Jennifer Koh, Miranda V. Shum, Joo Ha Hwang, Robert J. Huang
{"title":"Detection and surveillance of gastric cancer precursors: evolving guidelines and technologies","authors":"Jennifer Koh, Miranda V. Shum, Joo Ha Hwang, Robert J. Huang","doi":"10.21037/ales-23-13","DOIUrl":null,"url":null,"abstract":": Non-cardiac gastric adenocarcinoma (NCGA) remains a leading source of global morbidity and mortality. Despite its lower incidence in the United States and Western Europe, the overall poor survival and prognosis from this cancer suggest a need for earlier detection. NCGA develops through a well-known stepwise progression of precursor lesions, including chronic gastritis, atrophic gastritis, intestinal metaplasia, and dysplasia. Identification and surveillance of high-risk individuals carrying these precursors may be one important avenue to improve NCGA outcomes through earlier detection. In addition, identifying NCGA precursors creates an opportunity for definitive management with early endoscopic resection, and therefore a potential for reduction in cancer morbidity and mortality. This review has two main objectives. The first aim is to describe and evaluate various imaging technologies that are currently used to aid and improve the endoscopic detection of NCGA precursor lesions. These modalities include image-enhanced endoscopy (both dye-based and virtual), confocal laser endomicroscopy, and auto-fluorescence imaging. The second aim is to appraise current surveillance strategies for individuals carrying precursor lesions, with an emphasis on synthesizing recommendations from several recent surveillance guidelines published in the United States and Europe. In this review, we also highlight future innovative technologies and directions, including the utilization of artificial intelligence for rapid lesion recognition and molecular-based individual risk stratification.","PeriodicalId":8024,"journal":{"name":"Annals of Laparoscopic and Endoscopic Surgery","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Laparoscopic and Endoscopic Surgery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/ales-23-13","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0
Abstract
: Non-cardiac gastric adenocarcinoma (NCGA) remains a leading source of global morbidity and mortality. Despite its lower incidence in the United States and Western Europe, the overall poor survival and prognosis from this cancer suggest a need for earlier detection. NCGA develops through a well-known stepwise progression of precursor lesions, including chronic gastritis, atrophic gastritis, intestinal metaplasia, and dysplasia. Identification and surveillance of high-risk individuals carrying these precursors may be one important avenue to improve NCGA outcomes through earlier detection. In addition, identifying NCGA precursors creates an opportunity for definitive management with early endoscopic resection, and therefore a potential for reduction in cancer morbidity and mortality. This review has two main objectives. The first aim is to describe and evaluate various imaging technologies that are currently used to aid and improve the endoscopic detection of NCGA precursor lesions. These modalities include image-enhanced endoscopy (both dye-based and virtual), confocal laser endomicroscopy, and auto-fluorescence imaging. The second aim is to appraise current surveillance strategies for individuals carrying precursor lesions, with an emphasis on synthesizing recommendations from several recent surveillance guidelines published in the United States and Europe. In this review, we also highlight future innovative technologies and directions, including the utilization of artificial intelligence for rapid lesion recognition and molecular-based individual risk stratification.