Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp DetectionNCT04339855
AI for Colorectal Polyp Detection in Endoscopy
An observational study of Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp Detection, run by Johannes Gutenberg University Mainz at 1 site in Germany.
Trial summary
Linked color imaging (LCI) has shown its effectiveness in multiple randomized controlled trials for enhanced colorectal polyp detection. Most recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp Detection
- What is being tested?
- CAD with LCI for colorectal polyp detection
- How many people
- 600 participants
- Where
- 1 siteGermany
- Study dates
- 1 Feb 2019to 30 Sep 2020
- 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: Patients ondergoing screeining or surveillance endoscopy
Who may be able to join
- Full endoscopy withdrawal videos with LCI of patients ondergoing screening or surveillance endoscopy
Who cannot join
- non adequate bowel preparation
- no full length withdrawal in LCI mode
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Artificial Intelligence Combined With LCI for Colorectal Polyp Detection
Linked color imaging (LCI) has shown its effectiveness in multiple randomized controlled trials for enhanced colorectal polyp detection. Most recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new technique enhancing colorectal polyp detection. Study aim was to evaluate a new developed deep-learning computer-aided detection (CAD) system in combination with LCI for colorectal polyp detection.
- Being tested
- CAD with LCI for colorectal polyp detection
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
CAD with LCI for colorectal polyp detectionOther
Polyps within fully recorded endoscopy videos with LCI mode, covering the whole spectrum of adenomatous histology, are used to evaluate the efficacy of CAD with LCI for polyp detection.
What is being measured
The primary outcome is the main question the study is designed to answer.
Colorectal polyp detection rate in comparison to traditional detection rate
Measured: 2019-2020
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Apr 2020
- Study start1 Feb 2019
- Primary completion31 Aug 2020 (estimated)
- Study completion30 Sep 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp DetectionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
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
- Other
- Time perspective
- Other
- Enrolment
- 600 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Johannes Gutenberg University Mainz
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Prof. Helmut Neumann, Johannes Gutenberg University Mainz
- Investigators
- Helmut Neumann, Prof. Dr., Principal investigator, Head of Interdisciplinary Endoscopy
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04339855
- Sponsor's protocol ID
- HN_01KR7Zt
- Status last verified
- Sep 2020
- First submitted
- 7 Apr 2020
- Last updated
- 7 Sep 2020
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 7 Sep 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence Combined With LCI for Colorectal Polyp Detection
- ClinicalTrials.gov ID
- NCT04339855
- Acronym / sponsor ID
- HN_01KR7Zt
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 600 participants (estimated)
- Lead sponsor
- Johannes Gutenberg University MainzUniversity, hospital or other
- Study start
- 1 Feb 2019 (actual)
- Primary completion
- 31 Aug 2020 (estimated)
- Study completion
- 30 Sep 2020 (estimated)
- First posted
- 9 Apr 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Linked color imaging (LCI) has shown its effectiveness in multiple randomized controlled trials for enhanced colorectal polyp detection. Most recently, artificial intelligence (AI) with deep learning through convolutional neural networks has dramatically improved and is increasingly recognized as a promising new technique enhancing colorectal polyp detection. Study aim was to evaluate a new developed deep-learning computer-aided detection (CAD) system in combination with LCI for colorectal polyp detection.
Study design
- Observational model
- Other
- Time perspective
- Other
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients ondergoing screeining or surveillance endoscopy
Key inclusion criteria (1 listed)
- Full endoscopy withdrawal videos with LCI of patients ondergoing screening or surveillance endoscopy
Key exclusion criteria (2 listed)
- non adequate bowel preparation
- no full length withdrawal in LCI mode
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| CAD with LCI for colorectal polyp detectionPolyps within fully recorded endoscopy videos with LCI mode, covering the whole spectrum of adenomatous histology, are used to evaluate the efficacy of CAD with LCI for polyp detection. | Other | – |
Primary outcome
Colorectal polyp detection rate in comparison to traditional detection rate
Time frame: 2019-2020
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Sep 2020.
- Individual participant dataSharing planned: Undecided
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Helmut Neumann, Prof. Dr. principal investigator
Head of Interdisciplinary Endoscopy
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Focus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp Detection, run by Johannes Gutenberg University Mainz at 1 site in Germany.
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 2 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: status not confirmed, as of the sponsor's last update on 7 Sep 2020. 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 Germany. 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?
Results are not available in the source record.
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?
Colorectal polyp detection rate in comparison to traditional detection rate (time frame: 2019-2020). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 7 Sep 2020; AzTrials last refreshed its copy on 31 Oct 2026.