NCT06786793

Brief Summary

Colorectal cancer is the second most common malignancy in the countries of the European Union. Colonoscopy is the primary method for detecting and preventing the development of colorectal cancer is endoscopic examination. This study aims to evaluate the impact of artificial intelligence on the detection rate of polyps and early stages of colorectal cancer.

Trial Health

57
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
630

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Nov 2024

Geographic Reach
1 country

2 active sites

Status
recruiting

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

November 1, 2024

Completed
2 months until next milestone

First Submitted

Initial submission to the registry

January 12, 2025

Completed
10 days until next milestone

First Posted

Study publicly available on registry

January 22, 2025

Completed
9 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

October 31, 2025

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2025

Completed
Last Updated

January 22, 2025

Status Verified

January 1, 2025

Enrollment Period

12 months

First QC Date

January 12, 2025

Last Update Submit

January 15, 2025

Conditions

Quality Indicators, Health CareArtificial Intelligence (AI)Colonoscopy Diagnostic Techniques and Procedures

Keywords

Quality IndicatiorsColonoscopyArtificial Intelligence (AI)Computer-aided Detection (CADe)Adenoma detection rate (ADR)

Outcome Measures

Primary Outcomes (1)

  • Adenoma detection rate (ADR)

    The percentage of colonoscopies when at least one histologically proven adenoma was found.

    During the colonoscopy examination

Secondary Outcomes (3)

  • Utility of artificial intelligence for both novice and experienced endoscopists

    During the colonoscopy examination

  • Assessing the morphology of polyps detected during colonoscopy

    During the colonoscopy examination

  • Cost analysis of procedures performed with the use of artificial intelligence

    Through study completion, an average of 6 months

Study Arms (2)

AI-group

EXPERIMENTAL

AI-group will include patients undergoing colonoscopy with the support of the ENDO-AID OIP-1 artificial intelligence system for colorectal polyp detection.

Device: Computer-aided detection (CADe)

Non-AI-group

NO INTERVENTION

Non-AI-group will consist of patients undergoing colonoscopy without the assistance of this system.

Interventions

Computer-aided detection (CADe)DEVICE

Endo-Aid CADe system is an AI-assisted computer-aided lesion detection application on ENDO-AID hardware. It uses a complex algorithm created via a neural network developed and taught by Olympus. With this new app, the sophisticated machine learning system can alert the endoscopist in real-time when a suspicious lesion appears on the screen. The image from the vision processor is transferred to the CADe device. The computer application recognizes the shape of the polyps and marks their place on the monitor screen.

AI-group

Eligibility Criteria

Age50 Years - 65 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Consent to participate in the study,
  • Age between 50 and 65 years,
  • Scheduled outpatient colonoscopy.

You may not qualify if:

  • Previous colonoscopy,
  • History of colorectal surgery,
  • Ongoing biological therapy for any indication,
  • Primary sclerosing cholangitis,
  • Familial polyposis syndrome,
  • Chronic diarrhea,
  • Ulcerative colitis,
  • Crohn's disease.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (2)

MEDICINA Medical Center

Krakow, Lesser Poladn, 31559, Poland

RECRUITING

Brothers Hospitallers Medical Center, Hospital of St John of god in Krakow

Krakow, Lesser Polasd, 31061, Poland

RECRUITING

Related Publications (7)

  • Boroff ES, Gurudu SR, Hentz JG, Leighton JA, Ramirez FC. Polyp and adenoma detection rates in the proximal and distal colon. Am J Gastroenterol. 2013 Jun;108(6):993-9. doi: 10.1038/ajg.2013.68. Epub 2013 Apr 9.

    PMID: 23567353BACKGROUND

  • Mori Y, Kudo SE, East JE, Rastogi A, Bretthauer M, Misawa M, Sekiguchi M, Matsuda T, Saito Y, Ikematsu H, Hotta K, Ohtsuka K, Kudo T, Mori K. Cost savings in colonoscopy with artificial intelligence-aided polyp diagnosis: an add-on analysis of a clinical trial (with video). Gastrointest Endosc. 2020 Oct;92(4):905-911.e1. doi: 10.1016/j.gie.2020.03.3759. Epub 2020 Mar 30.

    PMID: 32240683BACKGROUND

  • van Doorn SC, Klanderman RB, Hazewinkel Y, Fockens P, Dekker E. Adenoma detection rate varies greatly during colonoscopy training. Gastrointest Endosc. 2015 Jul;82(1):122-9. doi: 10.1016/j.gie.2014.12.038. Epub 2015 Mar 24.

    PMID: 25817896BACKGROUND

  • Barua I, Vinsard DG, Jodal HC, Loberg M, Kalager M, Holme O, 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 Sep 29.

    PMID: 32557490BACKGROUND

  • 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.

    PMID: 32371116BACKGROUND

  • Corley 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: 24693890BACKGROUND

  • Kaminski MF, Regula J, Kraszewska E, Polkowski M, Wojciechowska U, Didkowska J, Zwierko M, Rupinski M, Nowacki MP, Butruk E. Quality indicators for colonoscopy and the risk of interval cancer. N Engl J Med. 2010 May 13;362(19):1795-803. doi: 10.1056/NEJMoa0907667.

    PMID: 20463339BACKGROUND

Study Officials

  • Miroslaw Szura, Prof.

    Jagiellonian University in Krakow

    STUDY CHAIR

  • Zofia Orzeszko, MD

    Jagiellonian University in Krakow

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Zofia Orzeszko, MD

CONTACT

+48123797145z.orzeszko@bonifratrzy.krakow.pl

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
DIAGNOSTIC
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal Investigator

Study Record Dates

First Submitted

January 12, 2025

First Posted

January 22, 2025

Study Start

November 1, 2024

Primary Completion

October 31, 2025

Study Completion

December 31, 2025

Last Updated

January 22, 2025

Record last verified: 2025-01

Data Sharing

IPD Sharing
Will not share

Locations

PL(2)