The accepted screening technique for colon cancer is white light endoscopy. While most abnormal growths (lesions) are detected by this method, a significant number are missed during colonoscopy, potentially resulting in advanced disease. Missed lesions are often flat and inconspicuous in color. A prototype ultraviolet spectral imager measuring autofluorescence (AF) and reflectance has been developed and applied in a study of 21 fresh human colon surgical specimens. Six excitation wavelengths from 280 to 440 nm and formulaic ratio imaging were utilized to increase lesion contrast and cause neoplasms to appear bright compared to normal tissue. It was found that in the subset of lesions which were most difficult to visualize in standard color photographs [low contrast lesions, (LCLs)] a ratio image (F340/F440) of AF images excited at 340 and 440 nm produced extraordinary images and was effective in about 70% of these difficult cases. Contrast may be due to increased levels of reduced nicotinamide adenine dinucleotide, increased hemoglobin absorption, and reduced signal from submucosal collagen. A second successful ratio image (R480/R555) combined two reflectance images to produce exceptional images especially in particular LCLs where F340/F440 was ineffective. The newly discovered ratio images can potentially improve detection rate in screening with a novel AF colonoscope.
With no sufficient screening test for ovarian cancer, a method to evaluate the ovarian disease state quickly and nondestructively is needed. The authors have applied a wide-field spectral imager to freshly resected ovaries of 30 human patients in a study believed to be the first of its magnitude. Endogenous fluorescence was excited with 365-nm light and imaged in eight emission bands collectively covering the 400- to 640-nm range. Linear discriminant analysis was used to classify all image pixels and generate diagnostic maps of the ovaries. Training the classifier with previously collected single-point autofluorescence measurements of a spectroscopic probe enabled this novel classification. The process by which probe-collected spectra were transformed for comparison with imager spectra is described. Sensitivity of 100% and specificity of 51% were obtained in classifying normal and cancerous ovaries using autofluorescence data alone. Specificity increased to 69% when autofluorescence data were divided by green reflectance data to correct for spatial variation in tissue absorption properties. Benign neoplasm ovaries were also found to classify as nonmalignant using the same algorithm. Although applied ex vivo, the method described here appears useful for quick assessment of cancer presence in the human ovary.
Detection of flat neoplasia is a major challenge in colorectal cancer screening, as missed lesions can lead to the development of an unexpected 'incident' cancer prior to the subsequent endoscopy. The use of a tryptophan-related autofluorescence has been reported to be increased in murine intestinal dysplasia. The emission spectra of cells isolated from human adenocarcinoma and normal mucosa of the colon were studied and showed markedly greater emission intensity from cancerous cells compared to cells obtained from the surrounding normal mucosa. A proto-type multispectral imaging system optimized for ultraviolet macroscopic imaging of tissue was used to obtain autofluorescence images of surgical specimens of colonic neoplasms and normal mucosa after resection. Fluorescence images did not display the expected greater emission from the tumor as compared to the normal mucosa, most probably due to increased optical absorption and scattering in the tumors. Increased fluorescence intensity in neoplasms was observed however, once fluorescence images were corrected using reflectance images. Tryptophan fluorescence alone may be useful in differentiating normal and cancerous cells, while in tissues its autofluorescence image divided by green reflectance may be useful in displaying neoplasms.
The Advanced Radars and Electro-Optical Sensors group at the University of Missouri is constructing a new all-optical analog-to-digital converter (ADC) platform. This integrated optics application especially suits the data acquisition and processing requirements of mobile sensor systems that have dramatically increased alongside the requirements for reductions in system mass, volume, and power consumption. The platform of the ADC is composed of a direct-modulated laser (DML) at λ = 1.55 μm with a 40 G bits/sec sampling optical pulse source; a prism LiTaO3 (lithium tantalate) electro-optical deflector; an integrated focusing unit; a three-dimensional binary-coded spatial filter array; and collection optics. Using discrete Fourier transform, we also investigate both the center frequency-shifting phenomenon of the optical pulse propagation, and the frequency response. The simulations are calculated by using the two-dimensional Finite Difference Time Domain (FDTD) method, the results of which are much more reliable than Beam Propagation Methods (BPM). The spatial filter array and collection optics will be fabricated by the separated implanted oxygen process (SIMOX), silicon on insulator (SOI). Also, a new design and simulation of LiTaO3 (lithium tantalate) electro-optical deflector to be integrated in the same substrate is proposed. This platform is to be tested for 50 Giga-samples/sec analog-to-digital conversion, and be the prototype of a 100 Giga-samples/sec ADC.
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