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We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled
cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging
system consists of a fluorescence microscope, robotic imaging positioner, customized
cryostat, PC-based control system, and visualization/analysis software. The system alternates
between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface
image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells,
GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove
subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next
image was scaled, blurred, and subtracted from the current image. We estimated scaling and
blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation
parameters were found [uT : heart (267 ± 47.6 μm), liver (218 ± 27.1 μm), brain (161 ± 27.4 μm)]
to be within the range of estimates in the literature. "Next image" processing removed subsurface
fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and
analysis of 200 microsphere images in the brain gave 97±2% reduction of subsurface
fluorescence. Fluorescent signals were determined to arise from single cells based upon
geometric and integrated intensity measurements. Next image processing greatly improved axial
resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells
with connected component analysis by up to 24%. Analysis of image volumes identified
metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere
distribution correlated with blood flow patterns.
We developed and evaluated cryo-imaging to provide single-cell detection of
fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB),
micron-scale, fluorescence, and bright field image data. Here we describe our image preprocessing,
analysis, and visualization techniques. Processing improves axial resolution, reduces
subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D
volume renderings enable us to evaluate cell distribution patterns. Applications include the
myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore
labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue
engineering, etc.
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