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.
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Hyperspectral imaging fluorescence excitation scanning spectral characteristics of remodeled mouse arteries
Coronary artery disease (CAD), or atherosclerosis, is responsible for nearly a third of all American deaths annually. Detection of plaques and differentiation of plaque stage remains a complicating factor for treatment. Classification of plaque before significant blockage or rupture could inform clinical decisions and prevent mortality. Current detection methods are either nonspecific, slow, or require the use of potentially harmful contrast agents. Recent advances in hyperspectral imaging could be used to detect changes in the autofluorescence of arteries associated with vessel remodeling and subsequent plaque formation and could detect and classify existing lesions. Here, we present data comparing spectral image characteristics of a mouse model designed to undergo vessel remodeling.
C57Bl/6 mice underwent ligation of three of four caudal branches of the left common carotid artery (left external carotid, internal carotid, and occipital artery) with the superior thyroid artery left intact under IACUC approved protocol. Vessels were harvested at a variety of timepoints to compare degrees of remodeling, including 4 weeks and 5 months post-surgery. Immediately following harvest, vessels were prepared by longitudinal opening to expose the luminal surface to a 20X objective. A custom inverted microscope (TE-2000, Nikon Instruments) with a Xe arc lamp and thin film tunable filter arrary (Versachrome, Semrock, Inc.) were used to achieve spectral imaging. Excitation scans utilized wavelengths between 340 nm and 550 nm in 5 nm increments. Hyperspectral data were generated and analyzed with custom Matlab scripts and visualized in ENVI. Preliminary data suggest consistent spectral features associated with control and remodeled vessels.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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- Award ID(s):
- 1725937
- NSF-PAR ID:
- 10107072
- Date Published:
- Journal Name:
- Proc. SPIE 10890, Label-free Biomedical Imaging and Sensing (LBIS) 2019, 108902M
- Volume:
- 10890
- Page Range / eLocation ID:
- 94
- 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/10.1117/12.2510770
