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Three Dimensional Light Microscopy: Imaging & Corrections for Quantitative Analysis

Published online by Cambridge University Press:  02 July 2020

J.N. Turner
Affiliation:
Wadsworth Center, New York State Department of Health, The University at Albany, Albany, New York12201; School of Public Health, The University at Albany, Albany, New York12201; Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York12180
W. hain
Affiliation:
Wadsworth Center, New York State Department of Health, The University at Albany, Albany, New York12201; School of Public Health, The University at Albany, Albany, New York12201;
D.H. Szarowski
Affiliation:
Wadsworth Center, New York State Department of Health, The University at Albany, Albany, New York12201;
S. Lasek
Affiliation:
Wadsworth Center, New York State Department of Health, The University at Albany, Albany, New York12201;
L. Kam
Affiliation:
Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York12180
A. Can
Affiliation:
Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, New York12180
K. Al-Kofahi
Affiliation:
Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, New York12180
B. Roysam
Affiliation:
Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, New York12180
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Extract

There are several forms of three-dimensional (3-D) light microscopy but all utilize the principle of optical section recording, i.e. the 3-D image is a sequence of two-dimensional (2-D) images called optical sections. The optical sections are particular focal planes formed within the thick specimen and usually correspond to the conventional image projections recorded in a light microscope, referred to as x,y projections. The optical sections are recorded for a sequence of focus- or z-positions. This “stack” of 2-D images is the data set for the 3-D image. If quantitative analysis is to be performed on the 3-D images, the choice of the z-dimension increment between 2-D images is especially important, and its value may be more or less critical depending on the analysis algorithm used. A reasonable starting value for this dimension is the depth-of-field of the objective lens, but the actual value may have to be smaller to optimize the image analysis or larger to decrease the influence of photobleaching. The most photostable dyes should be selected and the specimen should be mounted in index-of-refraction matching media with an antioxidant.

The image resolution in all three-dimensions is determined by the 3-D point-spread-function (psf), and as a rough rule of thumb the z-resolution is degraded by a factor of 3 relative to the x,y resolution. To achieve or at least approach isotropic resolution the 3-D image can be deconvolved. Figure 1 shows the 2-D maximum value projection of a 3-D image of a cultured glial cell dual labeled for actin and vinculin before and after deconvolution. The actin fibers and vinculin focal contacts are more clearly resolved after deconvolution. Although a single cultured cell might traditionally be considered a thin object, it is really a thick object if the desired spatial resolution is less than the thickness of the cell. It is desirable to image as deep into a thick object as possible to maximize the tissue volume sampled. However, it has been shown that the image signal decreases with depth into the specimen. Figure 2 demonstrates this effect in a 3-D image of the nuclei of the rat hippocampus that have been labeled with the fluorescent Schiffs reagent acriflavine. In the x,y projection, it is not clear why some nuclei are dimmer than others, but the x,z projection shows that the dimmer ones tend to be deeper in the section. It has been shown that this depth dependent signal attenuation follows the form of an exponential function.

Type
From 3-D Light Microscopic Images to Quantitative Insight
Copyright
Copyright © Microscopy Society of America

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References

1. Turner, J.N., et al., Int. J. Imaging Science Technology, 8 (1997)2403.0.CO;2-A>CrossRefGoogle Scholar

2. Rigaut, J., et al., Anal. Quant Cytol Histol 13 (1991)223Google Scholar

3. Kayali, S.MS, Thesis, Rensselaer Polytechnic Institute, (1996)Google Scholar

4. Work partially supported by: NIH NCRR R01RR10957, SI011382Google Scholar