Computer-aided techniques for chromogenic immunohistochemistry: Status and directions

doi:10.1016/j.compbiomed.2012.08.004

Computers in Biology and Medicine

Volume 42, Issue 10, October 2012, Pages 1012-1025

https://doi.org/10.1016/j.compbiomed.2012.08.004 Get rights and content

Abstract

Although immunohistochemistry (IHC) is a popular imaging technique, the quantitative analysis of IHC images via computer-aided methods is an emerging field that is gaining more and more importance thanks to the new developments in digital high-throughput scanners. In this paper, we discuss the main steps of IHC and review the techniques for computer-aided chromogenic IHC analysis, including methods to determine the location of interest of the antigens and quantify their activations. Moreover, we discuss the issues arising from the standardization of the immunostaining process, that are generally overlooked by the current literature, and finally provide requirements for reliable computer-aided IHC quantification.

Introduction

The continuous developments in bioimaging technologies (especially microscopy) have established the ultimate proliferation of computer-aided biological imaging techniques as an effective way of extracting clinical and functional information from molecules and tissues [1], [2]. Pathologists are relying more and more on microscopy image analysis to assess the presence and activity of target antigens in the tissues, with important applications in the diagnosis and assessment of tumors as well as for several research purposes.

The analysis in situ of the activation of specific proteins provides critical information about multi-factorial genetic pathologies and tumors [3], [4], supports the design of personalized targeted therapies [5], allows to define a group of potential candidates to protein family-inhibiting therapies [3], [6], [7].

One of the most popular imaging techniques in this field is immunohistochemistry (IHC), that uses marked antibodies to link specific proteins in situ, as well as their ligands; the evaluation of the coloured stains at the specific sub-cellular regions where the markers are localized (i.e. nucleus, cellular membrane, cytoplasm) provides information about the presence and the activation of the target proteins in the tissue, and therefore it is useful for the assessment of important pathologies [3], [4]. Immunohistochemistry is widely used in clinical and research laboratories since the early seventies for the qualitative assessment of the tissue specimens, and it has acquired a central role in pathology thanks to its wide availability, low cost, easy and long preservation of the stained slides [8]. In the last few years, with the continuing developments in digital, high-throughput tissue slide scanners, IHC is gaining more and more importance as a technique able to provide not just qualitative but also semi-quantitative or quantitative measurements of protein activations. Nevertheless, this shift from qualitative to quantitative raises a lot of issues about the robustness of the IHC assay; moreover, the reliability of the results obtained through visual evaluation of the specimens, inherently subjective, is heavily questioned [9].

The automation of the image analysis task through computer-aided techniques is acknowledged for being a possible solution towards the standardization of the IHC test and the extraction of reliable quantitative measurements of protein activation [10], [11], [12]. On top of that, the new demands of modern pathology and personalized medicine require precise and highly localized measures of protein activations, at cellular and sub-cellular level [11], which is not feasible with simple visual evaluation. This has determined a growing effort in the development of automated techniques for the segmentation and the analysis of IHC tissue images, able to recognize and measure the antigens' activations within their specific regions of interest [13].

Different tissue images associated with different diseases may exhibit unique characteristics, both in terms of tissue morphology and evaluation procedure, demanding specific image analysis pipeline. However, several image analysis components remain common in most of the applications, so that it is possible to identify a typical work-flow for computer-aided IHC analysis. This work-flow contains sequential segmentation steps with the aim of identifying the specific regions of interest of the studied antigens, followed by the quantification of the antigens'activation.

After introducing the background of digital pathology and immunohistochemical analysis, in this paper we provide a critical overview of the image analysis techniques applied to the main steps of IHC, analysing potentials and limitations of the different approaches, and we discuss the open challenges for a standardized quantification of protein expression.

Section snippets

Digital microscopy image analysis

Digital microscopy is the effective integration of digital imaging and light microscopy, where a comprehensive platform combining optical, electronic, mechanical, image processing and computer technologies assists the pathologist in acquiring, observing, analysing and sharing pathology image data in digital form [14]. In the past few years, the digital revolution in the field of bioimaging has rapidly transformed the work of the pathologists, traditionally limited to the microscopic observation

Immunohistochemistry: fundamentals

Immunohistochemistry (or IHC) is a widespread procedure in digital pathology that refers to the process of localizing antigens (e.g. proteins) in the tissue; the localization is obtained exploiting the principle of antibodies binding specifically to antigens [20]: the tissue is stained with the labeled antibodies that selectively bind to the antigens under investigation.

Immunohistochemical staining is widely used in the diagnosis of abnormal cells such as those found in tumors. Specific

The standardization issue and the role of automated image analysis

The need for standardization in IHC has been stressed as a major critical issue since the late 1970s. In fact for a long time this widespread technique, despite being extensively used for either diagnostic and research purposes, has been relegated to a secondary role because of the extreme variability of the results. This variability covers all the aspects of the assay, from sample preparation to image analysis.

The most important contributions to IHC standardization come from the works of Clive

Computer aided IHC analysis

With the growing awareness that computer-assisted technologies are the best solution to reduce the variability of pathologists evaluation and provide highly specific per-cell information, the market nowadays provides a good number of image analysis systems for IHC. The availability of such systems in pathology laboratories, very limited at the beginning due to high costs of acquisition and maintenance, is now starting to become wider especially in the US thanks to the intervention of medical

Separation of label contributions

The first step after image acquisition and digitalization is the separation of the contributions of the different labels (see Fig. 3). In this phase the contributions of the main chromogen (labelling the test antigen) and of the counter stain are distinguished so that their specific information can be processed separately.

Specific spectral deconvolution and unmixing approaches are applied in case of multispectral microscopy images [17], [13]. Multispectral imaging is an advanced imaging

Selection of the location of the target antigen

Several segmentation and image classification techniques are applied to the aim of selecting regions of interest in the images, depending on the specific tissue or cell locations targeted by the studied antigens (see Fig. 3). These techniques can be categorized based on the anatomical region of interest they are target at. Tissue compartmentalization is generally aimed at classifying the specimen into two or more broad tissue areas, while cell segmentation techniques identify the main

IHC quantification and semi-quantification

The final step of the IHC workflow is the quantification of the activation of the target antigens (see Fig. 3).

As we anticipated in Section 3, the immunohistochemical test has traditionally been qualitative, consisting in simple observation of the presence and darkness of specific stains within the tissue. However, the rapid evolution of the technique as a valid diagnostic and prognostic tool for tumor marker identification and cancer assessment has rapidly shifted the aim of the IHC test from

Recommendations for reliable automated quantitative IHC

The opinions about the feasibility of a full standardization of IHC is still controversial, because of the many variables that need to be controlled. However, in the last few years there have been extensive efforts towards the solution of the problem. We here try to summarize the main points and provide a few recommendations in this sense.

First of all, a profound re-education of the laboratories and pathologists performing the IHC analysis is needed. In fact, in spite of the remarkable

Conclusions

In the last few years biologists and pathologists are relying more and more on image analysis, and immunohistochemistry (IHC) is nowadays one of the most popular imaging techniques to analyse the presence and activity of target antigens in the tissues, with important applications in the diagnosis and assessment of tumors as well as for several research purposes. However, immunohistochemistry has been traditionally affected by lack of reproducibility due to technological variabilities as well as

Summary

Although chromogenic immunohistochemistry (IHC) is a popular imaging technique in clinical and research laboratories, the quantitative analysis of IHC images is still an emerging field, that is gaining more and more importance thanks to the new developments in digital high-throughput tissue slide scanners.

The recent shift to quantitative immunohistochemistry raises a lot of issues about the robustness of the technique and questions heavily the repeatability of the results obtained through

Conflict of interest statement

None declared.

Acknowledgements

The authors acknowledge Dr. Marco Volante and his collaborators of Hospital S. Luigi of Orbassano, Torino, Italy for the helpful discussion.

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Computer-aided techniques for chromogenic immunohistochemistry: Status and directions

Abstract

Introduction

Section snippets

Digital microscopy image analysis

Immunohistochemistry: fundamentals

The standardization issue and the role of automated image analysis

Computer aided IHC analysis

Separation of label contributions

Selection of the location of the target antigen

IHC quantification and semi-quantification

Recommendations for reliable automated quantitative IHC

Conclusions

Summary

Conflict of interest statement

Acknowledgements

Comput. Math. Appl.

J. Pathol. Inf.

Computerized Med. Imaging Graphics

Computer Methods Programs Biomedicine

J. Neurosci. Methods

Pattern Recognition

Computer Methods Programs Biomedicine

Signal Process.

Pattern Recognition

Pattern Recognition

The colored revolution of bioimaging

IEEE Signal Process. Mag.

Markers of small cell lung cancer

World Journal of Surgical Oncology

Antibody-based proteomicsfast-tracking molecular diagnostics in oncology

Nat. Rev. Cancer

Digital pathology in personalized cancer therapy

Folia Histochem. Cytobiologica

Molecular profiling using immunohistochemistry (ihc) and dna microarray (dma) as a tool to determine potential therapeutic targets in patients who have progressed on multiple prior therapies

AACR Meet. Abstr.

Automated analysis of FISH and immunohistochemistry imagesa review

Cytometry. Part AJ. Int. Soc. Anal. Cytol.

High inter-observer agreement in immunohistochemical evaluation of her-2/neu expression in breast cancera multicentre gefpics study

Eur. J. Cancer

Immunohistochemistry and quantitative analysis of protein expression

Arch. Pathol. Lab. Med.

Quantification of immunohistochemistry—issues concerning methods, utility and semiquantitative assessment II

Histopathology

Image analysis as an adjunct to manual HER-2 immunohistochemical reviewa diagnostic tool to standardize interpretation

Histopathology

Cell-based quantification of molecular biomarkers in histopathology specimens

Histopathology

Digital microscopy imaging and new approaches in toxicologic pathology

Toxicol. Pathol.

Histopathological image analysisa review

IEEE Rev. Biomed. Eng.

Histology image analysis for carcinoma detection and grading

Computer Methods Programs Biomedicine

Technical aspects of immunohistochemistry

Vet. Pathol.

Practical aspects of immunomicroscopy on plant material

Mod. Res. Educ. Top. Microsc.

Optical disector counting in cryosections and vibratome sections underestimates particle numberseffects of tissue quality

Microsc. Res. Tech.

Optical projection tomography as a tool for 3D microscopy and gene expression studies

Science

Scalea chemical approach for fluorescence imaging and reconstruction of transparent mouse brain

Nat. Neurosci.

Review of imaging solutions for integrated quantitative immunohistochemistry in the pathology daily practice

Folia Histochem. Cytobiologica Pol. Acad. Sci. Pol. Histochem. Cytochem. Soc.

Quality assurance and standardization in immunohistochemistry. A proposal for the annual meeting of the biological stain commission, June 1991

Biotech. Histochem.

Standardization of immunohistochemistry for formalin-fixed, paraffin-embedded tissue sections based on the antigen-retrieval techniquefrom experiments to hypothesis

J. Histochem. Cytochem.

Use of cultured cells as a control for quantitative immunocytochemical analysis of estrogen receptor in breast cancer the quicgel method

Am. J. Clin. Pathol.

A novel quality control slide for quantitative immunohistochemistry testing

J. Histochem. Cytochem.

Protein-embedding techniquea potential approach to standardization of immunohistochemistry for formalin-fixed, paraffin-embedded tissue sections

J. Histochem. Cytochem.

Quantitation in immunohistologyfact or fiction? A discussion of variables that influence results

Appl.Immunohistochem. Mol. Morphol.

Mouse spleen tissue as a staining intensity reference for immunohistochemistry

Ann. Clin. Lab. Sci.

virtual flow cytometry of immunostained lymphocytes on microscopic tissue slidesihcflow^TM tissue cytometry