Endoscopic fluorescence detection of high-grade dysplasia in Barrett's esophagus.

Journal Article (Clinical Trial;Journal Article)

Background & aims

Early detection and treatment of esophageal cancer in Barrett's esophagus may improve patient survival if dysplasia is effectively detected at endoscopy. Typically, four-quadrant pinch biopsy specimens are taken at 2-cm intervals. This study was conducted to determine whether laser-induced fluorescence spectroscopy could be used to detect high-grade dysplasia in patients with Barrett's esophagus.

Methods

Four hundred ten-naonometer laser light was used to induce autofluorescence of Barrett's mucosa in 36 patients. The spectra were analyzed using the differential normalized fluorescence (DNF) index technique to differentiate high-grade dysplasia from either low-grade or nondysplastic mucosa. Each spectrum was classified as either premalignant or benign using two different DNF indices.

Results

Analysis of the fluorescence spectra from all patients collectively using the DNF intensity at 480 nm (DNF480) index showed that 96% of nondysplastic Barrett's esophagus samples were classified as benign, all low-grade dysplasia samples as benign, 90% of high-grade dysplasia samples as premalignant, and 28% of low-grade with focal high-grade dysplasia samples as premalignant. Using the two DNF indices concurrently, all patients with any high-grade dysplasia were classified correctly.

Conclusions

Laser-induced fluorescence spectroscopy has great potential to detect high-grade dysplasia in Barrett's esophagus when using the DNF technique.

Full Text

Duke Authors

Cited Authors

  • Panjehpour, M; Overholt, BF; Vo-Dinh, T; Haggitt, RC; Edwards, DH; Buckley, FP

Published Date

  • July 1996

Published In

Volume / Issue

  • 111 / 1

Start / End Page

  • 93 - 101

PubMed ID

  • 8698231

Electronic International Standard Serial Number (EISSN)

  • 1528-0012

International Standard Serial Number (ISSN)

  • 0016-5085

Digital Object Identifier (DOI)

  • 10.1053/gast.1996.v111.pm8698231

Language

  • eng