Hi Emily, You're correct that it's crucial to account for the area differentials between samples when quantifying signal from immunohistochemical (IHC) staining. As you've suggested, one approach to deal with this is to normalize the total signal to the total area of the sample, which essentially gives you an average signal intensity per unit area.

Here is a generalized step-by-step method using ImageJ (Fiji):

Repeat this process for each image, ensuring that you're using consistent settings throughout. By using this method, you're essentially determining the average intensity of the signal per unit area in each section. This can then be compared between sections, even if they are of different sizes. This is a simple and effective way to standardize your measurements across different sections.

Dear Emily Clark In theory you can measure "mean gray value" which is the average intensity per pixel (i.e. raw integrated density (RawIntDen) divided by the number of pixels in selected area, so it accounts for the area in a similar way than u describe (assuming all images are taken at the same scale and settings)). You can also do this manually (measure RawINtDen and area and divide).

In general, you need to define an area of interest that is really relevant for your measurement and to subtract the background level (determine e.g. with a negative control) before the quantification.

For the area of interest, it depends a bit how your signal looks. If it is relatively similarly distributed in the sample, you could define it morphologically e.g. the whole sample and then measuring mean grey value is ok. Otherwise if it is more in patches, you can define it by using a threshold based on the signal. Here you just have to be careful that if you use mean grey value, you only get information about the part in the selection and you loose information about the areas outside the thresholded area, (e.g. if you have a lot of areas with no signal within one sample and a lot in another sample, but similar intensities, they will look the same as the average per selected area is the same). So you could actually measure RawIntDen and later divide it by the entire area of the sample to get this information. The thresholding parameters need to be the same for all images.

I would not recommend ImageJ quantification unless your signal differences are obvious and dramatic. I strongly encourage you to perform a flow cytometry analysis of dissociated tissues or a western blotting analysis of the tumor samples.