Recent Progress of Image-Enhanced Endoscopy for Upper Gastrointestinal Neoplasia and Associated Lesions.

Abstract

BACKGROUND:

The main therapeutic modality of early upper gastrointestinal neoplasms has shifted from surgery to endoscopic therapy. The role of endoscopy has also expanded not only for more accurate diagnosis of neoplasms but also for the determination of extent and depth of neoplasms with a combination of multiple electronically modified images acquired with image-enhanced endoscopy (IEE) for assessing the feasibility of endoscopic treatment.

SUMMARY:

These IEE with or without magnifying endoscopy including narrow-band imaging, blue laser imaging, and linked color imaging (LCI) using narrow-band light have greatly changed the diagnosis for upper gastrointestinal neoplasms. These modalities produce high color contrast between cancer and surrounding mucosa at distant views and clear visualization of surface and vessels at close-up observations. LCI shows purple color of intestinal metaplasia (IM) distinct from other inflammatory gastric mucosae and facilitates the recognition of early gastric cancers often surrounded by IM. Recently, ultrathin endoscopy has provided high-resolution images similar to standard-caliber endoscopy. In addition, these advanced IEEs that integrate computer-assisted artificial intelligence systems are marked and will improve our diagnostic performance for neoplasia in the future.

KEY MESSAGE:

New IEE with sufficient brightness and color contrast has increasingly been used based on accumulated evidence for early and accurate detection of neoplastic lesions. We provide recent articles relevant to endoscopic diagnosis with IEE on esophageal, gastric, and duodenal neoplasms. Endoscopic equipment that integrates artificial intelligence support system is now being introduced into routine clinical use and is expected to enhance early detection of neoplastic lesions.

• Authors: Yoshimasa Miura, Hiroyuki Osawa, Kentaro Sugano
• Journal: Digestive diseases (Basel, Switzerland) (Dig Dis) Vol. 42 Issue 2 Pg. 186-198 ( 2024) ISSN: 1421-9875 [Electronic] Switzerland
• PMID: 37952532 (Publication Type: Journal Article, Review)
• Copyright: © 2023 S. Karger AG, Basel.

Topics

• Humans
• Artificial Intelligence
• Endoscopy, Gastrointestinal (methods)
• Gastrointestinal Neoplasms (diagnostic imaging)
• Image Enhancement (methods)
• Stomach Neoplasms (pathology)