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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04673136
Other study ID # CADILLAC-01
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date April 1, 2021
Est. completion date March 31, 2022

Study information

Verified date April 2022
Source Asociación Española de Gastroenterología
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial 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.


Recruitment information / eligibility

Status Completed
Enrollment 3400
Est. completion date March 31, 2022
Est. primary completion date March 31, 2022
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - 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. Exclusion Criteria: - 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.

Study Design


Intervention

Device:
GI-GENIUS Medtronic
Colonoscopy assisted by GI-GENIUS device
Other:
Colonoscopy
Standard colonoscopy

Locations

Country Name City State
Spain Hospital General Universitario de Alicante Alicante
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

Sponsors (2)

Lead Sponsor Collaborator
Asociación Española de Gastroenterología Medtronic

Country where clinical trial is conducted

Spain, 

References & Publications (4)

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: 10.111 — View Citation

Urban 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.2018.06.03 — View Citation

Wang 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 stu — View Citation

Wang 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 — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary 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 Detection of other type of lesions To determine the ability of the GI-GENIUS device to detect other lesions (colorectal cancer, adenomas, advanced adenomas, serrated polyps, advanced serrated polyps, non-polypoid lesions =10mm and right-sided advanced adenomas) 15 months
Secondary Characteristics of GI-GENIUS To describe the characteristics of using the GI-GENIUS device during a colonoscopy: withdrawal time, false-positive and false-negative rate of advanced lesions using the device, etc. 1 month
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