Usefulness of GI-GENIUS in FIT-based Colorectal Cancer Screening Program.
CADILLAC
1 other identifier
interventional
3,400
1 country
6
Brief Summary
Deep learning technology has an increasing role in medical image applications and, recently, an artificial intelligence device has been developed and commercialized by Medtronic for identification of polyps during colonoscopy (GI-GENIUS). This kind of computer-aided detection (CADe) devices have demonstrated its ability for improving polyp detection rate (PDR) and the adenoma detection rate (ADR). However, this increase in PDR and ADR is mainly made at the expense of small polyps and non advanced adenomas. Colonoscopies after a positive fecal immunochemical test (FIT) could be the scenario with a higher prevalence of advanced lesions which could be the ideal situation for demonstrating if these CADe systems are able also to increase the detection of advanced lesions and which kind of advanced lesions are these systems able to detect. The CADILLAC study will randomize individuals within the population-based Spanish colorectal cancer screening program to receive a colonoscopy where the endoscopist is assisted by the GI-GENIUS device or to receive a standard colonoscopy. If our results are positive, that could suppose a big step forward for CADe devices, in terms of definitive demonstration of being of help for efectively identify also advanced lesions.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Apr 2021
6 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
December 13, 2020
CompletedFirst Posted
Study publicly available on registry
December 17, 2020
CompletedStudy Start
First participant enrolled
April 1, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 31, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
March 31, 2022
CompletedApril 8, 2022
April 1, 2022
12 months
December 13, 2020
April 7, 2022
Conditions
Outcome Measures
Primary Outcomes (1)
Detection of advanced lesions
To determine the impact of the GI-GENIUS device as an assistant to the endoscopist to detect advanced lesions (advanced adenomas and advanced serrated polyps) in FIT-based screening colonoscopies.
15 months
Secondary Outcomes (2)
Detection of other type of lesions
15 months
Characteristics of GI-GENIUS
1 month
Study Arms (2)
Colonoscopy assisted by GI-GENIUS
EXPERIMENTALStandard colonoscopy
PLACEBO COMPARATORInterventions
Eligibility Criteria
You may qualify if:
- Individuals with a positive result in fecal immunochemical test within the population-based colorectal cancer screening program.
- Complete colonoscopy with cecal intubation.
- Inform consent signed.
You may not qualify if:
- Personal history of colorectal cancer.
- Family history of colorectal cancer: ≥2 FDR or ≥1 FDR diagnosed before 50 years of age.
- Family history of hereditary colorectal cancer syndromes: Lynch syndrome, FAP, etc.
- Personal history of inflammatory bowel disease.
- Terminal illness.
- Personal history of total proctocolectomy.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Asociación Española de Gastroenterologíalead
- Medtroniccollaborator
Study Sites (6)
Hospital General Universitario de Alicante
Alicante, 03010, Spain
Hospital Clinic Barcelona
Barcelona, Spain
Complexo Hospitalario de Ourense
Ourense, Spain
Hospital Universitario Central de Asturias
Oviedo, Spain
Hospital Universitario Río Hortega
Valladolid, Spain
Hospital Universitario Álvaro Cunqueiro
Vigo, Spain
Related Publications (5)
Aziz M, Fatima R, Dong C, Lee-Smith W, Nawras A. The impact of deep convolutional neural network-based artificial intelligence on colonoscopy outcomes: A systematic review with meta-analysis. J Gastroenterol Hepatol. 2020 Oct;35(10):1676-1683. doi: 10.1111/jgh.15070. Epub 2020 Apr 26.
PMID: 32267558RESULTUrban G, Tripathi P, Alkayali T, Mittal M, Jalali F, Karnes W, Baldi P. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy. Gastroenterology. 2018 Oct;155(4):1069-1078.e8. doi: 10.1053/j.gastro.2018.06.037. Epub 2018 Jun 18.
PMID: 29928897RESULTWang P, Berzin TM, Glissen Brown JR, Bharadwaj S, Becq A, Xiao X, Liu P, Li L, Song Y, Zhang D, Li Y, Xu G, Tu M, Liu X. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.
PMID: 30814121RESULTWang P, Liu X, Berzin TM, Glissen Brown JR, Liu P, Zhou C, Lei L, Li L, Guo Z, Lei S, Xiong F, Wang H, Song Y, Pan Y, Zhou G. Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study. Lancet Gastroenterol Hepatol. 2020 Apr;5(4):343-351. doi: 10.1016/S2468-1253(19)30411-X. Epub 2020 Jan 22.
PMID: 31981517RESULTMangas-Sanjuan C, de-Castro L, Cubiella J, Diez-Redondo P, Suarez A, Pellise M, Fernandez N, Zarraquinos S, Nunez-Rodriguez H, Alvarez-Garcia V, Ortiz O, Sala-Miquel N, Zapater P, Jover R; CADILLAC study investigators. Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias : A Randomized Trial. Ann Intern Med. 2023 Sep;176(9):1145-1152. doi: 10.7326/M22-2619. Epub 2023 Aug 29.
PMID: 37639723DERIVED
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- DIAGNOSTIC
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
December 13, 2020
First Posted
December 17, 2020
Study Start
April 1, 2021
Primary Completion
March 31, 2022
Study Completion
March 31, 2022
Last Updated
April 8, 2022
Record last verified: 2022-04
Data Sharing
- IPD Sharing
- Will not share