The CERTAIN Study: Combining Endo-cuff in a Randomized Trial for Artificial Intelligence Navigation

NCT ID: NCT04676308

Last Updated: 2022-09-14

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 1300 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-07-01
• Study Completion Date: 2022-05-31

Brief Summary

Colonoscopy is clinically used as the gold standard for detection of colon cancer (CRC) and removal of adenomatous polyps. Despite the success of colonoscopy in reducing cancer-related deaths, there exists a disappointing level of adenomas missed at colonoscopy. "Back-to-back" colonoscopies have indicated significant miss rates of 27% for small adenomas (< 5 mm) and 6% for adenomas of more than 10 mm in diameter. Studies performing both CT colonography and colonoscopy estimate that the colonoscopy miss rate for polyps over 10 mm in size may be as high as 12%. The clinical importance of missed lesions should be emphasized because these lesions may ultimately progress to CRC. Limitations in human visual perception and other human biases such as fatigue, distraction, level of alertness during examination increases recognition errors and way of mitigating them may be the key to improve polyp detection and further reduction in mortality from CRC.

Recent advances in artificial intelligence (AI), deep learning (DL), and computer vision have permitted to develop several AI platforms which have already proved their efficacy in increasing adenoma detection during colonoscopy9,10. As a matter of fact, the improvement in detection due to AI systems is only related to the increased capacity of detecting lesions within the visual field, that is dependent on the amount of mucosa exposed by the endoscopist during the scope withdrawal.

Increasing the mucosa exposure would theoretically be a complementary strategy to further improve polyps detection. A number of distal attachments have been tested to increase the mucosal exposure by flattening mucosal folds, including a transparent cap, cuff or rings. The additional diagnostic yield obtained by the second generation of cuff (Endocuff Vision; Olympus America, Center Valley, Pa, USA) was recently investigated by a meta-analysis of randomized controlled trials, showing a significant improvement in adenoma detection rate, and adenomas per colonoscopy, with a reduction in the mean withdrawal time without any increase in adverse events compared with standard high-definition colonoscopy without any distal attachment.

In conclusion, technologies providing either mucosal image enhancement (Artificial Intelligence assisted colonoscopy) or mucosal exposure device (Endocuff Vision assisted colonoscopy) significantly improved adenoma detection rate (ADR). However, the diagnostic yield obtained by combining the different strategies is still unknown.

Conditions

Artificial Intelligence

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

AI arm

Standard colonoscopy with Artificial Intelligence-GI GeniusTM

Artificial Intelligence

Intervention Type: OTHER

Artificial intelligence

Cuff arm

Endo-cuff Vision aided colonoscopy with Artificial Intelligence -GI GeniusTM

Artificial Intelligence

Intervention Type: OTHER

Artificial intelligence

Interventions

Artificial Intelligence

Artificial intelligence

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• subjects undergoing a colonoscopy for gastrointestinal symptoms, fecal immunohistochemical test positivity, primary screening or post-polypectomy surveillance

Exclusion Criteria

• subjects with personal history of CRC, or IBD.
• subjects affected with genetic mutations such as Lynch syndrome or Familiar Adenomatous Polyposis.
• patients with inadequate bowel preparation (defined as Boston Bowel Preparation Scale > 2 in any colonic segment).
• patients with previous colonic resection.
• patients on antithrombotic therapy, precluding polyp resection.
• patients with history of colonic strictures, precluding ECV use.
• patients who were not able or refused to give informed written consent.

• Minimum Eligible Age: 40 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Istituto Clinico Humanitas

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Endoscopy Unit, Humanitas Research Hospital

Rozzano, Milano, Italy

Countries

Italy

References

Spadaccini M, Hassan C, Rondonotti E, Antonelli G, Andrisani G, Lollo G, Auriemma F, Iacopini F, Facciorusso A, Maselli R, Fugazza A, Bambina Bergna IM, Cereatti F, Mangiavillano B, Radaelli F, Di Matteo F, Gross SA, Sharma P, Mori Y, Bretthauer M, Rex DK, Repici A; CERTAIN Study Group. Combination of Mucosa-Exposure Device and Computer-Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial. Gastroenterology. 2023 Jul;165(1):244-251.e3. doi: 10.1053/j.gastro.2023.03.237. Epub 2023 Apr 14.

Reference Type: DERIVED

PMID: 37061169 (View on PubMed)

Other Identifiers

1766

Identifier Type: -

Identifier Source: org_study_id