Optimization is an important but relatively unexplored aspect of contrast-enhanced fluorescence imaging, since minimizing contrast agent usage reduces the associated cost and potential toxicity. In a previous study, the authors developed a quantitative experimental approach to optimize quantum dot (QD)-based imaging using homogenized liver as a model tissue. In this follow-up study, the authors further extend and validate the approach using eight different tissues and five QDs emission wavelengths, and introduce quantitative imaging performance metrics, namely the threshold QD concentration and wavelength optimization gain. These metrics allow quantification of the improvements through spectral optimization in terms of reduced QD dose and identify the conditions that make the optimization process worthwhile. The authors show that, for most tissues, the most important parameter to optimize is the emission wavelength, yielding improvements of up to four orders of magnitude, followed by the excitation wavelength (up to 20-fold improvement) and the excitation filter bandwidth (up to 50% improvement). The authors also observe, by means of the optimization gain metric, that tissues exhibiting both high autofluorescence and strong pigmentation are generally better candidates for excitation wavelength optimization. This work contributes to the development of robust and quantitative dosimetry for QD-based fluorescence imaging near to the tissue surface.
The use of phantoms comprising diluted tissue homogenates with a buried capillary containing quantum dots is demonstrated as a method to investigate the optical and biophysical factors influencing the imaging of subsurface fluorescence contrast agents. Validation of the method is demonstrated using both liquid phantoms of known optical absorption and reduced scattering and Monte Carlo computer simulations of photon transport. Conclusions regarding the optimal excitation wavelength are given and quantified with respect to the tissue optical properties. The tissue homogenate method should be of value for quantitative optimization studies relevant to, for example, endoscopic imaging.
Different colors of visible light penetrate to varying depths in tissue due to the wavelength dependence of tissue optical absorption and elastic scattering. We exploit this to map the contour of the closest surface of a buried fluorescent object. This uses a novel algorithm based on the diffusion theory description of light propagation in tissue at each excitation wavelength to derive metrics that define the depth of the top surface of the object. The algorithm was validated using a tissue-simulating phantom. It was then demonstrated in vivo by subsurface brain tumor topography in a rodent model, using the fluorescence signal from protoporphyrin IX that is preferentially synthesized within malignant cells following systemic application of aminolevulinic acid. Comparisons to histomorphometry in the brain post mortem show the spatial accuracy of the technique. This method has potential for fluorescence image-guided tumor surgery, as well as other biomedical and nonbiological applications in subsurface sensing.
We are investigating the use of ZnS-capped CdSe quantum dot (QD) bioconjugates combined with fluorescence
endoscopy for improved early cancer detection in the esophagus, colon and lung. A major challenge in using fluorescent
contrast agents in vivo is to extract the relevant signal from the tissue autofluorescence (AF). The present studies are
aimed at maximizing the QD signal to AF background ratio (SBR) to facilitate detection. These contrast optimization
studies require optical phantoms that simulate tissue autofluorescence, absorption and scattering over the entire visible
spectrum, while allowing us to control the optical thickness. We present an optical phantom made of fresh homogenized
tissue diluted in water. The homogenized tissue is poured into a clear polymer tank designed to hold a QD-loaded silica
capillary in its center. Because of the non-linear effects of absorption and scattering on measured autofluorescence,
direct comparison between results obtained using tissue phantoms of different concentration is not possible. We
introduce mathematical models that make it possible to perform measurements on diluted tissue homogenates and
subsequently extrapolate the results to intact (non-diluted) tissue. Finally, we present preliminary QD contrast data
showing that the 380-420 nm spectral window is optimal for surface QD imaging.
Our group is investigating the use of ZnS-capped CdSe quantum dot (QD) bioconjugates combined with fluorescence
endoscopy for improved early cancer detection in the esophagus, colon and lung. A major challenge in using fluorescent
contrast agents in vivo is to extract the relevant signal from the tissue autofluorescence (AF). Our studies are aimed at
maximizing the QD signal to AF background ratio (SBR) to facilitate detection. This work quantitatively evaluates the
effect of the excitation wavelength on the SBR, using both experimental measurements and mathematical modeling.
Experimental SBR measurements were done by imaging QD solutions placed onto (surface) or embedded in (sub-surface)
ex vivo murine tissue samples (brain, kidney, liver, lung), using a polymethylmethacrylate (PMMA)
microchannel phantom. The results suggest that the maximum contrast is reached when the excitation wavelength is set
at 400±20 &mgr;m for the surface configuration. For the sub-surface configuration, the optimal excitation wavelength varies
with the tissue type and QD emission wavelengths. Our mathematical model, based on an approximation to the
diffusion equation, successfully predicts the optimal excitation wavelength for the surface configuration, but needs
further modifications to be accurate in the sub-surface configuration.
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