Review
Oncology
Edward Young, Louisa Edwards, Rajvinder Singh
Summary: Artificial intelligence (AI) systems have become increasingly available in the field of endoscopy, particularly in colonoscopy. This comprehensive review focuses on the application of AI in detecting and characterizing colorectal polyps, with the goal of improving the efficacy of colorectal cancer screening and prevention. AI-driven algorithms show potential in addressing the challenge of overlooked polyps and empowering gastroenterologists to accurately characterize polyps without extensive training in advanced mucosal imaging. By integrating AI technologies into routine colonoscopy, the detection and characterization of polyps can be advanced, potentially leading to more effective colorectal cancer screening and prevention.
Article
Surgery
Frederick H. Koh, Jasmine Ladlad, Eng-Kiong Teo, Cui-Li Lin, Fung-Joon Foo
Summary: This study evaluates the performance of real-time AI-aided colonoscopy in the detection of colonic polyps. The results show that using real-time AI-aided colonoscopy can improve the detection rate of colonic polyps, even for experienced endoscopists. This will improve the quality of colonoscopy.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Review
Health Care Sciences & Services
Scarlet Nazarian, Ben Glover, Hutan Ashrafian, Ara Darzi, Julian Teare
Summary: Artificial intelligence technologies show great potential in improving the detection and characterization of colorectal polyps, ultimately reducing the incidence of colorectal cancer. The current generation of AI-based systems demonstrate impressive accuracy in detecting and characterizing colorectal polyps.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Review
Medicine, General & Internal
Hui Pan, Mingyan Cai, Qi Liao, Yong Jiang, Yige Liu, Xiaolong Zhuang, Ying Yu
Summary: Based on a systematic review of multiple meta-analyses, this study concludes that artificial intelligence-aided colonoscopy (AIC) is superior to conventional colonoscopy (CC) in the detection of polyps and adenomas, especially in terms of polyp detection rate and adenoma detection rate.
FRONTIERS IN MEDICINE
(2022)
Review
Gastroenterology & Hepatology
Jianglei Li, Jiaxi Lu, Jin Yan, Yuyong Tan, Deliang Liu
Summary: This study found that artificial intelligence improves polyp and adenoma detection rates in colonoscopy, and better bowel preparation and training for detecting small polyps and adenomas can also enhance detection rates.
EUROPEAN JOURNAL OF GASTROENTEROLOGY & HEPATOLOGY
(2021)
Article
Health Care Sciences & Services
Ka Luen Thomas Lui, Sze Hang Kevin Liu, Kathy Leung, Joseph T. Wu, Ann G. Zauber, Wai Keung Leung
Summary: The widespread adoption of computer-aided detection (CADe) in detecting colorectal polyps would result in shorter surveillance intervals for patients, particularly according to the US Multi-Society Task Force on Colorectal Cancer (USMSTF) guideline. Based on simulation, CADe application would lead to approximately 19.1% and 1.9% of patients requiring shorter surveillance intervals, as recommended by the USMSTF and European Society of Gastrointestinal Endoscopy (ESGE) guidelines, respectively. Specifically, all or 2.7% of patients initially scheduled for 3-5 years of surveillance would have their intervals shortened to 3 years, according to the USMSTF guideline.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Review
Surgery
Shuen-Ern Chin, Fang-Ting Wan, Jasmine Ladlad, Koy-Min Chue, Eng-Kiong Teo, Cui-Li Lin, Fung-Joon H. Foo, Frederick Koh
Summary: This study evaluates the 1-year performance of AI-aided colonoscopy, showing that it is a cost-effective means of improving colonoscopy quality and advancing colorectal cancer screening in Singapore.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Review
Gastroenterology & Hepatology
Sagar Shah, Nathan Park, Nabil El Hage Chehade, Anastasia Chahine, Marc Monachese, Amelie Tiritilli, Zain Moosvi, Ronald Ortizo, Jason Samarasena
Summary: This study demonstrates that computer-aided colonoscopy (CAC) can effectively reduce the miss rates of adenomas and sessile serrated lesions, increase the adenoma detection rate, and improve the detection of adenomas larger than 10 mm.
JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY
(2023)
Review
Medicine, General & Internal
Lei Shao, Xinzong Yan, Chengjiang Liu, Can Guo, Baojia Cai
Summary: Artificial intelligence-assisted colonoscopy (AIAC) can effectively reduce the missed detection rate and improve the detection rate of adenoma, especially for small adenomas. However, more in-depth studies are needed to improve the clinical application of AIAC.
Review
Medicine, General & Internal
Shenghan Lou, Fenqi Du, Wenjie Song, Yixiu Xia, Xinyu Yue, Da Yang, Binbin Cui, Yanlong Liu, Peng Han
Summary: AI-aided colonoscopy significantly enhances the detection of colorectal neoplasia by reducing the miss rate. However, future studies should focus on evaluating the cost-effectiveness and long-term benefits of AI-aided colonoscopy in reducing cancer incidence.
Editorial Material
Surgery
Sarah Tham, Siok-Peng SKH Endoscopy Ctr, Frederick H. Koh, Eng-Kiong Teo, Cui-Li Lin, Fung-Joon Foo
Summary: There is a wide variation in endoscopists' knowledge and perceptions of artificial intelligence (AI). While most endoscopists are optimistic about AI's capabilities in administrative and clinical tasks, they are reserved about its ability to provide personalized and empathetic care. Acceptance of AI-aided colonoscopy systems is more related to endoscopists' experience with using the program rather than their general knowledge or perceptions of AI.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Article
Gastroenterology & Hepatology
Jooyoung Lee, Jung Ho Bae, Su Jin Chung, Hae Yeon Kang, Seung Joo Kang, Min-Sun Kwak, Ji Yeon Seo, Ji Hyun Song, Sun Young Yang, Jong In Yang, Seon Hee Lim, Jeong Yoon Yim, Joo Hyun Lim, Goh Eun Chung, Eun Hyo Jin, Ji Min Choi, Yoo Min Han, Joo Sung Kim
Summary: Comprehensive optical diagnosis training with WASP classification significantly increased the overall SDR of expert endoscopists, while it did not have a significant impact on ADR.
DIGESTIVE ENDOSCOPY
(2022)
Article
Medical Informatics
Mariusz Madalinski, Roger Prudham
Summary: By utilizing artificial intelligence methods to improve the quality of colonoscopy, all polyps with malignant potential can be removed, reducing cancer incidence. The integration of deep learning methodology with CADe systems has the potential to increase adenoma detection rates in bowel cancer screening.
JMIR MEDICAL INFORMATICS
(2021)
Review
Gastroenterology & Hepatology
Carola Rotermund, Roupen Djinbachian, Mahsa Taghiakbari, Markus D. Enderle, Axel Eickhoff, Daniel von Renteln
Summary: This study conducted a systematic review and meta-analysis to analyze the local recurrence rates (LRRs) of large colonic polyps. The results showed that endoscopic submucosal dissection (ESD) and endoscopic mucosal resection (EMR) with routine margin ablation significantly reduced LRR compared to standard EMR. These techniques should be considered as the standard for endoscopic removal of large colorectal polyps.
WORLD JOURNAL OF GASTROENTEROLOGY
(2022)
Article
Gastroenterology & Hepatology
Thomas J. Lux, Michael Banck, Zita Sassmannshausen, Joel Troya, Adrian Krenzer, Daniel Fitting, Boban Sudarevic, Wolfram G. Zoller, Frank Puppe, Alexander Meining, Alexander Hann
Summary: This study presents the first clinical experiences of a publicly available CADe system named EndoMind for data acquisition and real-time polyp detection. The system showed high usability and accuracy when used with different endoscopy processors in clinical routine.
INTERNATIONAL JOURNAL OF COLORECTAL DISEASE
(2022)
