BACKGROUND:Laser-induced fluorescence spectroscopy has the potential to detect colonic dysplasia in vivo. However, previous studies have limited their analyses to multivariate regression techniques and unblinded retrospective evaluation. The purpose of this study was to develop a probability-based algorithm to detect colonic dysplasia using laser-induced fluorescence spectroscopy and to evaluate it in a blinded manner. METHODS:Fluorescence spectra were collected from normal mucosa and colonic polyps during colonoscopy using 370 nm excitation. Tissue was classified as normal, hyperplastic, or adenomatous by histologic examination. Preliminary data was used to devise an algorithm to differentiate tissue type based on probability distributions of the fluorescence intensity at 460 nm and the ratio of the intensity at 680 nm to that at 600 nm. The algorithm was then tested in a blinded fashion. RESULTS: The algorithm correctly determined the tissue type in 88% of cases, equal to the agreement of independent pathologists. Sensitivity, specificity, and positive predictive value for the detection of dysplasia was 90%, 95%, and 90%, respectively. CONCLUSIONS:Dysplasia was detected in vivo using fluorescence spectroscopy and a probability-based algorithm. This method may form the basis for a new surveillance technique for patients with increased risk for dysplastic transformation.
RCT Entities:
BACKGROUND: Laser-induced fluorescence spectroscopy has the potential to detect colonic dysplasia in vivo. However, previous studies have limited their analyses to multivariate regression techniques and unblinded retrospective evaluation. The purpose of this study was to develop a probability-based algorithm to detect colonic dysplasia using laser-induced fluorescence spectroscopy and to evaluate it in a blinded manner. METHODS: Fluorescence spectra were collected from normal mucosa and colonic polyps during colonoscopy using 370 nm excitation. Tissue was classified as normal, hyperplastic, or adenomatous by histologic examination. Preliminary data was used to devise an algorithm to differentiate tissue type based on probability distributions of the fluorescence intensity at 460 nm and the ratio of the intensity at 680 nm to that at 600 nm. The algorithm was then tested in a blinded fashion. RESULTS: The algorithm correctly determined the tissue type in 88% of cases, equal to the agreement of independent pathologists. Sensitivity, specificity, and positive predictive value for the detection of dysplasia was 90%, 95%, and 90%, respectively. CONCLUSIONS:Dysplasia was detected in vivo using fluorescence spectroscopy and a probability-based algorithm. This method may form the basis for a new surveillance technique for patients with increased risk for dysplastic transformation.
Authors: Sergio Coda; Alex J Thompson; Gordon T Kennedy; Kim L Roche; Lakshmana Ayaru; Devinder S Bansi; Gordon W Stamp; Andrew V Thillainayagam; Paul M W French; Chris Dunsby Journal: Biomed Opt Express Date: 2014-01-16 Impact factor: 3.732