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NCT04676308: CERTAIN

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

Completed Last updated 14 September 2022
What this trial tests

trial testing Artificial Intelligence in Artificial Intelligence in 1,300 participants. Completed in 31 May 2022.

Timeline
1 July 2021
Primary endpoint
31 May 2022
31 May 2022

Quick facts

Lead sponsorIstituto Clinico Humanitas
StatusCompleted
Study typeOBSERVATIONAL
Enrollment1,300
Start date1 July 2021
Primary completion31 May 2022
Estimated completion31 May 2022
Sites1 location across Italy

Drugs / interventions tested

Conditions studied

Sponsor

Istituto Clinico Humanitas

Who can join

Adults 40 to 80, any sex, with Artificial Intelligence. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

2 peer-reviewed publications reference this trial (live from Europe PMC):

  1. Combination of Mucosa-Exposure Device and Computer-Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial.
    Spadaccini M, Hassan C, Rondonotti E, Antonelli G, et al · · 2023 · cited 40× · PMID 37061169 · DOI 10.1053/j.gastro.2023.03.237
  2. Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening.
    Spadaccini M, Massimi D, Mori Y, Alfarone L, et al · · 2023 · cited 8× · PMID 36980409 · DOI 10.3390/diagnostics13061102

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Other trials of Artificial Intelligence

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Data sources for this page

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