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with conventional biopsy specimens taken from the same site, including normal colonic mucosa, hyperplastic polyps, adenomatous polyps, chronic colitis, and colon cancer. Spectral analysis was carried out with a validated computerized model that used principal component analysis followed by linear discriminant analysis. Cross val-idation was carried out by using 60 % of the data as a ‘‘training set’ ’ and the remaining 40 % of the data as a ‘‘test set.’’ Results: A total of 483 spectra were analyzed (290 normal, 19 hyperplastic, 69 adenomatous polyps, 74 chronic colitis, and 31 colorectal cancer). The sensitivity and the specificity of differentiating adenomas from hyperplastic polyps was 84 % and 84%, respectively; for cancer from adenomatous polyps, 80 % and 75%, respectively; for co-litis from normal tissue, 77 % and 82%, respectively; and for dysplastic mucosa (from polyps) from colitis, 85% and 88%, respectively. Conclusions: ESS holds promise for differentiating colonic lesions with good accuracy and, therefore, is a po-tentially useful tool to make an instantaneous diagnosis during colonoscopy. It could prove a valuable aid for targeting biopsies in dysplasia surveillance in inflammatory bowel disease and for deciding which small polyps should be removed. (Gastrointest Endosc 2006;63:257-61.) Despite significant technologic improvements in vide

Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.468.8487
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