Study of capsule endoscopy delivery at scale through enhanced <scp>artificial intelligence‐enabled</scp> analysis (the CESCAIL study)

Lei, Ian Io; Tompkins, Katie; White, Elizabeth; Watson, Angus; Parsons, Nicholas R.; Noufaily, Angela; Seguí, Santi; Wenzek, Hagen; Badreldin, Rawya; Conlin, Abby; Arasaradnam, Ramesh P.

doi:10.1111/codi.16575

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…In 2022, the research conducted by Piccirelli et al investigating the diagnostic accuracy of Express View of IntroMedic achieved a 97% sensitivity and 100% specificity [75] . As AI polyp detection tools are commercially available for colonoscopy, such as FujiFilm's CADeye [76] and EndoBRAIN (Olympus), the imminent release and usage of AI tools for capsule endoscopy is expected with these promising results, which will likely only be further supported by future research such as the planned multi-centre CESCAIL study [77] [Table 4]. Li and Meng [24] Erosions and ulcers…”

Section: Polyps and Tumoursmentioning

confidence: 99%

Artificial intelligence in capsule endoscopy: development status and future expectations

George,

Tan,

Kovoor

et al. 2024

Mini-invasive Surg

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In this review, we aim to illustrate the state-of-the-art artificial intelligence (AI) applications in the field of capsule endoscopy. AI has made significant strides in gastrointestinal imaging, particularly in capsule endoscopy - a non-invasive procedure for capturing gastrointestinal tract images. However, manual analysis of capsule endoscopy videos is labour-intensive and error-prone, prompting the development of automated computational algorithms and AI models. While currently serving as a supplementary observer, AI has the capacity to evolve into an autonomous, integrated reading system, potentially significantly reducing capsule reading time while surpassing human accuracy. We searched Embase, Pubmed, Medline, and Cochrane databases from inception to 06 Jul 2023 for studies investigating the use of AI for capsule endoscopy and screened retrieved records for eligibility. Quantitative and qualitative data were extracted and synthesised to identify current themes. In the search, 824 articles were collected, and 291 duplicates and 31 abstracts were deleted. After a double-screening process and full-text review, 106 publications were included in the review. Themes pertaining to AI for capsule endoscopy included active gastrointestinal bleeding, erosions and ulcers, vascular lesions and angiodysplasias, polyps and tumours, inflammatory bowel disease, coeliac disease, hookworms, bowel prep assessment, and multiple lesion detection. This review provides current insights into the impact of AI on capsule endoscopy as of 2023. AI holds the potential for faster and precise readings and the prospect of autonomous image analysis. However, careful consideration of diagnostic requirements and potential challenges is crucial. The untapped potential within vision transformer technology hints at further evolution and even greater patient benefit.

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Section: Polyps and Tumoursmentioning

confidence: 99%

Artificial intelligence in capsule endoscopy: development status and future expectations

George,

Tan,

Kovoor

et al. 2024

Mini-invasive Surg

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“…CCE is also currently being evaluated for polyp detection utilizing Artificial intelligence to enhance pathways for utility ( Table 2 ) 55 , 56 :…”

Section: Use Of Cce In Clinical Practicementioning

confidence: 99%

Clinical utility of colon capsule endoscopy: a moving target?

Jalayeri Nia,

Arasaradnam,

Koulaouzidis

2023

Therap Adv Gastroenterol

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The purpose of this article is to provide an overview of white light colon capsule endoscopy’s current clinical application, concentrating on its most recent developments. Second-generation colon capsule endoscopy (CCE2) is approved by the FDA for use as an adjunctive test in patients with incomplete colonoscopy and within Europe in patients at average risk, those with incomplete colonoscopies or those unwilling to undergo conventional colonoscopies. Since the publication of European Society of GI Endoscopy guidelines on the use of CCE, there has been a significant increase in comparative studies on the diagnostic yield of CCE. This paper discusses CCE2 in further detail. It explains newly developed colon capsule system and the current status on the use of CCE, it also provides a comprehensive summary of systematic reviews on the implementation of CCE in colorectal cancer screening from a methodological perspective. Patients with ulcerative colitis can benefit from CCE2 in terms of assessing mucosal inflammation. As part of this review, performance of CCE2 for assessing disease severity in ulcerative colitis is compared with colonoscopy. Finally, an assessment if CCE can become a cost-effective clinical service overall.

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“…The stages of integrating artificial intelligence (AI) into the CCE process detailed by Robertson et al propose a scenario where AI could initially replace the pre-reading process and eventually take on the responsibility for analysing the entire CCE video prior to the clinician’s validation and reporting. 12 – 14 This proposal comprises of different stages. It suggested that the clinician would be presented with all the polyps’ images without a comprehensive review of the whole CCE video.…”

Section: Introductionmentioning

confidence: 99%

Rationalizing polyp matching criteria in colon capsule endoscopy: an international expert consensus through RAND (modified DELPHI) process

Lei,

Koulaouzidis,

Baatrup

et al. 2024

Therap Adv Gastroenterol

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Background: Colon capsule endoscopy (CCE) has gained momentum as an alternative modality for the investigation of the lower gastrointestinal tract. Of the few challenges that remain, the comparison and – eventually – matching of polyps at different timestamps leads to the potential for double reporting and can contribute to false-positive findings and inaccuracies. With the impending artificial intelligence integration, the risk of double reporting the same polyp due to the lack of information on spatial orientation underscores the necessity for establishing criteria for polyp matching. Objectives: This RAND/University of California, Los Angeles (modified Delphi) process aims to identify the key factors or components used to match polyps within a CCE video. This involves exploring the attributes of each factor to create comprehensive polyp-matching criteria based on international expert consensus. Design: A systematic qualitative study using surveys. Methods: A panel of 11 international CCE experts convened to assess a survey comprised of 60 statements. Participants anonymously rated statement appropriateness on a 1–9 scale (1–3: inappropriate, 4–6: uncertain and 7–9: appropriate). Following a virtual group discussion of the Round 1 results, a Round 2 survey was developed and completed before the final analysis. Results: The factors that were agreed to be essential for polyp matching include (1) timestamp, (2) polyp localization, (3) polyp vascular pattern, (4) polyp size, (5) time interval of the polyp appearance between the green and yellow camera, (6) surrounding tissue, (7) polyp morphology and (8) polyp surface and contour. When five or more factors are satisfied, it was agreed that the comparing polyps are likely the same polyp. Conclusion: This study has established the first complete criteria for polyp matching in CCE. While it might not provide a definitive solution for matching difficult, small and common polyps, these criteria serve as a framework to guide and facilitate the process of polyp-matching.

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Study of capsule endoscopy delivery at scale through enhanced artificial intelligence‐enabled analysis (the CESCAIL study)

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 6 publications

References 17 publications

Artificial intelligence in capsule endoscopy: development status and future expectations

Artificial intelligence in capsule endoscopy: development status and future expectations

Clinical utility of colon capsule endoscopy: a moving target?

Rationalizing polyp matching criteria in colon capsule endoscopy: an international expert consensus through RAND (modified DELPHI) process

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