Dear Amalie, I have no experience with NovaRed. This being said, I see no objection in quantifying its signal the same way as any other HRP substrate.

Some things to consider:

• Peroxidase-developed signals are not linear, so I would suggest you not to quantify in terms of more/less signal than... Instead you could count positive vs negative cells. This has been thoroughly discussed here for DAB and I strongly suggest you to read https://www.researchgate.net/post/How_do_I_conduct_semi_quantification_with_DAB_chromogen_IHC_in_ImageJ and https://www.researchgate.net/post/How_do_I_quantify_DAB_using_ImageJ.
• Assuming you agree to use some of the methods (Mustafa [@Hesham N. Mustafa] or the Positive/Negative I suggested or any other), you will find necessary to segment your image. As your picture shows nicely delineated cells and nuclei are quite evident, I guess you could manage with the segmentation algorithms bundled into ImageJ/FIJI (please see http://imagej.net/Segmentation for a nice introduction).
• As you only have one stain and no metachromasia, I see no point in using colour images. 8-bit or 16-bit grayscale images are better suited for your purposes.

Best,

Daniel

you can rule the deconvolution by selecting the color you want to discriminate

select "From ROI" in the list of the tool and if you check the box show matrix you can reuse your parameters by selecting "user value" in the list for the next analyses.

Hi Amalie,

I would try the following simple procedure:

Send to

J Histochem Cytochem. 1997 Nov;45(11):1559-65.

Application of photoshop-based image analysis to quantification of hormone receptorexpression in breast cancer.

Lehr HA1, Mankoff DA, Corwin D, Santeusanio G, Gown AM.

Author information

Abstract

The benefit of quantifying estrogen receptor (ER) and progesterone receptor (PR) expression in breast cancer is well established. However, in routine breast cancer diagnosis, receptor expression is often quantified in arbitrary scores with high inter- and intraobserver variability. In this study we tested the validity of an image analysis system employing inexpensive, commercially available computer software on a personal computer. In a series of 28 invasive ductal breast cancers, immunohistochemical determinations of ER and PR were performed, along with biochemical analyses on fresh tumor homogenates, by the dextran-coated charcoal technique (DCC) and by enzyme immunoassay (EIA). From each immunohistochemical slide, three representative tumor fields (x20 objective) were captured and digitized with a Macintosh personal computer. Using the tools of Photoshop software, optical density plots of tumor cell nuclei were generated and, after background subtraction, were used as an index of immunostaining intensity. This immunostaining index showed a strong semilogarithmic correlation with biochemical receptor assessments of ER (DCC, r = 0.70, p < 0.001; EIA, r = 0.76, p < 0.001) and even better of PR (DCC, r = 0.86; p < 0.01; EIA, r = 0.80, p < 0.001). A strong linear correlation of ER and PR quantification was also seen between DCC and EIA techniques (ER, r = 0.62, p < 0.001; PR, r = 0.92, p < 0.001). This study demonstrates that a simple, inexpensive, commercially available software program can be accurately applied to the quantification of immunohistochemical hormone receptor studies.

Best regards,

Fred