Complete Chromogen Separation and Analysis in Double Immunohistochemical Stains Using Photoshop-based Image Analysis

Abstract

SUMMARYSimultaneous detection of two different antigens on paraffin-embedded and frozen tissues can be accomplished by double immunohistochemistry. However, many double chromogen systems suffer from signal overlap, precluding definite signal quantification. To separate and quantitatively analyze the different chromogens, we imported images into a Macintosh computer using a CCD camera attached to a diagnostic microscope and used Photoshop software for the recognition, selection, and separation of colors. We show here that Photoshop-based image analysis allows complete separation of chromogens not only on the basis of their RGB spectral characteristics, but also on the basis of information concerning saturation, hue, and luminosity intrinsic to the digitized images. We demonstrate that Photoshop-based image analysis provides superior results compared to color separation using bandpass filters. Quantification of the individual chromogens is then provided by Photoshop using the Histogram command, which supplies information on the luminosity (corresponding to gray levels of black-and-white images) and on the number of pixels as a measure of spatial distribution. (J Histochem Cytochem 47:119-125, 1999)

Carbonic Anhydrase IX is Not a Predictor of Outcomes in Non-Metastatic Clear Cell Renal Cell Carcinoma - A Digital Analysis of Tissue Microarray

“…The color of interest can be objectively measured in its red/green/blue components (RGB) using the histogram (16,17). Adobe Photoshop® is a widely available, low cost software, and its use makes this technology available and reproducible to other centers (16,17,(25)(26)(27).…”

“…Adobe Photoshop® is a widely available, low cost software, and its use makes this technology available and reproducible to other centers (16,17,(25)(26)(27). The gene that codifies CA-IX is regulated by HIF-1α expression, and HIF-1α is controlled by the VHL protein.…”

“…The technique consists in counting the pixels of the brown color of interest, in an area measurement, adapted from Lehr et al (16,17).…”

An image analysis‐based approach for automated counting of cancer cell nuclei in tissue sections

“…The proposed PCA-based algorithm was compared with five common threshold selection techniques that have been used widely by many researchers for similar cell segmentation purposes (5,32,33), since they hold the advantage of being fast and simple to implement, as discussed by others (6). These thresholding techniques were: method A, iterative selection (24); method B, entropic thresholding (22); method C, Otsu's method (23); and method D, fuzzy sets (21).…”

“…Semiautomated systems have been developed to count pixels in spatial regions specified by the user (4), or within thresholds set interactively (5), while other investigators have experimented in the color domain (6). More sophisticated approaches have used multistage segmentation based on statistical models, and exhibited their potential to overcome many of the limitations of previously existing methods, but these were demonstrated in small-scale images containing fairly circular and uniformly stained nuclei (7).…”