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Quantification of histochemical staining by color deconvolution
1Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston 77030, USA.
Objective:
To develop a flexible method of separation and quantification of immunohistochemical staining by means of color image analysis.
Study Design:
An algorithm was developed to deconvolve the color information acquired with red-green-blue (RGB) cameras and to calculate the contribution of each of the applied stains based on stain-specific RGB absorption. The algorithm was tested using different combinations of diaminobenzidine, hematoxylin and eosin at different staining levels.
Results:
Quantification of the different stains was not significantly influenced by the combination of multiple stains in a single sample. The color deconvolution algorithm resulted in comparable quantification independent of the stain combinations as long as the histochemical procedures did not influence the amount of stain in the sample due to bleaching because of stain solubility and saturation of staining was prevented.
Conclusion:
This image analysis algorithm provides a robust and flexible method for objective immunohistochemical analysis of samples stained with up to three different stains using a laboratory microscope, standard RGB camera setup and the public domain program NIH Image.