Cheng-Long Wang, Xiang-Yu Sui, Yi Zeng, Jia-Yi Wu, Jun-Jie Xing, Song Zhang, Jia-Hui Wei, Kevin Chang, Yi-Ta Wu, Zhao-Shen Li, Sheng-Bing Zhao, Yu Bai, En-Da Yu
{"title":"Colorectal Polyp Size Measurement Faces Infinite Possibilities: Artificial Intelligence Is the Key.","authors":"Cheng-Long Wang, Xiang-Yu Sui, Yi Zeng, Jia-Yi Wu, Jun-Jie Xing, Song Zhang, Jia-Hui Wei, Kevin Chang, Yi-Ta Wu, Zhao-Shen Li, Sheng-Bing Zhao, Yu Bai, En-Da Yu","doi":"10.1159/000547299","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Colorectal neoplasia poses a severe health threat worldwide. The accurate measurement of polyp size is essential for risk stratification, selecting polypectomy techniques, and determining the surveillance interval.</p><p><strong>Summary: </strong>The methods routinely used for measuring polyp size, including objective ex vivo measurement, subjective visual estimation by an endoscopist, and objective precise measurement using endoscopic instruments, all have limitations. Therefore, the integration of artificial intelligence (AI) with endoscopy has been explored as a promising method for measuring the size of colorectal polyps. However, current AI systems are limited to endoscopic reference media or nonprospective real-time measurements. Consequently, AI-assisted endoscopy for precise, real-time automatic measurement of colorectal polyp size holds great promise for the future. Nevertheless, further extensive studies are necessary.</p><p><strong>Key messages: </strong>This review focuses on summarizing the advancements in colorectal polyp size research and further explores the potential of AI-assisted measurements.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"1-18"},"PeriodicalIF":3.0000,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digestion","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000547299","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Colorectal neoplasia poses a severe health threat worldwide. The accurate measurement of polyp size is essential for risk stratification, selecting polypectomy techniques, and determining the surveillance interval.
Summary: The methods routinely used for measuring polyp size, including objective ex vivo measurement, subjective visual estimation by an endoscopist, and objective precise measurement using endoscopic instruments, all have limitations. Therefore, the integration of artificial intelligence (AI) with endoscopy has been explored as a promising method for measuring the size of colorectal polyps. However, current AI systems are limited to endoscopic reference media or nonprospective real-time measurements. Consequently, AI-assisted endoscopy for precise, real-time automatic measurement of colorectal polyp size holds great promise for the future. Nevertheless, further extensive studies are necessary.
Key messages: This review focuses on summarizing the advancements in colorectal polyp size research and further explores the potential of AI-assisted measurements.
期刊介绍:
''Digestion'' concentrates on clinical research reports: in addition to editorials and reviews, the journal features sections on Stomach/Esophagus, Bowel, Neuro-Gastroenterology, Liver/Bile, Pancreas, Metabolism/Nutrition and Gastrointestinal Oncology. Papers cover physiology in humans, metabolic studies and clinical work on the etiology, diagnosis, and therapy of human diseases. It is thus especially cut out for gastroenterologists employed in hospitals and outpatient units. Moreover, the journal''s coverage of studies on the metabolism and effects of therapeutic drugs carries considerable value for clinicians and investigators beyond the immediate field of gastroenterology.