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Proceedings Paper

Melanin-targeted nonlinear microscopy for label-free molecular diagnosis and staining (Conference Presentation)
Author(s): Warren S. Warren

Paper Abstract

Visible absorption in tissue is dominated by a very small number of chromophores (hemoglobins and melanins) with broad optical spectra; for melanins in particular, the optical absorption spectrum is typically featureless. In addition, scattering limits penetration depth. As a result, the most common microscopy application by far is with excised tissue, which can be stained. However, nonlinear optical methods have the additional advantages of greater penetration depth and reduced sensitivity to scattering. Traditional nonlinear microscopy relies on mechanisms which produce light of a different color than the irradiating lasers, such as second harmonic generation or two photon induced fluorescence, and this contrast is sparse in biological issue without expressing or injecting different chromophores. Recently, stable laser sources and pulse shaping/pulse train modulation methods have made it possible to detect a much wider range of nonlinear molecular signatures, even at modest laser powers (much less than a laser pointer). Here we show the utility of a variety of such signatures (pump-probe, pulse-shaped stimulated Raman, cross-phase modulation) to quantitatively image the biochemical composition of transparent or pigmented tissue in a variety of applications, ranging from thin, unstained tissue sections to live knockout mice. The rich biochemical information provided by this method can be used as an indicator of melanocyte activity, which in turn (for example) reflects the status of melanocytic lesions. Comparisons with model systems (synthetic melanin nanoparticles, sepia melanin) and analysis of melanin degradation pathways in vivo have led to a quantitative understanding of the molecular basis of these changes.

Paper Details

Date Published: 24 April 2017
PDF: 1 pages
Proc. SPIE 10076, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II, 1007603 (24 April 2017); doi: 10.1117/12.2256444
Show Author Affiliations
Warren S. Warren, Duke Univ. (United States)

Published in SPIE Proceedings Vol. 10076:
High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II
Kevin K. Tsia; Keisuke Goda, Editor(s)

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