Date of Graduation
Bachelor of Science in Biomedical Engineering
Label-free metabolic imaging through quantification of NADH and FAD autofluorescence has become a powerful and efficient tool for non-invasive measurements of cell metabolism. It has applications in a variety of fields including diagnostic and therapeutic monitoring. However, NADH and FAD imaging typically selects specific single excitation and emission bands where it is assumed that these fluorophores are individually isolated. In some cases of isolated cell imaging, this assumption holds true, but for samples with other intrinsic fluorophores present (i.e. collagen and elastin), it can interfere with quantitative results. Elastin and collagen autofluorescence prevent the broader application of these optical metabolic imaging techniques to complex tissue with significant extracellular matrix, such as skin, heart, and lung tissue. Therefore, a method was established to more accurately distinguish NADH and FAD among other intrinsic fluorophores with spectral unmixing through nonnegative matrix factorization. By isolating spectra from pure solutions of NADH and FAD, other fluorophore spectra can be unmixed with an alternating least squares approach. As more spectra are isolated, the ability to quantify necessary fluorophore concentrations becomes more accurate. With further work, this study could enable accurate optical metabolic imaging within tissues containing a complex mix of naturally present fluorophores and speed the production of incorporating fluorescence imaging into clinical settings.
Spectral Unmixing, Fluoresence, Cellular Imaging
Woodbury, L. (2020). Autofluorescence Spectral Unmixing for Quantitative Metabolic Imaging within Tissues. Biomedical Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/bmeguht/81
Bioimaging and Biomedical Optics Commons, Molecular, Cellular, and Tissue Engineering Commons