A major benefit of fluorescence microscopy is the now plentiful selection of fluorescent markers. These labels can be chosen to serve complementary functions, such as tracking labeled subcellular molecules near demarcated organelles. However, with the standard 3 or 4 emission channels, multiple label detection is restricted to segregated regions of the electromagnetic spectrum, as in RGB coloring. Hyperspectral imaging allows the user to discern many fluorescence labels by their unique spectral properties, provided there is significant differentiation of their emission spectra. The cost of this technique is often an increase in gain or exposure time to accommodate the signal reduction from separating the signal into many discrete excitation or emission channels. Recent advances in hyperspectral imaging have allowed the acquisition of more signal in a shorter time period by scanning the excitation spectra of fluorophores. Here, we explore the selection of optimal channels for both significant signal separation and sufficient signal detection using excitation-scanning hyperspectral imaging. Excitation spectra were obtained using a custom inverted microscope (TE-2000, Nikon Instruments) with a Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) Tunable filters had bandwidths between 13 and 17 nm. Scans utilized excitation wavelengths between 340 nm and 550 nm. Hyperspectral image stacks were generated and analyzed using ENVI and custom MATLAB scripts. Among channel consideration criteria were: number of channels, spectral range of scan, spacing of center wavelengths, and acquisition time.
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Demystifying autofluorescence with excitation scanning hyperspectral imaging
Autofluorescence has historically been considered a nuisance in medical imaging. Many endogenous fluorophores, specifically, collagen, elastin, NADH, and FAD, are found throughout the human body. Diagnostically, these signals can be prohibitive since they can outcompete signals introduced for diagnostic purposes. Recent advances in hyperspectral imaging have allowed the acquisition of significantly more data in a shorter time period by scanning the excitation spectra of fluorophores. The reduced acquisition time and increased signal-to-noise ratio allow for separation of significantly more fluorophores than previously possible. Here, we propose to utilize excitation-scanning of autofluorescence to examine tissues and diagnose pathologies.
Spectra of autofluorescent molecules were obtained using a custom inverted microscope (TE-2000, Nikon Instruments) with a Xe arc lamp and thin film tunable filter array
(VersaChrome, Semrock, Inc.) Scans utilized excitation wavelengths from 360 nm to 550 nm in 5 nm increments. The resultant spectra were used to examine hyperspectral image stacks from various collaborative studies, including an atherosclerotic rat model and a colon cancer study. Hyperspectral images were analyzed with ENVI and custom Matlab scripts including linear spectral unmixing (LSU) and principal component analysis (PCA). Initial results suggest the ability to separate the signals of endogenous fluorophores and measure the relative concentrations of fluorophores among healthy and diseased states of similar tissues. These results suggest pathology-specific changes to endogenous fluorophores can be detected using excitationscanning
hyperspectral imaging. Future work will expand the library of pure molecules and will examine more defined
disease states.
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- Award ID(s):
- 1725937
- NSF-PAR ID:
- 10064181
- Date Published:
- Journal Name:
- Proc. SPIE 10497, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVI
- Volume:
- 10497
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1117/12.2290818
