Abstract
BackgroundRecent technical advances in digital image capture and analysis greatly improve the measurement of protein expression in tissues. Breast cancer biomarkers provide a unique opportunity to utilize digital image analysis to evaluate sources of variability that are caused by the tissue preparation, in particular the decalcification treatment associated with the analysis of bone metastatic breast cancer, and to develop methods for comparison of digital data and categorical scores rendered by pathologists.MethodsTissues were prospectively decalcified for up to 24 hours and stained by immunohistochemistry (IHC) for ER, PR, Ki-67 and p53. HER2 positive breast cancer sections were retrieved from the pathology archives, and annotated with the categorical HER2 expression scores from the pathology reports. Digital images were captured with Leica and Aperio slide scanners. The conversion of the digital to categorical scores was accomplished with a Gaussian mixture model and tested for accuracy by comparison to clinical scores.ResultsWe observe significant effects of the decalcification treatment on common breast cancer biomarkers that are used in the clinic. ER, PR and p53 staining intensities decreased 15 – 20%, whereas Ki-67 decreased > 90% during the first 6 hrs of treatment and stabilized thereafter. In comparison with the Aperio images, pixel intensities generated by the Leica system are lower. A novel statistical model for conversion of digital to categorical scores provides a systematic approach for conversion of nuclear and membrane stains and demonstrated a high concordance with clinical scores.ConclusionDigital image analysis greatly improves the quantification of protein expression in human tissues. Decalcification affects the accuracy of immunohistochemical staining results and cannot be reversed by image analysis. Measurement data obtained on a continuous scoring scale can be converted to categorical scores for comparison with categorical dataset that are generated by pathologists.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_213Electronic supplementary materialThe online version of this article (doi:10.1186/s13000-014-0213-9) contains supplementary material, which is available to authorized users.
Highlights
Recent technical advances in digital image capture and analysis greatly improve the measurement of protein expression in tissues
We demonstrate a statistical approach to convert the staining intensity that is measured by the instrument into a categorical score that is familiar to pathologists and researchers reporting protein expression in tissues
Since bone biopsies are decalcified prior to immunohistochemical staining to prepare the bone for the generation of micro thin sections, the validity of biomarker measurements is endangered by the decalcification treatment
Summary
Recent technical advances in digital image capture and analysis greatly improve the measurement of protein expression in tissues. A computer-assisted approach has advantages compared to the conventional, visual assessment of staining intensities in terms of quantification, dynamic range, reproducibility and sensitivity [1,2]. We demonstrate a statistical approach to convert the staining intensity that is measured by the instrument into a categorical score that is familiar to pathologists and researchers reporting protein expression in tissues. There is a need to seek computer assistance to improve the accuracy and reproducibility of IHC- based measurements and to establish a systematic approach for converting digital into visual, categorical scales that are used by pathologists
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