Quantitation of in vivo Fluorescense Signals
The quantization of fluorescence signals in vivo can be a difficult task, often due to interference caused by skin autofluorescence which occurs to a greater or lesser extent at all excitation wavelengths. This skin autofluorescence and the contrast problem it causes for in vivo fluorescence measurements, although less of a problem in the NIR, can be the limiting factor for the limit of detection of fluorophores at all wavelengths.
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Figure 1: Images and data acquired from 4 mice, each injected in 2 sites with various doses of the fluorescent compound, doxorubicin (DOX): 1000, 500, 250, 125, 62.5, 31.25, 15.63, and 7.18 ng. Monochrome images were acquired at the peak emission of DOX. Upper left image shows a monochrome image of the mouse with the 250- and 125-ng amounts of DOX, and the lower left image shows the same animal after spectrally unmixing the DOX signals from tissue autofluorescence. Both the increase in sensitivity and the improvement in quantitative accuracy can be seen in the two plots on the right, with the upper right before and the lower left after unmixing.
Autofluorescence from skin, organs and food emits at wavelengths which overlap those of fluorophores of interest. The monochrome (not spectrally unmixed) image of the mouse in the top left panel shows how autofluorescence can mask the location and amount of the injected DOX signals. By utilizing a patented methodology, however, a Maestro multispectral imaging system is able to remove the interference from the autofluorescence by spectrally characterizing skin and DOX signals and quantitating each separately (autofluorescence image not shown). The isolated DOX signal seen in the lower left image has much higher contrast and the measured intensities now reflect only signals arising from DOX fluorescence itself. The improvement in sensitivity and accuracy over monochrome approaches is shown in the right-hand graphs which show the integrated intensities over the injection sites before (above) and after (below) spectral unmixing.
This example demonstrates how removing the autofluorescence from in vivo signals can dramatically increase contrast and improve quantitative accuracy.
Enhancing Image Contrast and Improving Quantitative Analysis with Multispectral Imaging and Spectral Unmixing (pdf)
