Review – Diagnosis of Helicobacter pylori infection

Abstract

In this review, we present an overview of the main articles published in the field of Helicobacter pylori diagnosis in the past year. Key themes emerging in this area include rapid point-of-care testing and the use of artificial intelligence to enhance the efficacy of existing invasive diagnostic platforms. Studies in the field of endoscopy focussed on improving detection methods to diagnose H. pylori and associated diseases, targeted biopsy sampling, gastric juice analysis by Endofaster and the adoption of artificial intelligence in medical imaging. There have been some studies evaluating staining protocols for histopathology and exciting developments in the field of digital pathology for H. pylori detection and characterisation of inflammatory pathologies. Many articles have addressed the need for rapid, accurate, non-invasive point-of-care tests to analyse saliva or stool for the detection of H. pylori and/or its antimicrobial resistance. Finally, developments and considerations for the molecular detection of H. pylori and antimicrobial resistance using gastric samples are also discussed.

Keywords

• invasive
• non-invasive
• endoscopy
• histopathology
• artificial intelligence
• molecular test
• point-ofcare test
• antimicrobial susceptibility testing.