Search for: All records

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. 

Systems engineering captures the desires and needs of the customer to conceptualize a system from the overall goal down to the small details prior to any physical development. While many systems projects tend to be large and complicated (i.e., cloud-based infrastructure, long-term space travel shuttles, missile defense systems), systems engineering can also be applied to smaller, complex systems. Here, the system of interest is the endoscope, a standard biomedical screening device used in laparoscopic surgery, screening of upper and lower gastrointestinal tracts, and inspection of the upper airway. Often, endoscopic inspection is used to identify pre-cancerous and cancerous tissues, and hence, a requirement for endoscopic systems is the ability to provide images with high contrast between areas of normal tissue and neoplasia (early-stage abnormal tissue growth). For this manuscript, the endoscope was reviewed for all the technological advancements thus far to theorize what the next version of the system could be in order to provide improved detection capabilities. Endoscopic technology was decomposed into categories, using systems architecture and systems thinking, to visualize the improvements throughout the system’s lifetime from the original to current state-of-the-art. Results from this review were used to identify trends in subsystems and components to estimate the theoretical performance maxima for different subsystems as well as areas for further development. The subsystem analysis indicated that future endoscope systems will focus on more complex imaging and higher computational requirements that will provide improved contrast in order to have higher accuracy in optical diagnoses of early, abnormal tissue growth. 

Positive outcomes for colorectal cancer treatment have been linked to early detection. The difficulty in detecting early lesions is the limited contrast with surrounding mucosa and minimal definitive markers to distinguish between hyperplastic and carcinoma lesions. Colorectal cancer is the 3rd leading cancer for incidence and mortality rates which is potentially linked to missed early lesions which allow for increased growth and metastatic potential. One potential technology for early-stage lesion detection is hyperspectral imaging. Traditionally, hyperspectral imaging uses reflectance spectroscopic data to provide a component analysis, per pixel, of an image in fields such as remote sensing, agriculture, food processing and archaeology. This work aims to acquire higher signal-to-noise fluorescence spectroscopic data, harnessing the autofluorescence of tissue, adding a hyperspectral contrast to colorectal cancer detection while maintaining spatial resolution at video-rate speeds. We have previously designed a multi-furcated LED-based spectral light source to prove this concept. Our results demonstrated that the technique is feasible, but the initial prototype has a high light transmission loss (~98%) minimizing spatial resolution and slowing video acquisition. Here, we present updated results in developing an optical ray-tracing model of light source geometries to maximize irradiance throughput for excitation-scanning hyperspectral imaging. Results show combining solid light guide branches have a compounding light loss effect, however, there is potential to minimize light loss through the use of optical claddings. This simulation data will provide the necessary metrics to verify and validate future physical optical components within the hyperspectral endoscopic system for detecting colorectal cancer. 

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. 

Hyperspectral imaging (HSI) technology has been applied in a range of fields for target detection and mixture analysis. While its original applications were in remote sensing, modern uses include agriculture, historical document authentications and medicine. HSI has shown great utility in fluorescence microscopy; however, acquisition speeds have been slow due to light losses associated with spectral filtering. We are currently developing a rapid hyperspectral imaging platform for 5-dimensional imaging (RHIP-5D), a confocal imaging system that will allow users to obtain simultaneous measurements of many fluorescent labels. We have previously reported on optical modeling performance of the system. This previous model investigated geometrical capability of designing a multifaceted mirror imaging system as an initial approach to sample light at many wavelengths. The design utilized light-emitting diodes (LEDs) and a multifaceted mirror array to combine light sources into a liquid light guide (LLG). The computational model was constructed using Monte Carlo optical ray software (TracePro, Lambda Research Corp.). Recent results presented here show transmission has increased up to 9% through parametric optimization of each component. Future work will involve system validation using a prototype engineered based on our optimized model. System requirements will be evaluated to determine if potential design changes are needed to improve the system. We will report on spectral resolution to demonstrate feasibility of the RHIP-5D as a promising solution for overcoming current HSI acquisition speed and sensitivity limitations. 

Hyperspectral imaging has numerous applications in a range of fields for target detection. While its original applications were in remote sensing, new uses include analyzing food quality, agriculture and medicine, Hyperspectral imaging has shown utility in fluorescence microscopy for detecting signatures from many fluorescent molecules, but acquisition speeds have been slow due to the need to acquire many spectral bands and the light losses associated with spectral filtering. Therefore, a novel confocal microscope, the 5- Dimensional Rapid Hyperspectral Imaging Platform (RHIP-5D) was designed and is undergoing testing to overcome acquisition speed and sensitivity limitations. The current design utilizes light-emitting diodes (LEDs) and a multifaceted mirror array to combine light sources into a liquid light guide. Initial tests demonstrated feasibility and we are now working on determining the ideal location of the liquid light guide, LEDs, lenses and mirror array to optimize optical transmission. A computational model was constructed using Monte Carlo optical ray tracing in TracePro software (Lambda Research Corp.). LED sources were simulated by importing irradiance properties from the manufacturers’ specifications. Optical properties of lenses were modeled using lens files available from the manufacturer. Analysis of the model includes geometry and parametric optimization, assessing lens power, mirror angles and location of optical elements. Initial results show an increase of transmission is possible by up to 20%. Future work will involve evaluating the position of the liquid light guide as well as analyzing lens configurations to further increase optical transmission. 

Hyperspectral imaging (HSI) is a technology used in remote sensing, food processing and documentation recovery. Recently, this approach has been applied in the medical field to spectrally interrogate regions of interest within respective substrates. In spectral imaging, a two (spatial) dimensional image is collected, at many different (spectral) wavelengths, to sample spectral signatures from different regions and/or components within a sample. Here, we report on the use of hyperspectral imaging for endoscopic applications. Colorectal cancer is the 3rd leading cancer for incidences and deaths in the US. One factor of severity is the miss rate of precancerous/flat lesions (~65% accuracy). Integrating HSI into colonoscopy procedures could minimize misdiagnosis and unnecessary resections. We have previously reported a working prototype light source with 16 high-powered light emitting diodes (LEDs) capable of high speed cycling and imaging. In recent testing, we have found our current prototype is limited by transmission loss (~99%) through the multi-furcated solid light guide (lightpipe) and the desired framerate (20-30 fps) could not be achieved. Here, we report on a series of experimental and modeling studies to better optimize the lightpipe and the spectral endoscopy system as a whole. The lightpipe was experimentally evaluated using an integrating sphere and spectrometer (Ocean Optics). Modeling the lightpipe was performed using Monte Carlo optical ray tracing in TracePro (Lambda Research Corp.). Results of these optimization studies will aid in manufacturing a revised prototype with the newly designed light guide and increased sensitivity. Once the desired optical output (5-10 mW) is achieved then the HIS endoscope system will be able to be implemented without adding onto the procedure time.