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Decision Support & AI

ER

The estrogen receptor (ER) is a predictive and prognostic tumor marker for patients with breast cancer. ER is a nuclear transcription factor that, when activated by the hormone estrogen, stimulates the growth of normal breast epithelial cells [1]. This stimulation mechanism can also act on tumor cells. In the treatment of breast cancer, ER-positive patients have been shown to respond better to chemotherapy and hormone therapy. Therefore, ER status is considered one of the strongest predictive markers in breast cancer management. ER positivity is evaluated with immunohistochemistry technique. ER has a nuclear staining pattern that shows weak, medium and dark staining intensity in microscopic evaluation. In the assessment of ER positivity, the ratio of the positive stained tumor cells to all tumor cells is calculated [2].

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Keywords

Estrogen Receptor,Hormone Therapy, Image Analysis, Breast Cancer.

Methods

The techniques of nuclear classification algorithm is used to detect the nuclei in morphological form and size and classify them as positive or negative according to pixel colorization and intensity. Also, tile extraction, color deconvolution, morphological filters, threshold value method,and cell segmentation algorithms are used to develop ER analysis. The analysis algorithm contains H-DAB colour deconvolution method. To detect negative nuclei H channel, and to detect and classify brown nuclei DAB channel are used. The positive nuclei are classified into three groups according to given threshold values by the user before running the analysis.

Quantitative output variables
  • H-Score
  • Dark Brown Nuclei Number
  • Medium Brown Nuclei Number
  • Light Brown Nuclei Number
  • Blue Nuclei Number
  • Stroma Nuclei Number 
  • ER Positivity 
Workflow
  1. View the ER whole slide digital image with ViraPath.
  2. Outline tumor either manually or automatically using Virapath Tissue Segmentation algorithm 
  3. Select ER analysis and calibrate the parameters.
  4. Run the analysis
References

[1]Sunil R. Lakhani, Ian O. Ellis, Stuart J. Schnitt, Puay Hoon Tan, Marc J. van de Vijver (Ed.). (2012). WHO Classification of Tumours of the Breast (4th ed.) International Agency for Research on Cancer (IARC), Lyon, France: pp 22-23.

[2]Hammond, M. E. H., Hayes, D. F., Dowsett, M., Allred, D. C., Hagerty, K. L., Badve, S., ... & Hicks, D. G. (2010). American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer (unabridged version). Archives of pathology & laboratory medicine, 134(7), e48-e72.

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