A Novel Image Cytometric Method for Quantitation of Immunohistochemical Staining of Cytoplasmic Antigens

Evaluation of molecular markers by immunohistochemical labelling of tissue sections has traditionally been performed by qualitative assessment by trained pathologists. For those markers with a staining component present outside of the nucleus, there has been no image histometric method available to reliably and consistently define cell interfaces within the tissue. We present a new method of approximating cellular boundaries to define cellular regions within which quantitative measurements of staining intensity may be made. The method is based upon Voronoi tessellation of a defined region of interest (ROI), and requires only the position of the nuclear centroids within the ROI. Here we describe the VORSTAIN software which has been developed based on the Oncometrics CytoSavant Automated Image Cytometry System. To demonstrate this technique, human breast cancer sections immunohistochemically stained for bcl‐2 protein and counter‐stained with nuclear methyl green stain were evaluated. Intra‐observer variation in the measured values was between 1.5–2.6% and inter‐observer variation was between 1.8–4.4%. The primary source of variability was due to difficulties in interpreting the exact position of the nuclear centroids. Analysis of mean staining densities for each slide correlated well with subjective scoring performed by two independent pathologists. Using VORSTAIN, significant variation of staining intensities between regions within the same slide was measured for some sections, indicating a large degree of heterogeneity within the tumours. The ability to accurately quantitate the degree of heterogeneity of molecular marker expression within tumours may be a valuable tool in prognostication.

[1]  D. C. Aziz,et al.  Quantitation and morphometric analysis of tumors by image analysis. , 1994, Journal of cellular biochemistry. Supplement.

[2]  S. M. Crawford,et al.  TUMOUR MARKERS , 1986, The Lancet.

[3]  Prognostic value of estrogen and progesterone receptors in operable breast cancer: Results of a univariate and multivariate analysis , 1988, Cancer.

[4]  J. Baak,et al.  Quantitative immunohistochemistry using the CAS 200/486 image analysis system in invasive breast carcinoma: a reproducibility study. , 1995, Analytical cellular pathology : the journal of the European Society for Analytical Cellular Pathology.

[5]  G. Sledge Implications of the new biology for therapy in breast cancer. , 1996, Seminars in oncology.

[6]  Adrian Bowyer,et al.  Computing Dirichlet Tessellations , 1981, Comput. J..

[7]  R. Gascoyne,et al.  Immunohistochemical analysis of Mcl-1 and Bcl-2 proteins in normal and neoplastic lymph nodes. , 1994, The American journal of pathology.

[8]  R. Marcelpoil,et al.  Methods for the study of cellular sociology: Voronoi diagrams and parametrization of the spatial relationships , 1992 .

[9]  G Brugal,et al.  Cellular sociology applied to neuroendocrine tumors of the lung: quantitative model of neoplastic architecture. , 1996, Cytometry.

[10]  P. V. van Diest,et al.  Quantitation of HER-2/neu oncoprotein overexpression in invasive breast cancer by image analysis: a study comparing fresh and paraffin-embedded material. , 1991, Analytical cellular pathology : the journal of the European Society for Analytical Cellular Pathology.

[11]  J. Bacus,et al.  HER-2/neu oncogene expression and DNA ploidy analysis in breast cancer. , 1990, Archives of pathology & laboratory medicine.

[12]  R. Chandebois,et al.  Cell sociology: A way of reconsidering the current concepts of morphogenesis , 1976, Acta biotheoretica.

[13]  V. Kosma,et al.  Expression of c-myc proteins in breast cancer as related to established prognostic factors and survival. , 1995, Anticancer research.

[14]  D. Crawford,et al.  Tumor markers. An update. , 1996, The Medical clinics of North America.

[15]  D. Johnston,et al.  Comparison of visual and CAS-200 quantitation of immunocytochemical staining in breast carcinoma samples. , 1992, Analytical and quantitative cytology and histology.

[16]  J. Bacus,et al.  The evaluation of estrogen receptor in primary breast carcinoma by computer-assisted image analysis. , 1988, American journal of clinical pathology.

[17]  Franz Aurenhammer,et al.  Voronoi diagrams—a survey of a fundamental geometric data structure , 1991, CSUR.

[18]  W. McGuire,et al.  Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. , 1987, Science.

[19]  W. Jonat,et al.  The problem of nonresponding estrogen receptor‐positive patients with advanced breast cancer , 1980, Cancer.

[20]  Aziz Dc,et al.  Quantitation and morphometric analysis of tumors by image analysis. , 1994 .

[21]  R. Gascoyne,et al.  Short Communication Immunohistochemical Analysis of Mci-1 Protein in Human Tissues Differential Regulation of Mcl- 1 and Bcl-2 Protein Production Suggests a Unique Role for Mcl- 1 in Control of Programmed Cell Death In Vivo , 2007 .

[22]  Franz Aurenhammer,et al.  Power Diagrams: Properties, Algorithms and Applications , 1987, SIAM J. Comput..