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Author Topic: Quanitification of IHC images  (Read 1927 times)

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Offline GAnthoni

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Quanitification of IHC images
« on: May 17, 2017, 03:34:21 PM »
Hey team, hoping for some help here.
The images look great, but I'm running into a roadblock for quantification of neurites in hippocampus, any suggestions?
Details: I have several coronal rat brain slices (50um thick) which have three abs on them (primaries added as a cocktail, anti- TH, p-75, and ChAT) HRP- conjugated secondaries added individually and washed (anti- mouse, goat, and rabbit) each with an amplification step (TSA --> FITC, TRITC, and Coumarin) [these are super old animals]. I used a Nikon A1 scanning confocal to get ~.8um sections (from 11-20ish sections each) at 20x. In order to make sure results are quantifyable, the exact same microscope settings are used to capture each image stack.
Ive used ImageJ to split color and then manually adjust brightness and contrast of each stack such that adjusted levels match one another for each color. (this has been optimized to a "one size fits most" level). This is the step I believe may be causing problems, but let me continue.
This is followed by subtracting the background with a standardized "rolling ball" algorithm. Finally, the image is made binary using the auto-threshold function “Moments” (Tsai’s method attempts to preserve the moments of the original image in the threshold result; Tsai, 1985). From here the ROI boundary is thrown on and "analyze particles" is used to quantify objects by %area.
The problem is that when I use these "universal" brightness/contrast levels across all stacks of the same color (in the same region of the hippocampus) I get one result that looks good, but seems to hide a substantial number of neurites that may be important. However when I try to include the multitude of "missing signal" by creating images based on "relative levels" (in which each stack gets a custom brightness/contrast modification), the results are strikingly different. While I trust the universal levels to be comparable in regards to absolute levels of antigen present (necessary for results) I feel like there is a large amount of information that is missing (number of antigen-positive axons). I have come to the general conclusion that the %area obtained from the "universal" or "absolute" levels is a reflection of just that, the absolute levels of antigen being detected (of course this doesn't account for linear ranges above the detection threshold...) and that by modulating the brightness/contrast individually for each stack I am better able to detect number of antigen-positive structures.
Am I right to think this? Is there a better way to go about accurately assessing actual levels of these antigens? (we'll be doing Westerns too, but the cytoarchitectural information is critical to understanding potential mechanisms of action).

Quanitification of IHC images
« on: May 17, 2017, 03:34:21 PM »