Abstract
In anatomic pathology, immunohistochemistry (IHC) serves as a diagnostic and prognostic method for identification of disease markers in tissue samples that directly influences classification and grading the disease, influencing patient management. However, till today over most of the world, pathological analysis of tissue samples remained a time-consuming and subjective procedure, wherein the intensity of antibody staining is manually judged and thus scoring decision is directly influenced by visual bias. This instigated us to design a simple method of automated digital IHC image analysis algorithm for an unbiased, quantitative assessment of antibody staining intensity in tissue sections. As a first step, we adopted the spectral deconvolution method of DAB/hematoxylin color spectra by using optimized optical density vectors of the color deconvolution plugin for proper separation of the DAB color spectra. Then the DAB stained image is displayed in a new window wherein it undergoes pixel-by-pixel analysis, and displays the full profile along with its scoring decision. Based on the mathematical formula conceptualized, the algorithm is thoroughly tested by analyzing scores assigned to thousands (n = 1703) of DAB stained IHC images including sample images taken from human protein atlas web resource. The IHC Profiler plugin developed is compatible with the open resource digital image analysis software, ImageJ, which creates a pixel-by-pixel analysis profile of a digital IHC image and further assigns a score in a four tier system. A comparison study between manual pathological analysis and IHC Profiler resolved in a match of 88.6% (P<0.0001, CI = 95%). This new tool developed for clinical histopathological sample analysis can be adopted globally for scoring most protein targets where the marker protein expression is of cytoplasmic and/or nuclear type. We foresee that this method will minimize the problem of inter-observer variations across labs and further help in worldwide patient stratification potentially benefitting various multinational clinical trial initiatives.
Highlights
Identification of various marker proteins in human tissue sample has been an important prerequisite in the clinical management of various diseases including cancer
Keeping in view the above mentioned limitations of various analytical methods, we report here, the development of an open source plugin named IHC Profiler, which is compatible with the ImageJ software and demonstrate the method for IHC analysis using color deconvolution and computerized pixel profiling leading to the assignment of an automated score to the respective image
The images produced upon color deconvolution by the new optical density (OD) vectors are represented in the figure (Figure 1B)
Summary
Identification of various marker proteins in human tissue sample has been an important prerequisite in the clinical management of various diseases including cancer. Staining of various marker proteins located either in the cell nuclei, cytoplasm or membrane are often considered as pathological determinants for classifying and grading the disease. For identifying the presence and the extent of expression of such proteins, qualitative assessments is commonly done following techniques such as immunohistochemistry (IHC), immunocytochemistry (ICC) and immunofluorescence (IF) [1]. The basic underlying principle of these techniques is the staining of the biopsy tissue samples with antibodies specific to the molecular marker of interest. In IHC method, visualization of the antibody-antigen reaction is accomplished by the use of a secondary antibody conjugated to an enzyme, such as peroxidase, which catalyses a brown color-producing reaction. The processed sample slides are generally judged under a light microscope by a trained pathologist to assign a score based on the visual parameters set
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
