EVALUATION OF IMMUNOHISTOCHEMISTRY (IHC) MARKER HER2 IN BREAST CANCER

Abstract
The paper discusses a novel approach involving algorithm implementation and hardware Devkit processing for estimating the extent of cancer in a breast tissue sample. The process aims at providing a reliable, repeatable, and fast method that could replace the traditional method of manual examination and estimation. Immunohistochemistry (IHC) and Fluorescence in situ Hybridization (FISH) are the two main methods used to detect the marker status in clinical practice. FISH is though more reliable than IHC, but IHC is widely used as it is cheaper, convenient to operate and conserve, the morphology is clear. The IHC markers are Estrogen receptor (ER, Progesterone receptor (PR), Human Epidermal Growth Factor (HER2) that give clear indications of the presence of cancer cells in the tissue sample. HER2 remains the most reliable marker for the detection of breast cancer. The Human Epidermal Growth Factor Receptor (HER2) markers are discussed in the paper, as it gives clear indications of the presence of cancer cells in the tissue sample. HER2 is identified based on the color and intensity of the cell membrane staining. The color and intensity is obviously based on the thresholding for classifying the cancerous cells into severity levels in terms of score to estimate the extent of spread of cancer in breast tissue. For HER2 evaluation, the percentage of staining is calculated in terms of ratio of stain pixel count to the total pixel count. The evaluation of HER2 is obtained through simulation software (MATLAB) using intensity based algorithm and same is run on embedded processor evaluation board Devkit 8500. The results are validated with doctors.

Authors
Prasanna G. Shete1, Gajanan K. Kharate2
PVG’s College of Engineering and Technology, India1, Matoshri College of Engineering and Research, India2

Keywords
Breast Cancer, IHC, HSV Model Based, HER2, Intensity Based Membrane Staining
Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 7 , Issue: 1 )
Date of Publication :
August 2016

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