Posted by
spetry on
Sep 13, 2012; 11:56am
URL: http://imagej.273.s1.nabble.com/Fluorescence-intensity-analysis-with-tissues-tp5000037p5000059.html
Hi,
first of all let me thank both of you for your input.
Sean Burke wrote
[..]
Have you thought about exporting to FCS Express Image Cytometry for analysis of the segmented data.
[..]
I will have a look at FCS Express, thanks for the link.
Olivier Burri wrote
[..]
From what you say in 3) you seem to have a very large difference
between your two conditions, so this should be doable. Some
considerations though.
1) How many different replicates do you have? (Of the same animal, of
other animals prepared in another batch). Ideally I think it would be
good if you assessed the variability within the same animal and the
variability between animals for both your WT and "treated" conditions.
That way, hopefully the difference you find between the conditions
will be larger than the uncertainty and you can be safer in your
interpretations.
2) Did you perform your stainings in batch, so as to minimize
variabiliy coming from the staining protocol?
[..]
Maybe some more information here which I forgot to mention, sorry.
Basically, I am interested in Insulin and two different antioxidant enzymes.
I stained in two batches, respectively to the latter two. Insulin was stained in both batches in order to be able to clearly identify the islets of Langerhans. Also, nucelus staining was done with Hoechst 33342.
The experiment includes two groups of mice with three corresponding time points each. I stained two sections from three mice each for each group and time point in order to have a good and statistically trustworthy average.
Most important, the huge difference in intensity appears between the two different enzyme stainings. Those do not have to be comparable, so I suppose my worries about the difference are softened.
Olivier Burri wrote
[..]
Usually when you normalize with the area it's to get a density
measurement, and is part of a different type of experiment where you
find your cell area (threshold) and you normalize that with the tissue
area to estimate the density of your sample. I am not sure about
measuring intensities inside cells (Using a threshold I guess) and
then normalizing the intensities. You'd get something like Pixel
Intensities / um2 which doesn't mean much more than just average
intensity...
When you normalize intensity measurements, you do it as ratios of
signals coming from within your own sample, like when you check for
the presence of actin on Western blots. Do you have some marker you
could use as an internal control? Some cytoplasmic marker for example,
that should be homogeneous no matter the condition, that would allow
for normalizing your signal to this one. It can also be a good
indicator that the staining protocol happened correctly.
As mentioned above I also stained nuclei. Maybe I can normalise the other stainings with pictures taken with the respective filter, for those should be stained equally. I think I will try this approach. Taking several images from random positions on every mouse / timepoint / group and calculating the average might be a good start!
I will study the density issue further, but for I am measuring the intensity in the whole islet area and not in single cells using the area does not seem like a reasonable approach. I tried to divide the measured intensities by the mean islet area, but that also seems not reasonable to me now.
Olivier Burri wrote
A way we try it out here is to test out all the available automatic
thresholds available on Fiji/ImageJ using a macro. First the user sets
the threshold manually on a set of images (about 10 or more). Then the
plugin launches the auto-threshold methods on the images and recovers
their values. Then the plugin compares your values to the ones that
were automatically selected and recommends a threshold and a
correction factor that could be used (Something that is done in Cell
Profiler, for example).
However thresholds are usually not set on the data you want to measure
but on some other channel that acts as a mask to your data. Something
that only stains the tissue or cells that you are interested in.
[..]
Hope that's a bit of inspiration. If you'd like the little macro I was
mentioning, let me know. I'd have to comment it a bit to make it
useable but would be happy to share it.
My thoughts about thresholds were based on the idea of further reducing background / low and high peeks in staining, but your point seems logic to me. If you don't mind I would like to try out the macro of yours anyway, just to see how the data behave.
Thank you very much for your detailed answer, I appreciate it a lot!