SignificanceEmerging evidence that aggressive breast tumors rely on various substrates including lipids and glucose to proliferate and recur necessitates the development of tools to track multiple metabolic and vascular endpoints concurrently in vivo.AimOur quantitative spectroscopy technique provides time-matched measurements of the three major axes of breast cancer metabolism as well as tissue vascular properties in vivo.ApproachWe leverage exogenous fluorophores to quantify oxidative phosphorylation, glucose uptake, and fatty acid oxidation, and endogenous contrast for measurements of hemoglobin and oxygen saturation. An inverse Monte Carlo algorithm corrects for aberrations resulting from tissue optical properties, allowing the unmixing of spectrally overlapping fluorophores.ResultsImplementation of our inverse Monte Carlo resulted in a linear relationship of fluorophore intensity with concentration (R2<0.99) in tissue-mimicking phantom validation studies. We next sequenced fluorophore delivery to faithfully recapitulate independent measurement of each fluorophore. The ratio of Bodipy FL C16/2-NBDG administered to a single animal is not different from that in paired animals receiving individual fluorophores (p=n.s.). Clustering of five variables was effective in distinguishing tumor from mammary tissue (sensitivity = 0.75, specificity = 0.83, and accuracy = 0.79).ConclusionsOur system can measure major axes of metabolism and associated vascular endpoints, allowing for future study of tumor metabolic flexibility.
We developed an approach to quantify intra-tumoral metabolic heterogeneity of in vivo tumor models by leveraging a computationally designed multi-scale microscope and a suite of exogenous fluorescent contrast agents to provide functional and structural information.
Commercial imaging systems such as mobile phones are suitable for fluorescence detection of in vivo and ex vivo tissue samples. To leverage this potential, a uniform plane of excitation light is necessary to make quantitative measurements of regions within an image. We have developed a computational model to simulate the illumination of an arbitrary number of sources. Using a pattern search algorithm, the position of these sources can be determined to generate a uniform plane of excitation light. Initial studies demonstrate that 4 fiber optic sources can be used to generate uniform illumination for biopsy samples with different geometries.
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