The Library
Study of capsule endoscopy delivery at scale through enhanced artificial intelligence-enabled analysis (the CESCAIL study)
Tools
Lei, Ian Io, Tompkins, Katie, White, Elizabeth, Watson, Angus, Parsons, Angus, Parsons, Nicholas R., Noufaily, Angela, Segui, Santi, Wenzek, Hagen, Badreldin, Rawya, Conlin, Abby and Arasaradnam, Ramesh P. (2023) Study of capsule endoscopy delivery at scale through enhanced artificial intelligence-enabled analysis (the CESCAIL study). Colorectal Disease, 25 (7). pp. 1498-1505. doi:10.1111/codi.16575 ISSN 1462-8910.
|
PDF
Colorectal Disease - 2023 - Lei - Study of capsule endoscopy delivery at scale through enhanced artificial.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1977Kb) | Preview |
|
PDF
WRAP-capsule-endoscopy-delivery-scale-through-enhanced-AI-analysis-study-Lei-2023.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (570Kb) |
Official URL: https://doi.org/10.1111/codi.16575
Abstract
Aim
Lower gastrointestinal (GI) diagnostics have been facing relentless capacity constraints for many years, even before the COVID-19 era. Restrictions from the COVID pandemic have resulted in a significant backlog in lower GI diagnostics. Given recent developments in deep neural networks (DNNs) and the application of artificial intelligence (AI) in endoscopy, automating capsule video analysis is now within reach. Comparable to the efficiency and accuracy of AI applications in small bowel capsule endoscopy, AI in colon capsule analysis will also improve the efficiency of video reading and address the relentless demand on lower GI services. The aim of the CESCAIL study is to determine the feasibility, accuracy and productivity of AI-enabled analysis tools (AiSPEED) for polyp detection compared with the ‘gold standard’: a conventional care pathway with clinician analysis.
Method
This multi-centre, diagnostic accuracy study aims to recruit 674 participants retrospectively and prospectively from centres conducting colon capsule endoscopy (CCE) as part of their standard care pathway. After the study participants have undergone CCE, the colon capsule videos will be uploaded onto two different pathways: AI-enabled video analysis and the gold standard conventional clinician analysis pathway. The reports generated from both pathways will be compared for accuracy (sensitivity and specificity). The reading time can only be compared in the prospective cohort. In addition to validating the AI tool, this study will also provide observational data concerning its use to assess the pathway execution in real-world performance.
Results
The study is currently recruiting participants at multiple centres within the United Kingdom and is at the stage of collecting data.
Conclusion
This standard diagnostic accuracy study carries no additional risk to patients as it does not affect the standard care pathway, and hence patient care remains unaffected.
Item Type: | Journal Article | ||||||||
---|---|---|---|---|---|---|---|---|---|
Subjects: | Q Science > Q Science (General) R Medicine > R Medicine (General) R Medicine > RA Public aspects of medicine R Medicine > RC Internal medicine |
||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School | ||||||||
Library of Congress Subject Headings (LCSH): | Colon (Anatomy) -- Cancer -- Diagnosis, Rectum -- Cancer -- Diagnosis , Medical screening, Capsule endoscopy, Artificial intelligence -- Medical applications | ||||||||
Journal or Publication Title: | Colorectal Disease | ||||||||
Publisher: | Wiley | ||||||||
ISSN: | 1462-8910 | ||||||||
Official Date: | July 2023 | ||||||||
Dates: |
|
||||||||
Volume: | 25 | ||||||||
Number: | 7 | ||||||||
Page Range: | pp. 1498-1505 | ||||||||
DOI: | 10.1111/codi.16575 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||
Date of first compliant deposit: | 24 March 2023 | ||||||||
Date of first compliant Open Access: | 25 May 2023 | ||||||||
RIOXX Funder/Project Grant: |
|
||||||||
Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year