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

NCT04676308 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1300

Last updated 2022-09-14

No results posted yet for this study

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

Interventions

OTHER

Artificial Intelligence

Artificial intelligence

Sponsors & Collaborators

  • Istituto Clinico Humanitas

    lead OTHER

Eligibility

Min Age
40 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-07-01
Primary Completion
2022-05-31
Completion
2022-05-31

Countries

  • Italy

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04676308 on ClinicalTrials.gov