BACKGROUND AND OBJECTIVES: The first objective of this study was to evaluate the performance of fluorescence spectroscopy for diagnosing pre-cancers in stratified squamous epithelial tissues in vivo using two different probe geometries with (1) overlapping versus (2) non-overlapping illumination and collection areas on the tissue surface. Probe (1) and probe (2) are preferentially sensitive to the fluorescence originating from the tissue surface and sub-surface tissue depths, respectively. The second objective was to design a novel, angled illumination fiber-optic probe to maximally exploit the depth-dependent fluorescence properties of epithelial tissues. STUDY DESIGN/ MATERIALS AND METHODS: In the first study, spectra were measured from epithelial pre-cancers and normal tissues in the hamster cheek pouch and analyzed with a non-parametric classification algorithm. In the second study, Monte Carlo modeling was used to simulate fluorescence measurements from an epithelial tissue model with the angled illumination probe. RESULTS: An unbiased classification algorithm based on spectra measured with probes (1) and (2), classified pre-cancerous and normal tissues with 78 and 94% accuracy, respectively. The angled illumination probe design provides the capability to detect fluorescence from a wide range of tissue depths in an epithelial tissue model. CONCLUSIONS: The first study demonstrates that fluorescence originating from sub-surface tissue depths (probe (2)) is more diagnostic than fluorescence originating from the tissue surface (probe (1)) in the hamster cheek pouch model. However in general, it is difficult to know a priori the optimal probe geometry for pre-cancer detection in a particular epithelial tissue model. The angled illumination probe provides the capability to measure tissue fluorescence selectively from different depths within epithelial tissues, thus obviating the need to select a single optimal probe design for the fluorescence-based diagnosis of epithelial pre-cancers. Copyright 2004 Wiley-Liss, Inc.
BACKGROUND AND OBJECTIVES: The first objective of this study was to evaluate the performance of fluorescence spectroscopy for diagnosing pre-cancers in stratified squamous epithelial tissues in vivo using two different probe geometries with (1) overlapping versus (2) non-overlapping illumination and collection areas on the tissue surface. Probe (1) and probe (2) are preferentially sensitive to the fluorescence originating from the tissue surface and sub-surface tissue depths, respectively. The second objective was to design a novel, angled illumination fiber-optic probe to maximally exploit the depth-dependent fluorescence properties of epithelial tissues. STUDY DESIGN/ MATERIALS AND METHODS: In the first study, spectra were measured from epithelial pre-cancers and normal tissues in the hamster cheek pouch and analyzed with a non-parametric classification algorithm. In the second study, Monte Carlo modeling was used to simulate fluorescence measurements from an epithelial tissue model with the angled illumination probe. RESULTS: An unbiased classification algorithm based on spectra measured with probes (1) and (2), classified pre-cancerous and normal tissues with 78 and 94% accuracy, respectively. The angled illumination probe design provides the capability to detect fluorescence from a wide range of tissue depths in an epithelial tissue model. CONCLUSIONS: The first study demonstrates that fluorescence originating from sub-surface tissue depths (probe (2)) is more diagnostic than fluorescence originating from the tissue surface (probe (1)) in the hamster cheek pouch model. However in general, it is difficult to know a priori the optimal probe geometry for pre-cancer detection in a particular epithelial tissue model. The angled illumination probe provides the capability to measure tissue fluorescence selectively from different depths within epithelial tissues, thus obviating the need to select a single optimal probe design for the fluorescence-based diagnosis of epithelial pre-cancers. Copyright 2004 Wiley-Liss, Inc.
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