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Updated: Jun 19, 2026

Quantitative Fundus Autofluorescence for the Evaluation of Retinal Diseases
Published on: March 11, 2016
Autofluorescence imaging videoendoscopy in the diagnosis of chronic atrophic fundal gastritis
Takuya Inoue1, Noriya Uedo, Ryu Ishihara
1Department of Gastrointestinal Oncology, Osaka Medical Center for Cancer and Cardiovascular Disease, 1-3-3 Nakamichi, Higashinari-ku, Osaka 537-8511, Japan.
Purpose:
Diagnosis of chronic atrophic fundal gastritis (CAFG) is important to understand the pathogenesis of gastric diseases and assess the risk of gastric cancer. Autofluorescence imaging videoendoscopy (AFI) may enable the detection of mucosal features not apparent by conventional white-light endoscopy. The purpose of this study was to estimate the diagnostic ability of AFI in CAFG.
Methods:
A total of 77 patients were enrolled. Images of the gastric body in AFI and white-light mode were taken to assess the extent of gastritis, and biopsies were taken from green (n = 119) and purple (n = 146) mucosa in AFI images. The diagnostic accuracy of green mucosa for CAFG was investigated according to the Sydney system.
Results:
In per-patient analysis, the accuracy of green mucosa in patients with activity, inflammation, atrophy and intestinal metaplasia was 64, 93, 88 and 81%, respectively. In per-biopsy analysis, the accuracy for activity, inflammation, atrophy and intestinal metaplasia was 55, 62, 76 and 76%, respectively. Green areas in the gastric body exhibited more inflammation (p < 0.001), atrophy (p < 0.001) and intestinal metaplasia (p < 0.001), whereas purple areas rarely contained atrophy or intestinal metaplasia. The kappa statistics for inter- and intra-observer agreement of AFI on assessing the extent of CAFG were 0.66 and 0.47, while those for white-light endoscopy were 0.56 and 0.39.
Conclusions:
AFI could diagnose the extent of CAFG as a green area in the gastric body, with higher reproducibility compared with white-light endoscopy. Therefore, AFI may be a useful adjunct to endoscopy to identify patients at high risk of developing gastric cancer.
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