An official website of the United States government
Fluorescence imaging microscopy has traditionally been used because of the high specificity that is achievable through fluorescence labeling techniques and optical filtering. When combined with spectral imaging technologies, fluorescence microscopy can allow for quantitative identification of multiple fluorescent labels. We are working to develop a new approach for spectral imaging that samples the fluorescence excitation spectrum and may provide increased signal strength. The enhanced signal strength may be used to provide increased spectral sensitivity and spectral, spatial, and temporal sampling capabilities. A proof of concept excitation scanning system has shown over 10-fold increase in signal to noise ratio compared to emission scanning hyperspectral imaging. Traditional hyperspectral imaging fluorescence microscopy methods often require minutes of acquisition time. We are developing a new configuration that utilizes solid state LEDs to combine multiple illumination wavelengths in a 2-mirror assembly to overcome the temporal limitations of traditional hyperspectral imaging. We have previously reported on the theoretical performance of some of the aspects of this system by using optical ray trace modeling. Here, we present results from prototyping and benchtop testing of the system, including assembly, optical characterization, and data collection. This work required the assembly and characterization of a novel excitation scanning hyperspectral microscopy system, containing 12 LEDs ranging from 365- 425 nm, 12 lenses, a spherical mirror, and a flat mirror. This unique approach may reduce the long image acquisition times seen in traditional hyperspectral imaging while maintaining high specificity and sensitivity for multilabel identification and autofluorescence imaging in real time.
more »
« less
Applications and assessment of an excitation-scanning hyperspectral imaging system
The majority of microscopic and endoscopic technologies utilize white light illumination. For a number of applications, hyper-spectral imaging can be shown to have significant improvements over standard white-light imaging techniques. This is true for both microscopy and in vivo imaging. However, hyperspectral imaging methods have suffered from slow application times. Often, minutes are required to gather a full imaging stack. Here we will describe and evaluate a novel excitation-scanning hyperspectral imaging system and discuss some applications. We have developed and are optimizing a novel approach called excitation-scanning hyperspectral imaging that provides an order of magnitude increased signal strength. This excitation scanning technique has enabled us to produce a microscopy system capable of high speed hyperspectral imaging with the potential for live video acquisition. The excitation-scanning hyperspectral imaging technology we developed may impact a range of applications. The current design uses digital strobing to illuminate at 16 wavelengths with millisecond image acquisition time. Analog intensity control enables a fully customizable excitation profile. A significant advantage of excitation-scanning hyperspectral imaging is can identify multiple targets simultaneously in real time. Finally, we are exploring utilizing this technology for a variety of applications ranging from measuring cAMP distribution in three dimensions within a cell to electrophysiology.
more »
« less
- Award ID(s):
- 1725937
- PAR ID:
- 10064179
- Date Published:
- Journal Name:
- Proc. SPIE 10497, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVI
- Volume:
- 10497
- Page Range / eLocation ID:
- 1049706
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
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.more » « less
-
Hyperspectral imaging technologies have shown great promise for biomedical applications. These techniques have been especially useful for detection of molecular events and characterization of cell, tissue, and biomaterial composition. Unfortunately, hyperspectral imaging technologies have been slow to translate to clinical devices – likely due to increased cost and complexity of the technology as well as long acquisition times often required to sample a spectral image. We have demonstrated that hyperspectral imaging approaches which scan the fluorescence excitation spectrum can provide increased signal strength and faster imaging, compared to traditional emission-scanning approaches. We have also demonstrated that excitation-scanning approaches may be able to detect spectral differences between colonic adenomas and adenocarcinomas and normal mucosa in flash-frozen tissues. Here, we report feasibility results from using excitation-scanning hyperspectral imaging to screen pairs of fresh tumoral and nontumoral colorectal tissues. Tissues were imaged using a novel hyperspectral imaging fluorescence excitation scanning microscope, sampling a wavelength range of 360-550 nm, at 5 nm increments. Image data were corrected to achieve a NIST-traceable flat spectral response. Image data were then analyzed using a range of supervised and unsupervised classification approaches within ENVI software (Harris Geospatial Solutions). Supervised classification resulted in >99% accuracy for single-patient image data, but only 64% accuracy for multi-patient classification (n=9 to date), with the drop in accuracy due to increased false-positive detection rates. Hence, initial data indicate that this approach may be a viable detection approach, but that larger patient sample sizes need to be evaluated and the effects of inter-patient variability studied.more » « less
-
Abstract Colorectal cancer is one of the top contributors to cancer-related deaths in the United States, with over 100,000 estimated cases in 2020 and over 50,000 deaths. The most common screening technique is minimally invasive colonoscopy using either reflected white light endoscopy or narrow-band imaging. However, current imaging modalities have only moderate sensitivity and specificity for lesion detection. We have developed a novel fluorescence excitation-scanning hyperspectral imaging (HSI) approach to sample image and spectroscopic data simultaneously on microscope and endoscope platforms for enhanced diagnostic potential. Unfortunately, fluorescence excitation-scanning HSI datasets pose major challenges for data processing, interpretability, and classification due to their high dimensionality. Here, we present an end-to-end scalable Artificial Intelligence (AI) framework built for classification of excitation-scanning HSI microscopy data that provides accurate image classification and interpretability of the AI decision-making process. The developed AI framework is able to perform real-time HSI classification with different speed/classification performance trade-offs by tailoring the dimensionality of the dataset, supporting different dimensions of deep learning models, and varying the architecture of deep learning models. We have also incorporated tools to visualize the exact location of the lesion detected by the AI decision-making process and to provide heatmap-based pixel-by-pixel interpretability. In addition, our deep learning framework provides wavelength-dependent impact as a heatmap, which allows visualization of the contributions of HSI wavelength bands during the AI decision-making process. This framework is well-suited for HSI microscope and endoscope platforms, where real-time analysis and visualization of classification results are required by clinicians.more » « less
-
Many hardware approaches have been developed for implementing hyperspectral imaging on fluorescence microscope systems; each with tradeoffs in spectral sensitivity and spectral, spatial, and temporal sampling. For example, tunable filter-based systems typically have limited wavelength switching speeds and sensitivities that preclude high-speed spectral imaging. Here, we present a novel approach combining multiple illumination wavelengths using solid state LEDs in a 2-mirror configuration similar to a Cassegrain reflector assembly. This approach provides spectral discrimination by scanning a range of fluorescence excitation wavelengths, which we have previously shown can improve spectral image acquisition time compared to traditional fluorescence emission-scanning hyperspectral imaging. In this work, the geometry of the LED and other optical components was optimized. A model of the spectral illuminator was designed using TracePro ray tracing software (Lambda Research Corp.) that included an emitter, lens, Spherical mirror, flat mirror, and liquid light guide input. A parametric sensitivity study was performed to optimize the optical throughput varying the LED viewing angle, properties of the Spherical reflectors, the lens configuration, focal length, and position. The following factors significantly affected the optical throughput: LED viewing angle, lens position, and lens focal length. Several types of configurations were evaluated, and an optimized lens and LED position were determined. Initial optimization results indicate that a 10% optical transmission can be achieved for either a 16 or 32 wavelength system. Future work will include continuing to optimize the ray trace model, prototyping, and experimental testing of the optimized configuration.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1117/12.2290120
