Computer-aided Detection During Screening Colonoscopy
Real-time Computer-aided Polyp/Adenoma Detection During Screening Colonoscopy: a Single-center Crossover Trial
1 other identifier
interventional
312
1 country
1
Brief Summary
Nowadays, colonoscopy is considered the gold standard for the detection of lesions in the colorectal mucosa. However, around 25% of polyps may be missed during the conventional colonoscopy. Based on this, new technological tools aimed to improve the quality of the procedures, diminishing the technical and operator-related factors associated with the missed lesions. These tools use artificial intelligence (AI), a computer system able to perform human tasks after a previous training process from a large dataset. The DiscoveryTM AI-assisted polyp detector (Pentax Medical, Hoya Group, Tokyo, Japan) is a newly developed detection system based on AI. It was designed to alert and direct the attention to potential mucosal lesions. According to its remarkable features, it may increase the polyp and adenoma detection rates (PDR and ADR, respectively) and decrease the adenoma miss rate (AMR). Based on the above, the investigators aim to assess the real-world effectiveness of the DiscoveryTM AI-assisted polyp detector system in clinical practice and compare the results between expert (seniors) and non-expert (juniors) endoscopists.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Jan 2020
Longer than P75 for not_applicable
1 active site
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
Study Start
First participant enrolled
January 11, 2020
CompletedFirst Submitted
Initial submission to the registry
February 9, 2023
CompletedFirst Posted
Study publicly available on registry
February 21, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 11, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
September 1, 2024
CompletedSeptember 28, 2023
September 1, 2023
4.4 years
February 9, 2023
September 26, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (3)
Adenoma detection rate (ADR)
The ADR will be determined by every new colonoscopy (second intervention) with at least one adenoma, histologically proven/NBI NICE classification. Results will be compared between experts and non-experts endoscopists.
up to one month
Polyp detection rate (PDR)
The PDR will be determined by every new colonoscopy (second intervention) with at least one polyp. Results will be compared between experts and non-experts endoscopists.
up to two hours
Diagnostic performance of AI-assisted polyp detector
The diagnostic performance of the AI-assisted system will be assessed by sensitivity, specificity, positive and negative predictive values (PPV and NPV) and observer agreement.
up to three years
Secondary Outcomes (1)
Adenoma Miss Rate (AMR)
Up to one month
Study Arms (2)
HD-colonoscopy + AI-HD colonoscopy
EXPERIMENTALThis group is comprised by patients \>45 years of age submitted for diagnostic colonoscopy. In the same session a HD-colonoscopy will be performed followed by an HD-colonoscopy with artificial intelligence assistance. The second procedure will be performed by an operator with the same-level-of -expertise in comparison to the initial procedure (expert or non-expert) and blinded to the results of the previous intervention.
AI-HD colonoscopy + HD-colonoscopy
EXPERIMENTALThis group is comprised by patients \>45 years of age submitted for diagnostic colonoscopy. In the same session a HD-colonoscopy assisted by artificial intelligence will be performed followed by an HD-colonoscopy alone.The second procedure will be performed by an operator with the same-level-of -expertise in comparison to the initial procedure (expert or non-expert) and blinded to the results of the previous intervention.
Interventions
HD-colonoscopy performed by an expert or non-expert endoscopist. All lesions will be recorded, assessed, and removed for histological analysis.
HD-colonoscopy with AI-assisted polyp detector. New polyps detected by AI will be recorded, removed, and studied.
Eligibility Criteria
You may qualify if:
- Adults ≥45 years old
- Patients referred for screening colonoscopy
- Adequate bowel preparation, Boston Bowel Preparation Scale (BBPS) ≥8
- Patients who authorized for endoscopic approach.
You may not qualify if:
- Pregnancy
- Any clinical condition which makes endoscopy inviable.
- Patients with history of Colorectal Carcinoma.
- Patients with history of Inflammatory Bowel Disease (IBD)
- Inability to provide informed consent
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Instituto Ecuatoriano de Enfermedades Digestivas (IECED)
Guayaquil, Guayas, 090505, Ecuador
Related Publications (5)
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 study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.
PMID: 30814121BACKGROUNDCorley DA, Jensen CD, Marks AR, Zhao WK, Lee JK, Doubeni CA, Zauber AG, de Boer J, Fireman BH, Schottinger JE, Quinn VP, Ghai NR, Levin TR, Quesenberry CP. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med. 2014 Apr 3;370(14):1298-306. doi: 10.1056/NEJMoa1309086.
PMID: 24693890BACKGROUNDKroner PT, Engels MM, Glicksberg BS, Johnson KW, Mzaik O, van Hooft JE, Wallace MB, El-Serag HB, Krittanawong C. Artificial intelligence in gastroenterology: A state-of-the-art review. World J Gastroenterol. 2021 Oct 28;27(40):6794-6824. doi: 10.3748/wjg.v27.i40.6794.
PMID: 34790008BACKGROUNDParsa N, Byrne MF. Artificial intelligence for identification and characterization of colonic polyps. Ther Adv Gastrointest Endosc. 2021 Jun 29;14:26317745211014698. doi: 10.1177/26317745211014698. eCollection 2021 Jan-Dec.
PMID: 34263163BACKGROUNDGong D, Wu L, Zhang J, Mu G, Shen L, Liu J, Wang Z, Zhou W, An P, Huang X, Jiang X, Li Y, Wan X, Hu S, Chen Y, Hu X, Xu Y, Zhu X, Li S, Yao L, He X, Chen D, Huang L, Wei X, Wang X, Yu H. Detection of colorectal adenomas with a real-time computer-aided system (ENDOANGEL): a randomised controlled study. Lancet Gastroenterol Hepatol. 2020 Apr;5(4):352-361. doi: 10.1016/S2468-1253(19)30413-3. Epub 2020 Jan 22.
PMID: 31981518BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Carlos Robles-Medranda, MD FASGE
Instituto Ecuatoriano de Enfermedades Digestivas (IECED)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- SINGLE
- Who Masked
- CARE PROVIDER
- Purpose
- DIAGNOSTIC
- Intervention Model
- CROSSOVER
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Head of the Endoscopy Division
Study Record Dates
First Submitted
February 9, 2023
First Posted
February 21, 2023
Study Start
January 11, 2020
Primary Completion
June 11, 2024
Study Completion
September 1, 2024
Last Updated
September 28, 2023
Record last verified: 2023-09