Bowel DiseaseNOCENCT06152289
Development of New Diagnostic Tools in Capsule Endoscopy
An observational study of Bowel Disease and Crohn Disease, run by Assistance Publique - Hôpitaux de Paris at 1 site in France.
Trial summary
Patients participating to this study will provide images and videos of capsule endoscopy to train, tune and evaluate technological bricks of artificial intelligence solutions, in order to improve diagnostic performances of the procedure, while reducing reading time by physicians. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Bowel Disease, Crohn Disease, Celiac Disease
- How many people
- 10,000 participants
- Where
- 1 siteFrance
- Study dates
- 10 Feb 2023to Feb 2028
- Phase
- Observational
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Any patient in whom a capsule endoscopy examination is performed as part of routine care
Who may be able to join
- Any patient in whom a capsule endoscopy examination is performed as part of routine care.
Who cannot join
- Opposition to the use of images and videos from daily, routine care for research purposes.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
France1 site, 1 recruiting
- Recruiting
Centre d'Endoscopie Digestive Hôpital Saint-Antoine
Paris, 75012
Xavier DRAY, MD PhD, +33 (0) 49 28 21 60, Xavier.dray@aphp.fr
About this study
Patients participating to this study will provide images and videos of capsule endoscopy to train, tune and evaluate technological bricks of artificial intelligence solutions, in order to improve diagnostic performances of the procedure, while reducing reading time by physicians.
Read the detailed description
Capsule endoscopy is a minimally-invasive diagnostic procedure based on the ingestion (or endoscopic delivery) of a miniaturized biocompatible, camera. Capsules capture tenths of thousands images of the digestive tract. Reading the captured images and reporting is long, tedious, and at risk of errors when the reader's attention is disturbed. Artificial intelligence is expected to alleviate these limitations, by both improving diagnostic performances of capsule endoscopy while reducing reading time.
Any patient in whom a capsule endoscopy examination is performed as part of routine care will be invited to participate to the study. Their de-identified images and videos will be extracted, thus allowing the creation of several databases for training, tuning and testing technological bricks of artificial intelligence. Basic clinical data will be collected (age, gender, indication for capsule endoscopy, type of device, ingestion or delivery of capsule). Images and videos will be characterized centrally and consensually by a panel of 3 expert readers, according to their level of relevance in relation to the type and indication of capsule endoscopy.
The various, developed technological bricks will aim to automatically detect and characterize anatomical landmarks and abnormal findings, and to quote the intestine cleanliness.
Assessment of diagnostic performance and reading time will be performed within a few months or up to five years, for each technological brick, individually and then combined, according to their stepwise development.
- Conditions
- Bowel Disease, Crohn Disease, Celiac Disease, Chronic Diarrhea, Tumor
- Keywords
- Small bowel, Capsule endoscopy, Artificial intelligence
- Medical subject headings
- Intestinal Diseases, Crohn Disease, Celiac Disease, Neoplasms
What is being measured
The primary outcome is the main question the study is designed to answer.
Develop an artificial intelligence solution to help with diagnosis in VCE
Sensitivity in detection of lesions of intermediate to high relevance as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Measured: Through study completion, 5 years
Secondary outcomes (4)
Evaluation of the diagnostic performance of the A.I. solution in terms of detection
Other diagnostic performance (specificity, positive and negative predictive values, accuracy) in detection of lesions of intermediate to high relevance as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Measured: Through study completion, 5 years
Evaluation of the diagnostic performance of the A.I. solution in terms of characterisation
Time needed for detection of lesions of intermediate to high relevance as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Measured: Through study completion, 5 years
Evaluation of the diagnostic performance of the A.I. solution in terms of recognition of anatomical landmarks
Diagnostic performances in positioning anatomical landmarks (1st gastric, small bowl and colonic images) as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
Measured: Through study completion, 5 years
Evaluation of the diagnostic performance of the A.I. solution in terms of quality of preparation of the various segments of the digestive tract
Diagnostic performances in quoting small bowel and colonic quality of preparation, as compared toed centrally and consensually quoted by a panel of 3 expert readers
Measured: Through study completion, 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Nov 2023
- Study start10 Feb 2023
- Primary completionFeb 2028 (estimated)
- Study completionFeb 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Bowel DiseaseStudies of the same condition, open and under way.
- More trials run by Assistance Publique - Hôpitaux de ParisThe sponsor's other registered studies.
- 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 10,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Assistance Publique - Hôpitaux de Paris
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06152289
- Sponsor's protocol ID
- APHP210791
- Acronym
- NOCE
- Status last verified
- Feb 2026
- First submitted
- 6 Jun 2023
- Last updated
- 2 Mar 2026
- Results posted
- No
- Data monitoring committee
- No
- 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 2 Mar 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of New Diagnostic Tools in Capsule Endoscopy
- ClinicalTrials.gov ID
- NCT06152289
- Acronym / sponsor ID
- NOCE / APHP210791
- Conditions
- Bowel Disease, Crohn Disease, Celiac Disease, Chronic Diarrhea, Tumor
- Keywords
- Small bowel, Capsule endoscopy, Artificial intelligence
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 10,000 participants (estimated)
- Lead sponsor
- Assistance Publique - Hôpitaux de ParisUniversity, hospital or other
- Study start
- 10 Feb 2023 (actual)
- Primary completion
- Feb 2028 (estimated)
- Study completion
- Feb 2028 (estimated)
- First posted
- 30 Nov 2023 (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.
Patients participating to this study will provide images and videos of capsule endoscopy to train, tune and evaluate technological bricks of artificial intelligence solutions, in order to improve diagnostic performances of the procedure, while reducing reading time by physicians.
Detailed description
Capsule endoscopy is a minimally-invasive diagnostic procedure based on the ingestion (or endoscopic delivery) of a miniaturized biocompatible, camera. Capsules capture tenths of thousands images of the digestive tract. Reading the captured images and reporting is long, tedious, and at risk of errors when the reader's attention is disturbed. Artificial intelligence is expected to alleviate these limitations, by both improving diagnostic performances of capsule endoscopy while reducing reading time.
Any patient in whom a capsule endoscopy examination is performed as part of routine care will be invited to participate to the study. Their de-identified images and videos will be extracted, thus allowing the creation of several databases for training, tuning and testing technological bricks of artificial intelligence. Basic clinical data will be collected (age, gender, indication for capsule endoscopy, type of device, ingestion or delivery of capsule). Images and videos will be characterized centrally and consensually by a panel of 3 expert readers, according to their level of relevance in relation to the type and indication of capsule endoscopy.
The various, developed technological bricks will aim to automatically detect and characterize anatomical landmarks and abnormal findings, and to quote the intestine cleanliness.
Assessment of diagnostic performance and reading time will be performed within a few months or up to five years, for each technological brick, individually and then combined, according to their stepwise development.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Any patient in whom a capsule endoscopy examination is performed as part of routine care
Key inclusion criteria (1 listed)
- Any patient in whom a capsule endoscopy examination is performed as part of routine care.
Key exclusion criteria (1 listed)
- Opposition to the use of images and videos from daily, routine care for research purposes.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Develop an artificial intelligence solution to help with diagnosis in VCE
Time frame: Through study completion, 5 years
Sensitivity in detection of lesions of intermediate to high relevance as identified centrally and consensually by a panel of 3 expert readers (AI vs standard reading)
4 secondary outcomes
Evaluation of the diagnostic performance of the A.I. solution in terms of detection
Time frame: Through study completion, 5 years
Evaluation of the diagnostic performance of the A.I. solution in terms of characterisation
Time frame: Through study completion, 5 years
Evaluation of the diagnostic performance of the A.I. solution in terms of recognition of anatomical landmarks
Time frame: Through study completion, 5 years
Evaluation of the diagnostic performance of the A.I. solution in terms of quality of preparation of the various segments of the digestive tract
Time frame: Through study completion, 5 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Mar 2026.
- Individual participant dataSharing planned: Undecided
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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.
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 Bowel Disease and Crohn Disease, run by Assistance Publique - Hôpitaux de Paris at 1 site in France.
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 1 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 2 Mar 2026. 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 France. 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 Xavier DRAY, MD PhD (+33 (0) 49 28 21 60, Xavier.dray@aphp.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Develop an artificial intelligence solution to help with diagnosis in VCE (time frame: Through study completion, 5 years). 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 2 Mar 2026.