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Quality Indicators, Health CareNCT06623331

The Implementation of Computer-aided Detection in Training Improves the Quality of Future Colonoscopies

An observational study of Quality Indicators, Health Care and Colonoscopy Diagnostic Techniques and Procedures, run by Jagiellonian University at 1 site in Poland.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record
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Trial summary

Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. Read more about this study

Who is it for?
Ages 18 years and older
What is being tested?
AI-enhanced endoscopy training and Conventional endoscopy training
How many people
6,000 participants
Where
1 sitePoland
Study dates
1 Jan 2022to 31 Mar 2024
Phase
Observational
Are there results?
None posted in the registry

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 18 years and older
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: This study included 6,000 adult patients who underwent a colonoscopy for various reasons in a single high-volume endoscopy clinic in Krakow.

Who may be able to join

  • adult participants who underwent a colonoscopy for various reasons performed by specific endoscopists that were assessed in terms of quality indicators

Who cannot join

  • a history of bowel resection
  • confirmed inflammatory bowel disease
  • suspicion of polyps or cancer in other imaging tests
  • suspicion of familial adenomatous polyposis

Trial locations and contacts

1 site in 1 country.

Poland1 site

  • Jagiellonian University

    Krakow, 31007

Other trials in Poland

About this study

Official title: The Implementation of Computer-aided Detection in an Initial Endoscopy Training Improves the Quality Measures of Trainees' Future Colonoscopies

Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. The study aimed to evaluate the quality indicators of endoscopists trained in an AI environment compared to those trained conventionally.

Read the detailed description

Computer-aided detection (CADe) based on artificial intelligence (AI) may improve colonoscopy quality. An increasing number of young endoscopists are trained in an AI environment. However its impact on trainees' future outcomes remains unclear. The study aimed to evaluate the quality indicators of endoscopists trained in an AI environment compared to those trained conventionally. A study included 6,000 adult patients who underwent a colonoscopy for various reasons. The study retrospectively evaluated the first 1,000 procedures performed by six endoscopists after completing training relying entirely on endoscopists' detection skills without AI enhancement. Three of those young endoscopists were trained with CADe, and three without additional assistance. Quality indicators were assessed in both groups. The morphology of detected polyps was evaluated to determine the influence of AI-enhanced training on laterally spreading tumors (LST) detection rate.

Being tested
AI-enhanced endoscopy training, Conventional endoscopy training
Keywords
Quality Indicators, 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.

  • AI-enhanced endoscopy trainingOther

    Endoscopists trained in AI-enhanced environment. Their quality indicators are measured after completing training, without additional AI enhancement.

  • Conventional endoscopy trainingOther

    Endoscopists trained conventionally

Study groups in NCT06623331
Study groupRoleWhat they receive
Group AColonoscopies performed by endoscopists trained in AI-enhanced environment. The quality indicators are measured after completing training without AI enhancement.
Receives: Other: AI-enhanced endoscopy training
Group BColonoscopies performed by endoscopists trained conventionally. The quality indicators are measured after completing training without AI enhancement.
Receives: Other: Conventional endoscopy training

What is being measured

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

  1. Serrated polyp detection rate (SDR)

    The percentage of colonoscopies when the serrated polyp was found

    Measured: During the colonoscopy examination

  2. withdrawal time

    The time from the cecal intubation to the end of the examination

    Measured: During the colonoscopy examination

  3. Cecal intubation rate (CIR)

    The percentage of colonoscopies with successful cecal intubations

    Measured: During the colonoscopy examination

  4. Adenoma Detection Rate (ADR)

    The percentage of colonoscopies when the adenoma was found

    Measured: During the colonoscopy examination

  5. Advanced adenoma detection rate (AADR)

    The percentage of colonoscopies when the advanced adenoma (\>10mm) was found

    Measured: During the colonoscopy examination

  6. Adenoma per colonoscopy score (APC)

    The average number of adenomas detected in a single colonoscopy

    Measured: During the colonoscopy examination

Secondary outcomes (1)

  1. Laterally spreading tumor detection rate

    The percentage of colonoscopies when the laterally spreading tumor lesion was found

    Measured: During the colonoscopy examination

Timeline

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

  1. First posted2 Oct 2024
  2. Study start1 Jan 2022
  3. Primary completion31 Jan 2024
  4. Study completion31 Mar 2024

Resources

More details

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

Study design
Study type
Observational
Observational model
Case-control
Time perspective
Retrospective
Enrolment
6,000 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06623331
Sponsor's protocol ID
2024.000.367
Status last verified
Jan 2025
First submitted
30 Sep 2024
Last updated
17 Jan 2025
Results posted
No
Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • Spadaccini M, Iannone A, Maselli R, Badalamenti M, Desai M, Chandrasekar VT, Patel HK, Fugazza A, Pellegatta G, Galtieri PA, Lollo G, Carrara S, Anderloni A, Rex DK, Savevski V, Wallace MB, Bhandari P, Roesch T, Gralnek IM, Sharma P, Hassan C, Repici A. Computer-aided detection versus advanced imaging for detection of colorectal neoplasia: a systematic review and network meta-analysis. Lancet Gastroenterol Hepatol. 2021 Oct;6(10):793-802. doi: 10.1016/S2468-1253(21)00215-6. Epub 2021 Aug 5.

    PubMed 34363763

  • 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

  • Wang P, Liu P, Glissen Brown JR, Berzin TM, Zhou G, Lei S, Liu X, Li L, Xiao X. Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study. Gastroenterology. 2020 Oct;159(4):1252-1261.e5. doi: 10.1053/j.gastro.2020.06.023. Epub 2020 Jun 17.

    PubMed 32562721

  • Glissen Brown JR, Mansour NM, Wang P, Chuchuca MA, Minchenberg SB, Chandnani M, Liu L, Gross SA, Sengupta N, Berzin TM. Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial). Clin Gastroenterol Hepatol. 2022 Jul;20(7):1499-1507.e4. doi: 10.1016/j.cgh.2021.09.009. Epub 2021 Sep 14.

    PubMed 34530161

  • 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?

An observational study of Quality Indicators, Health Care and Colonoscopy Diagnostic Techniques and Procedures, run by Jagiellonian University at 1 site 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 1 inclusion and 4 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: finished, as of the sponsor's last update on 17 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 1 site 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?

The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.

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

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Serrated polyp detection rate (SDR) (time frame: During the colonoscopy examination). The study lists 6 primary outcomes in all. 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 NCT06623331, 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 17 Jan 2025; AzTrials last refreshed its copy on 27 Oct 2026.

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