Fluorescence intensity on cardiac fibres

Hi there,
I am analyzing cardiac fibres with confocal microcopy. We are marking mitochondria and ROS with different markers on isolated fibres. Normally I just select the area of fibres and measure it to get area, intensity and integrated intensity.
As you see in the picture example, sometimes there are black areas inside the fibre (not those on the right side which are background and will be used for background correction). The picture only shows marked mitochondria.
The question I am asking is, whether or not one should include these holes in the analysis or not.
The first idea I had is to select the black areas and subtract them from the rest of the data.
Or is there a macro which helps to exclude all black areas from sample measuring. For example all black areas which have lower or same intensity as the background values.

Thanks a lot in advance

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That’s up to you :wink:

You can do that or just select the green area.

imageArea - blackArea = greenArea

I can’t tell you which one is simpler to detect without testing.

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I think I have to exclude them because it’s dependent on the individual preparation because these are physical holes.
And for measuring, this seems to be the dos simple approach, as long as there is no existing macro.
Thanks for the answer!

You could also set a threshold (Image > Adjust > Threshold) such that only the fibres are marked as foreground (i.e. they are shown in red). Set the threshold in such a way, that none of the background pixels are marked as foreground.

You then can the use the option Limit to threshold in Analyze > Set Measurements… to make the Measure command only take into account those pixels that are marked as foreground by the threshold.

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Hi all,

I just thought I’d take advantage of this thread to mention a few issues with measurements of intensity involving a threshold on the same channel as the one being measured. And more specifically using automatic thresholds.

@Felix, you are measuring the intensity of the cardiac fibers in order to compare different conditions, I take it. If you select multiple areas by hand, avoiding the holes, and measure them, then this is fine.

However, if you start using an automatic threshold, as suggested by @stelfrich you run the risk of biasing your results in exactly the way that you do not want. In short, auto threshold methods select a threshold based on the distribution of intensities in your image. If the distribution changes, then the threshold will change too. But you should not change the threshold, seeing as your’re changing how you measure each image.

Just like having an actin lane in your western blots, you need something that does not change in your data to measure what is changing accurately. In your case a membrane or cytoplasmic marker that is not affected by your experiments can help you detect the cell area so you can measure your fibers.

I’ve attached a figure to explain what I mean by bias. Thresholds on the same channel as the measured ones will lessen the potential variations you can observe. In this example case, we have DAPI stained cells always present and a GFP signal that is dependent on cell cycle. If I use only the GFP signal, if I select a too high threshold, I lose some cells with low intensities and thus believe my measured signal is higher than it actually is. Converesely if my threshold is too loose, I risk taking in too much background and artificially lower my measured signal.

Using a mask based on the DAPI, I can measure all cells for the green in a much more unbiased way.

Anyway, TL;DR feel free to draw out the regions, or set a hard manual threshold based on negative controls to make sure you are capturing specific signal and not background fluorescence and stick to it. Do not use automated threshold methods to detect AND measure the same thing.

All the best


Yes! Great comment, @oburri

@oburri Thanks! It would be awesome if your writeup here could be added to the Principles wiki page.


You are right, @oburri, in pointing that out. I meant a manual threshold but wasn’t clear about it. Thanks for the additional info! :slight_smile:

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Thanks for the answers. @oburri, I never felt that automated thresholding was the right thing to do because it won’t let me measure intensity differences between the images.
I will go for the manual method, measuring multiple areas and subtract background noise for each image.
Thanks everybody