics.

[28]  Andrew Lister,et al.  Immunohistochemical prognostic markers in diffuse large B-cell lymphoma: validation of tissue microarray as a prerequisite for broad clinical applications--a study from the Lunenburg Lymphoma Biomarker Consortium. , 2007, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

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

[30]  David G Armstrong,et al.  Reliability and validity of current physical examination techniques of the foot and ankle. , 2008, Journal of the American Podiatric Medical Association.