Determination of gastric atrophy with artificial intelligence compared to the assessments of the modified Kyoto and OLGA classifications

Yasuhiro Kodaka; Seiji Futagami; Yoshiyuki Watanabe; Satoki Shichijo; Noriya Uedo; Hiroyuki Aono; Kumiko Kirita; Yusuke Kato; Nobue Ueki; Shuhei Agawa; Hiroshi Yamawaki; Katsuhiko Iwakiri; Tomohiro Tada

doi:10.1002/jgh3.12810

Determination of gastric atrophy with artificial intelligence compared to the assessments of the modified Kyoto and OLGA classifications

JGH Open. 2022 Aug 26;6(10):704-710. doi: 10.1002/jgh3.12810. eCollection 2022 Oct.

Authors

Affiliations

¹ Division of Gastroenterology Nippon Medical School Tokyo Japan.
² Department of Gastrointestinal Oncology Osaka International Cancer Institute Osaka Japan.
³ AI Medical Service Inc. Tokyo Japan.
⁴ Tada Tomohiro Institute of Gastroenterology and Proctology Saitama Japan.

Abstract

Background and aim: Gastric atrophy is a precancerous lesion. We aimed to clarify whether gastric atrophy determined by artificial intelligence (AI) correlates with the diagnosis made by expert endoscopists using several endoscopic classifications, the Operative Link on Gastritis Assessment (OLGA) classification based on histological findings, and genotypes associated with gastric atrophy and cancer.

Methods: Two hundred seventy Helicobacter pylori-positive outpatients were enrolled. All patients' endoscopy data were retrospectively evaluated based on the Kimura-Takemoto, modified Kyoto, and OLGA classifications. The AI-trained neural network generated a continuous number between 0 and 1 for gastric atrophy. Nucleotide variance of some candidate genes was confirmed or selectively assessed for a variety of genotypes, including the COX-21195, IL-1β 511, and mPGES-1 genotypes.

Results: There were significant correlations between determinations of gastric atrophy by AI and by expert endoscopists using not only the Kimura-Takemoto classification (P < 0.001), but also the modified Kyoto classification (P = 0.046 and P < 0.001 for the two criteria). Moreover, there was a significant correlation with the OLGA classification (P = 0.009). Nucleotide variance of the COX-2, IL-1β, and mPGES-1genes was not significantly associated with gastric atrophy determined by AI. The area under the curve values of the combinations of AI and the modified Kyoto classification (0.746) and AI and the OLGA classification (0.675) were higher than in AI alone (0.665).

Conclusion: Combinations of AI and the modified Kyoto classification or of AI and the OLGA classification could be useful tools for evaluating gastric atrophy in patients with H. pylori infection as the risk of gastric cancer.

Keywords: Kyoto classification; Operative Link on Gastritis Assessment classification; artificial intelligence; gastric atrophy.