Software based analyses of immunohistochemical staining are designed for obtaining quantitative, reproducible, and objective data. However, often times only a certain type of positive cells or structures need to be quantified thus whole image analysis cannot be performed. Such an example is Hofbauer placental cells, which show positivity of some antigens together with trophoblast, but only Hofbauer cells represent the regions of interest (ROIs). Two independent observers evaluated the immunohistochemical staining intensity of Hofbauer cells in placenta samples stained for cytoplasmic antigens by ImageJ, QuPath and light microscopy. Thus, the precise manual determination of ROIs, i.e. Hofbauer cells, was necessary. We detected low inter-observer variability in staining intensity. Almost perfect agreement between observers was reached for ImageJ and QuPath whilst substantial agreement was reached for light microscopy evaluation. As for the comparison of ImageJ, QuPath and light microscopy, the agreement of all three methods (identical immunohistochemical intensity) was achieved for 38.1% samples. The almost perfect agreement of staining intensities was reached between ImageJ and QuPath, and moderate agreement for comparison of the light microscopy to both software. Software analyses are much more time-consuming, thus their utilization is at least questionable to evaluate ROIs with selection.

Department of Clinical and Molecular Pathology and Laboratory of Molecular Pathology Faculty of Medicine and Dentistry Palacky University 779 00 Olomouc Czech Republic

Department of Histology and Embryology Faculty of Medicine and Dentistry Palacky University 779 00 Olomouc Czech Republic

See more in PubMed

Aeffner, F., Wilson, K., Martin, N. T., Black, J. C., Hendriks, C. L. L., Bolon, B., et al. (2017) The Gold Standard Paradox in Digital Image Analysis: Manual Versus Automated Scoring as Ground Truth. Arch. Pathol. Lab. Med. 141; 1267–1275. PubMed

Aeffner, F., Zarella, M. D., Buchbinder, N., Bui, M. M., Goodman, M. R., Hartman, D. J., et al. (2019) Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association. J. Pathol. Inform. 10; 9–9. PubMed PMC

Bankhead, P., Loughrey, M. B., Fernández, J. A., Dombrowski, Y., McArt, D. G., Dunne, P. D., et al. (2017) QuPath: Open source software for digital pathology image analysis. Sci. Rep. 7; 16878. PubMed PMC

Bankhead, P., Fernández, J. A., McArt, D. G., Boyle, D. P., Li, G., Loughrey, M. B., et al. (2018) Integrated tumor identification and automated scoring minimizes pathologist involvement and provides new insights to key biomarkers in breast cancer. Lab. Invest. 98; 15–26. PubMed

Bellemare, J., Rouleau, M., Harvey, M., Popa, I., Pelletier, G., Têtu, B., et al. (2011) Immunohistochemical expression of conjugating UGT1A-derived isoforms in normal and tumoral drug-metabolizing tissues in humans. J. Pathol. 223; 425–435. PubMed

Conway, C., Dobson, L., O’Grady, A., Kay, E., Costello, S. and O’Shea, D. (2008) Virtual microscopy as an enabler of automated/quantitative assessment of protein expression in TMAs. Histochem. Cell Biol. 130; 447–463. PubMed

Fedchenko, N. and Reifenrath, J. (2014) Different approaches for interpretation and reporting of immunohistochemistry analysis results in the bone tissue—a review. Diagn. Pathol. 9; 221. PubMed PMC

Fiore, C., Bailey, D., Conlon, N., Wu, X., Martin, N., Fiorentino, M., et al. (2012) Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry. J. Clin. Pathol. 65; 496–502. PubMed PMC

Jaraj, S. J., Camparo, P., Boyle, H., Germain, F., Nilsson, B., Petersson, F., et al. (2009) Intra- and interobserver reproducibility of interpretation of immunohistochemical stains of prostate cancer. Virchows Arch. 455; 375–381. PubMed

Loughrey, M. B., Bankhead, P., Coleman, H. G., Hagan, R. S., Craig, S., McCorry, A. M. B., et al. (2018) Validation of the systematic scoring of immunohistochemically stained tumour tissue microarrays using QuPath digital image analysis. Histopathology 73; 327–338. PubMed

Mane, D. R., Kale, A. D. and Belaldavar, C. (2017) Validation of immunoexpression of tenascin-C in oral precancerous and cancerous tissues using ImageJ analysis with novel immunohistochemistry profiler plugin: An immunohistochemical quantitative analysis. J. Oral Maxillofac. Pathol. 21; 211–217. PubMed PMC

Melo, R. C. N., Raas, M. W. D., Palazzi, C., Neves, V. H., Malta, K. K. and Silva, T. P. (2020) Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders. Front. Med. (Lausanne) 6; 310–310. PubMed PMC

Nguyen, D. (2013) Quantifying chromogen intensity in immunohistochemistry via reciprocal intensity. Cancer InCytes 2(1): e.

Ogbureke, K. U. E. and Fisher, L. W. (2005) Renal expression of SIBLING proteins and their partner matrix metalloproteinases (MMPs). Kidney Int. 68; 155–166. PubMed

O’Hurley, G., Sjöstedt, E., Rahman, A., Li, B., Kampf, C., Pontén, F., et al. (2014) Garbage in, garbage out: a critical evaluation of strategies used for validation of immunohistochemical biomarkers. Mol. Oncol. 8; 783–798. PubMed PMC

Ong, C. W., Kim, L. G., Kong, H. H., Low, L. Y., Wang, T. T., Supriya, S., et al. (2010) Computer-assisted pathological immunohistochemistry scoring is more time-effective than conventional scoring, but provides no analytical advantage. Histopathology 56; 523–529. PubMed

Rimm, D. L. (2006) What brown cannot do for you. Nat. Biotechnol. 24; 914–916. PubMed

Rizzardi, A. E., Johnson, A. T., Vogel, R. I., Pambuccian, S. E., Henriksen, J., Skubitz, A. P., et al. (2012) Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring. Diagn. Pathol. 7; 42. PubMed PMC

Tong, G.-X., Yu, W. M., Beaubier, N. T., Weeden, E. M., Hamele-Bena, D., Mansukhani, M. M., et al. (2009) Expression of PAX8 in normal and neoplastic renal tissues: an immunohistochemical study. Mod. Pathol. 22; 1218–1227. PubMed

van Raaij, S., van Swelm, R., Bouman, K., Cliteur, M., van den Heuvel, M. C., Pertijs, J., et al. (2018) Tubular iron deposition and iron handling proteins in human healthy kidney and chronic kidney disease. Sci. Rep. 8; 9353. PubMed PMC

Varghese, F., Bukhari, A. B., Malhotra, R. and De, A. (2014) IHC Profiler: an open source plugin for the quantitative evaluation and automated scoring of immunohistochemistry images of human tissue samples. PLoS One 9; e96801. PubMed PMC

Weaver, D. L., Krag, D. N., Manna, E. A., Ashikaga, T., Harlow, S. P. and Bauer, K. D. (2003) Comparison of pathologist-detected and automated computer-assisted image analysis detected sentinel lymph node micrometastases in breast cancer. Mod. Pathol. 16; 1159–1163. PubMed

Synthetic Pyridoindole and Rutin Affect Upregulation of Endothelial Nitric Oxide Synthase and Heart Function in Rats Fed a High-Fat-Fructose Diet