Excitation-scanning hyperspectral imaging microscope

Abstract

Abstract. Hyperspectral imaging is a versatile tool that has recently been applied to a variety of biomedical applications, notably live-cell and whole-tissue signaling. Traditional hyperspectral imaging approaches filter the fluorescence emission over a broad wavelength range while exciting at a single band. However, these emission-scanning approaches have shown reduced sensitivity due to light attenuation from spectral filtering. Consequently, emission scanning has limited applicability for time-sensitive studies and photosensitive applications. In this work, we have developed an excitation-scanning hyperspectral imaging microscope that overcomes these limitations by providing high transmission with short acquisition times. This is achieved by filtering the fluorescence excitation rather than the emission. We tested the efficacy of the excitation-scanning microscope in a side-by-side comparison with emission scanning for detection of green fluorescent protein (GFP)-expressing endothelial cells in highly autofluorescent lung tissue. Excitation scanning provided higher signal-to-noise characteristics, as well as shorter acquisition times (300 ms∕wavelength band with excitation scanning versus 3 s∕wavelength band with emission scanning). Excitation scanning also provided higher delineation of nuclear and cell borders, and increased identification of GFP regions in highly autofluorescent tissue. These results demonstrate excitation scanning has utility in a wide range of time-dependent and photosensitive applications.

A theoretical‐experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods

“…For this example, we have used a similar biological assay as was used in Figure 1, but have acquired image data using two different spectral imaging microscope systems: a fluorescence emission-scanning hyperspectral imaging system [97,104] and a fluorescence excitation-scanning hyperspectral imaging system, both of which were previously developed in our lab [67]. In our prior work, we demonstrated that images acquired using the excitation-scanning system had significantly higher signal-to-noise ratios when all other imaging parameters were held constant (acquisition time, camera gain, etc.).…”

“…To correct for wavelength-dependent transmission artifacts, spectral image data were multiplied by a correction coefficient that was measured in reference to a NIST-traceable spectral illumination source. This was done by first measuring the wavelength-dependent system response using a fiber-coupled spectrometer (QE65000, Ocean Optics, Dunedin, FL) with integrating sphere and a NIST-traceable lamp (LS-1-CAL-INT, Ocean Optics), as described elsewhere [67,96,97]. In brief, the spectral response of either the emission-scanning or the excitation-scanning side of the microscope was measured and a correction factor calculated to correct image data to a flat spectral response.…”

“…A thin-film tunable filter based system similar to #2, but placed on the excitation side of the microscope, directly coupled to a Xe arclamp (Titan 300, Sunoptic Technologies, Jacksonville, Florida) and coupled to the microscope using a liquid light guide (Sutter Instrument Company, Novato, CA). Images were acquired using an EMCCD camera (Rolera EM-C 2 ) [67,86]. For imaging of NucBlue and Calcein Green labeled HEK293 cells, coverslips were mounted in Attofluor Cell Chambers (ThermoFisher Scientific, Waltham, MA), maintained in 1X PBS, and imaged using a Nikon A1R spectral confocal microscope (Nikon Instruments) equipped with 60X water immersion objective (Plan Apo VC 60x DIC N2 WI NA -1.2, Nikon Instruments) and 32 channel photomultiplier tube (PMT) array.…”

“…However, only a limited amount of research has been performed to apply many of the spectral image processing algorithms developed by the remote sensing community to biomedical applications [10]. Even less work has been done to quantitatively assess the effectiveness of spectral image analysis algorithms as applied to biological image data or to compare algorithms or spectral imaging systems to each other [10,[65][66][67]. Hence, it is not always clear which spectral imaging platform or analysis algorithm should be used for a particular biomedical imaging application.…”

Characterizing an Ionic Liquid as a Biological Fixative in Fluorescence Microscopy

“…1A). Segmenting the pixel data by Fourier transform using the Spectral Phasor (SP) method [8][9][10] offers an efficient representation of the hyperspectral data by condensing each spectrum in x,y,z into a single point in a 2D Phasor plot without data loss 8 ( Fig. 1B).…”