Lavender Color in Linked Color Imaging Enables Noninvasive Detection of Gastric Intestinal Metaplasia

Endoscopic diagnosis of Helicobacter pylori (H. pylori) infection, the most common cause of gastric cancer, is very important to clarify high-risk patients of gastric cancer for reducing morbidity and mortality of gastric cancer. Recently, the Kyoto classification of gastritis was developed based on the endoscopic characteristics of H. pylori infection-associated gastritis for clarifying H. pylori infection status and evaluating risk factors of gastric cancer. Recently, magnifying endoscopy with narrow-band imaging (NBI) has reported benefits of the accuracy and reproducibility of endoscopic diagnosis for H. pylori-related premalignant lesions. In addition to NBI, various types of image-enhanced endoscopies (IEEs) are available including autofluorescence imaging, blue laser imaging, and linked color imaging. This review focuses on understanding the clinical applications and the corresponding evidences shown to improve the diagnosis of gastritis based on Kyoto classification using currently available advanced technologies of IEEs.

Section: Iee For Diagnosis Of Kyoto Classification Of Gastritismentioning

confidence: 79%

Section: Bli and Lcimentioning

confidence: 94%

Can image‐enhanced endoscopy improve the diagnosis of Kyoto classification of gastritis in the clinical setting?

Dohi

Majima

Naito

et al. 2019

“…In a future study, we aim to include post‐eradication cases in training data and investigate the feature value of intestinal metaplasia particularly “map‐like redness”, which was reported to show a lavender color in the LCI mode …”

Section: Discussionmentioning

confidence: 99%

“…In a future study, we aim to include post-eradication cases in training data and investigate the feature value of intestinal metaplasia particularly "map-like redness", which was reported to show a lavender color in the LCI mode. 20 Currently, using the proposed AI system in doublechecking procedures in clinical practice is premature and this problem is not limited to our proposed system. In the future, it would be more suitable for developing countries, where the diagnosis and eradication of HP infection can be approved for patients with an endoscopic diagnosis of chronic gastritis.…”

Section: Discussionmentioning

confidence: 99%

Potential of automatic diagnosis system with linked color imaging for diagnosis of Helicobacter pylori infection

Yasuda

Hiroyasu

Hiwa

et al. 2019

Background and Aim It is necessary to establish universal methods for endoscopic diagnosis of Helicobacter pylori (HP) infection, such as computer‐aided diagnosis. In the present study, we propose a multistage diagnosis algorithm for HP infection. Methods The aims of this study are to: (i) to construct an interpretable automatic diagnostic system using a support vector machine for HP infection; and (ii) to compare the diagnosis capability of our artificial intelligence (AI) system with that of endoscopists. Presence of an HP infection determined through linked color imaging (LCI) was learned through machine learning. Trained classifiers automatically diagnosed HP‐positive and ‐negative patients examined using LCI. We retrospectively analyzed the new images from 105 consecutive patients; 42 were HP positive, 46 were post‐eradication, and 17 were uninfected. Five endoscopic images per case taken from different areas were read into the AI system, and used in the HP diagnosis. Results Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the diagnosis of HP infection using the AI system were 87.6%, 90.4%, 85.7%, 80.9%, and 93.1%, respectively. Accuracy of the AI system was higher than that of an inexperienced doctor, but there was no significant difference between the diagnosis of experienced physicians and the AI system. Conclusions The AI system can diagnose an HP infection with significant accuracy. There remains room for improvement, particularly for the diagnosis of post‐eradication patients. By learning more images and considering a diagnosis algorithm for post‐eradication patients, our new AI system will provide diagnostic support, particularly to inexperienced physicians.

“…However, although specific intestinal metaplasia can be diagnosed by white‐light endoscopy, non‐specific intestinal metaplasia is difficult to diagnose under white light. In contrast, image‐enhanced endoscopy, particularly by NBI 15 or LCI, 16 is useful for diagnosing non‐ specific intestinal metaplasia.…”

Section: [V] Risk Stratification After Endoscopic Examinationmentioning

confidence: 99%

Guidelines for endoscopic diagnosis of early gastric cancer

Yao

Uedo

Kamada

et al. 2020

137

144

The Japan Gastroenterological Endoscopy Society developed the Guideline for Endoscopic Diagnosis of Early Gastric Cancer based on scientific methods. Endoscopy for the diagnosis of early gastric cancer has been acknowledged as a useful and highly precise examination, and its use has become increasingly more common in recent years. However, the level of evidence in this field is low, and it is often necessary to determine recommendations based on expert consensus only. This clinical practice guideline consists of the following sections to provide the current guideline: [I] Risk stratification of gastric cancer before endoscopic examination, [II] Detection of early gastric cancer, [III] Qualitative diagnosis of early gastric cancer, [IV] Diagnosis to choose the therapeutic strategy for gastric cancer, [V] Risk stratification after endoscopic examination, and [VI] Surveillance of early gastric cancer.