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Quality Indicators, Health CareNCT06786793

Artificial Intelligence in Colonoscopy

A study testing Computer-aided detection (CADe) in people with Quality Indicators, Health Care and Artificial Intelligence (AI), run by Jagiellonian University at 2 sites in Poland.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts
Official record
Search all trials

Trial 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. Read more about this study

Who is it for?
Ages 50 to 65 years
What is being tested?
Computer-aided detection (CADe)
Type of treatment
Medical device
Could I receive a placebo?
No, everyone receives an active treatment
How many people
630 participants
Where
2 sitesPoland
Study dates
1 Nov 2024to 31 Dec 2025
Phase
Interventional
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 50 to 65 years
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Who may be able to join

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

Who cannot join

  • 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.

Trial locations and contacts

2 sites in 1 country. Contact the study team or a site near you to ask about taking part.

Zofia Orzeszko, MD contact

+48123797145

z.orzeszko@bonifratrzy.krakow.pl

Poland2 sites, 2 recruiting

  • MEDICINA Medical Center

    Krakow, Lesser Poladn, 31559

    Zofia Orzeszko, MD, +48123797145, z.orzeszko@bonifratrzy.krakow.pl

    Zofia Orzeszko, MD

    Recruiting

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

    Krakow, Lesser Polasd, 31061

    Zofia Orzeszko, MD, +48123797145, z.orzeszko@bonifratrzy.krakow.pl

    Tomasz Gach, PhD

    Recruiting

Other trials in Poland

About this study

Official title: Artificial Intelligence in Endoscopic Diagnosis of Colorectal Polyps: A Prospective Randomized Study.

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.

Read the detailed description

Colorectal cancer is the second most common malignancy in the countries of the European Union. The primary method for detecting and preventing the development of colorectal cancer is endoscopic examination-colonoscopy, during which precancerous lesions such as adenomas and serrated polyps can be removed. The effectiveness of colonoscopy depends on the adenoma detection rate, which varies among endoscopists and is influenced by their skills and experience. It has been proven that high-quality colonoscopy prevents the omission of colorectal cancer, which might develop in the future as so-called interval cancer. A breakthrough in machine learning in recent years has enabled the development of commercial artificial intelligence systems. These systems aim to improve the detection rates of precancerous polyps and, consequently, potentially reduce the risk of developing colorectal cancer. Artificial intelligence is also expected to help standardize performance across endoscopic procedures of varying quality, thereby contributing to a reduction in colorectal cancer incidence in the future. This study aims to evaluate the impact of artificial intelligence on the detection rate of polyps and early stages of colorectal cancer.

Being tested
Computer-aided detection (CADe)
Keywords
Quality Indicatiors, Colonoscopy, Artificial Intelligence (AI), Computer-aided Detection (CADe), Adenoma detection rate (ADR)

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • 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.

Study groups in NCT06786793
Study groupRoleWhat they receive
AI-groupExperimentalAI-group will include patients undergoing colonoscopy with the support of the ENDO-AID OIP-1 artificial intelligence system for colorectal polyp detection.
Receives: Device: Computer-aided detection (CADe)
Non-AI-groupNo interventionNon-AI-group will consist of patients undergoing colonoscopy without the assistance of this system.

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Adenoma detection rate (ADR)

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

    Measured: During the colonoscopy examination

Secondary outcomes (3)

  1. Utility of artificial intelligence for both novice and experienced endoscopists

    The difference in adenoma detection rates (ADR) achieved with and without AI in trainees and expert endoscopists.

    Measured: During the colonoscopy examination

  2. Assessing the morphology of polyps detected during colonoscopy

    Assessment of the differences in polyps' morphology detected in both arms of the study.

    Measured: During the colonoscopy examination

  3. Cost analysis of procedures performed with the use of artificial intelligence

    The assessment of cost-efficiency of AI implementation, including the increased cost of pathological evaluation and additional surveillance examinations.

    Measured: Through study completion, an average of 6 months

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted22 Jan 2025
  2. Study start1 Nov 2024
  3. Primary completion31 Oct 2025 (estimated)
  4. Study completion31 Dec 2025 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Interventional
Phase
Phase N/A
Primary purpose
Diagnosis
Allocation
Randomised
Intervention model
Parallel groups
Masking
None (open label)
Enrolment
630 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06786793
Sponsor's protocol ID
2024.000.421
Status last verified
Jan 2025
First submitted
12 Jan 2025
Last updated
22 Jan 2025
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • 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.

    PubMed 23567353

  • 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.

    PubMed 32240683

  • 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.

    PubMed 25817896

  • 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.

    PubMed 32557490

  • 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.

    PubMed 32371116

  • 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.

    PubMed 24693890

  • 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.

    PubMed 20463339

Questions about this trial

What is this clinical trial studying?

A study testing Computer-aided detection (CADe) in people with Quality Indicators, Health Care and Artificial Intelligence (AI), run by Jagiellonian University at 2 sites in Poland.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 3 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: looking for participants now, as of the sponsor's last update on 22 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 2 sites in Poland. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Zofia Orzeszko, MD (+48123797145, z.orzeszko@bonifratrzy.krakow.pl), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Adenoma detection rate (ADR) (time frame: During the colonoscopy examination). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT06786793, which also lists 7 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Jan 2025.

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