Over the last 20 year significant advances in light microscopy have occurred using confocal microscopy. The first systems were designed using a single laser light source, thus providing a single point of light that could be scanned across the biological sample producing an “optical section” that only contained in-focus information. By stacking a series of these on top of each other a three-dimensional image is created. More recently several additional advances have included (i) multi-photon imaging permitting greater depth of imaging as well as imaging living samples as either windowed tissues in whole organisms, fish and worms with low density, or 3-D cultures of organs or tissue slices and (ii) spinning disc imaging that uses convention white light sources, a spinning disc for “optical sectioning” and a series of filters to enable multi-spectral imaging. CIBR has one of the countries most complete confocal imaging facilities with commercial laser scanning microscopes, two coupled multi-photon microscopes, and a spinning disc confocal system.
The CIBR spinning disc system routinely measures four or five spectral signals and we are developing methods to image as many as seven. The methods developed here provide for high resolution imaging or large brain samples. These data are then processed using the FARSIGHT Image Analysis toolbox (a collaboration with Drs. Shain, CIBR, and Roysam, University of Houston) resulting in identification of every nucleus in a dataset (large volumes = 2x2x0.2 mm3), classification of these nuclei as neurons, astrocytes, microglia, or vascular elements, tracing of all of the astrocytes and microglia, and mapping of all of these elements in 3-dimensional space. While we have developed and validated these methods in brains samples following insertion of neuroprosthetic devices, we are now using these methods to image human brain samples to better understand changes in cell heterogeneity and organization associated with intractable epilepsy, medulloblastoma of children, and glioblastoma of adults. The goals of this research are to use quantitative measures to develop improved methods of disease classification for more exacting differential diagnosis and improved treatment.