Artificial Intelligence Aid Systems and Endocuff in Colorectal Adenoma Detection

Adenoma Detection Rate Clinical Trial

— CUFFAID  

Official title:

Computer-assisted Adenoma Detection Coloscopy With Endo-AID Artificial Intelligence System and Endocuff Versus Endocuff Assisted Colonoscopy: a Randomized Controlled Trial

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05141773
• Other study ID #: Computer aid colonoscopy
• Status: Not yet recruiting
• Phase: N/A
• Start date: November 22, 2021
• Est. completion date: February 28, 2022

Study information

• Verified date: November 2021
• Source: Hospital Universitario de Canarias
• Contact: Antonio Z Gimeno García, MD, PhD
• Phone: 34-922678039
• Email: antozeben[@]gmail.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The main purpose of the study to evaluate the usefulness of the Endo-AID artificial intelligence system combined with endocuff compared with endocuff in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy. The secondary aims were: - To evaluate the benefit of Endo-AID and endocuff in adenoma detection rate by comparing endoscopists with high and low adenoma detection rate. - To evaluate serrated detection rate, advanced adenoma detection rate, adenoma detection rate according to the size (<= 5mm, 6-9mm,> = 10mm) and number of adenomas by colonoscopy. Stratification by location and morphology.

Description:

Guidelines have been established regarding artificial intelligence (AI) applied to gastrointestinal endoscopy. Regarding the priority uses for their development, there are applications that improve vision, placing computer-assisted lesion detection (CADe) as one of the most necessary priorities, given the importance of colorectal cancer screening (CRC) and post-polypectomy surveillance. The evaluation of these systems in different clinical practices and patient groups has been recommend. In this regard, studies in the western population are limited and have been carried out by expert endoscopists. It has not been evaluated comparing with other strategies such as add-on devices. In addition, there are no studies with the recent CADe Endo-AID system (Olympus Corp. Tokyo). The main purpose of the study is to evaluate the usefulness of the Endo-AID artificial intelligence system with endocuff in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy compared with standard colonoscopy with endocuff. In addition, the benefit of the CADe system will be assessed according to the endoscopist ADR. A randomized controlled trial will be carried out in consecutive outpatients meeting the inclusion criteria and none of the exclusion criteria. Patients with be randomized to one of the two groups: CADe system with endocuff and standard colonoscopy with endocuff.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 696
• Est. completion date: February 28, 2022
• Est. primary completion date: February 28, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Age = 18 years.
• Patients referred for outpatient colonoscopy

Exclusion Criteria:

• Colonic resection
• Taking anticoagulants or antiaggregants that contraindicate the performance of therapy
• Patients with a recent colonoscopy (<6 months) of good quality (e.g. cited for endoscopic therapy)
• IBD
• Patients with incomplete colonoscopy
• Patients with inadequate preparation using the Boston Colonic Preparation Scale (BBPS). A cleaning quality of less than 2 points in any of the 3 colonic sections will be considered inadequate.
• Patients with polyposis syndromes

Related Conditions & MeSH terms

• Adenoma
• Adenoma Detection Rate

Intervention

Device:
• Computed adenoma detection system (CADe) plus endocuff
This is a computed system that helps the endoscopist to increase the detection of colorectal polyps. An add-on device (Endocuff) is also incorporated to the tip of the colonoscope
• Endocuff
An add-on device (Endocuff) is also incorporated to the tip of the colonoscope

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Hospital Universitario de Canarias

References & Publications (6)

Ashat M, Klair JS, Singh D, Murali AR, Krishnamoorthi R. Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis. Endosc Int Open. 2021 Apr;9(4):E513-E521. doi: 10.1055/a-1341-0457. Epub 2021 Mar 17. Review. — View Citation

Aziz M, Haghbin H, Gangwani MK, Sharma S, Nawras Y, Khan Z, Chandan S, Mohan BP, Lee-Smith W, Nawras A. Efficacy of Endocuff Vision compared to first-generation Endocuff in adenoma detection rate and polyp detection rate in high-definition colonoscopy: a systematic review and network meta-analysis. Endosc Int Open. 2021 Jan;9(1):E41-E50. doi: 10.1055/a-1293-7327. Epub 2021 Jan 1. Review. — View Citation

Barua I, Vinsard DG, Jodal HC, Løberg M, Kalager M, Holme Ø, Misawa M, Bretthauer M, Mori Y. Artificial intelligence for polyp detection during colonoscopy: a systematic review and meta-analysis. Endoscopy. 2021 Mar;53(3):277-284. doi: 10.1055/a-1201-7165. Epub 2020 Jun 17. — View Citation

Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rösch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26. Review. — View Citation

Ngu WS, Bevan R, Tsiamoulos ZP, Bassett P, Hoare Z, Rutter MD, Clifford G, Totton N, Lee TJ, Ramadas A, Silcock JG, Painter J, Neilson LJ, Saunders BP, Rees CJ. Improved adenoma detection with Endocuff Vision: the ADENOMA randomised controlled trial. Gut. 2019 Feb;68(2):280-288. doi: 10.1136/gutjnl-2017-314889. Epub 2018 Jan 23. — View Citation

Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C. Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. 2020 Aug;159(2):512-520.e7. doi: 10.1053/j.gastro.2020.04.062. Epub 2020 May 1. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Adenoma detection rate	(number of colonoscopies with adenoma/number of colonoscopies)	1 year
Secondary	Serrated detection rate	(number of colonoscopies with serrated adenoma/number of colonoscopies)	1 year
Secondary	Advanced adenoma detection rate	(number of colonoscopies with advanced adenomas/number of colonoscopies)	1 year