Artificial intelligence for the detection of polyps or cancer with colon capsule endoscopy

Therapeutic Advances in Gastrointestinal Endoscopy

Review

Hagen Wenzek¹  Santi Segui²  Alexander R. Robertson³  Anastasios Koulaouzidis⁴ 

[1] CorporateHealth International, New York, NY, USA;Department of Mathematics and Computer Science, Universitat de Barcelona, Barcelona, Spain;Gastrointestinal Unit, Western General Hospital, Edinburgh, UK;null;

关键词: artificial intelligence;    cancer;    capsule endoscopy;    colon;    polyp;    software;    innovation;   

DOI  :  10.1177/26317745211020277

 received in 2021-03-18, accepted in 2021-05-05,  发布年份 2021

来源: Sage Journals

【 摘 要 】

Colorectal cancer is common and can be devastating, with long-term survival rates vastly improved by early diagnosis. Colon capsule endoscopy (CCE) is increasingly recognised as a reliable option for colonic surveillance, but widespread adoption has been slow for several reasons, including the time-consuming reading process of the CCE recording. Automated image recognition and artificial intelligence (AI) are appealing solutions in CCE. Through a review of the currently available and developmental technologies, we discuss how AI is poised to deliver at the forefront of CCE in the coming years. Current practice for CCE reporting often involves a two-step approach, with a ‘pre-reader’ and ‘validator’. This requires skilled and experienced readers with a significant time commitment. Therefore, CCE is well-positioned to reap the benefits of the ongoing digital innovation. This is likely to initially involve an automated AI check of finished CCE evaluations as a quality control measure. Once felt reliable, AI could be used in conjunction with a ‘pre-reader’, before adopting more of this role by sending provisional results and abnormal frames to the validator. With time, AI would be able to evaluate the findings more thoroughly and reduce the input required from human readers and ultimately autogenerate a highly accurate report and recommendation of therapy, if required, for any pathology identified. As with many medical fields reliant on image recognition, AI will be a welcome aid in CCE. Initially, this will be as an adjunct to ‘double-check’ that nothing has been missed, but with time will hopefully lead to a faster, more convenient diagnostic service for the screening population.

【 授权许可】

CC BY-NC   
© The Author(s) 2021

【 图 表 】

Figure 3.