Pouches, IleoanalPouchVisionNCT04864587
Artificial Intelligence in Image Recognition of Pouchoscopies in Patients With Restorative Proctocolectomy
An observational study of Pouches, Ileoanal, run by Theresienkrankenhaus und St. Hedwig-Klinik GmbH at 1 site in Germany.
Trial summary
The application of artificial intelligence in pouchoscopy of patients with restorative proctocolectomy might improve the diagnosis of pouchitis and neoplasms. The aim of this pilot study is to develop a convolutional neural network algorithm for pouchoscopy Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pouches, Ileoanal
- What is being tested?
- Artificial intelligence used for image recognition in pouchoscopy
- How many people
- 500 participants
- Where
- 1 siteGermany
- Study dates
- 1 Jun 2021to 1 Jun 2023
- 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: Adult patients with inflammatory bowel disease and status after restorative proctocolectomy with ileoanal pouch might develop pouchitis or neoplasia in the pouch.
Who may be able to join
- All patients aged ≥ 18 years with inflammatory bowel disease and status after restorative proctocolectomy with ileoanal pouch who had received a pouchoscopy
Who cannot join
- Very poor endoscopic image quality
Trial locations and contacts
1 site in 1 country.
Germany1 site
Theresienkrankenhaus und St. Hedwigkliniken GmbH
Mannheim, Baden-Wurttemberg, 68165
About this study
The application of artificial intelligence in pouchoscopy of patients with restorative proctocolectomy might improve the diagnosis of pouchitis and neoplasms. The aim of this pilot study is to develop a convolutional neural network algorithm for pouchoscopy
Read the detailed description
Restorative proctocolectomy is the standard procedure for treatment of refractory severe colitis in inflammatory bowel disease as well as the standard procedure for carcinoma preventive treatment of patients with inflammatory bowel disease with colonic neoplasia and patients with familial adenomatous polyposis coli (FAP). Pouchoscopy can be used to monitor the success of therapy and to detect complications such as pouchitis or neoplasia. Artificial Intelligence assisted image recognition programs can support the examiner in finding a diagnosis and train physicians in training, objectify endoscopic findings in the context of studies and might make biopsies unnecessary, thus saving costs. The application of Artificial Intelligence in pouchoscopy has not been demonstrated to date. The aim of this study is to develop, an image recognition algorithm that reliably detects the different graduations of pouch inflammation. This requires training and fine-tuning of the image recognition program PiTorch using the largest possible amount of image data, which will be recruited from the image databases of the UMM and the Theresienkrankenhaus Mannheim. A test run for statistical evaluation will be performed on an independent cohort.
- Conditions
- Pouches, Ileoanal
- Being tested
- Artificial intelligence used for image recognition in pouchoscopy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence used for image recognition in pouchoscopyDiagnostic test
The aim of this study is to develop an image recognition algorithm that reliably detects the different graduations of pouch inflammation and neoplasms in the pouch
| Study group | Role | What they receive |
|---|---|---|
| Restorative colectomy with ileoanal pouch | Patients with restorative colectomy with ileoanal pouch who receive pouchoscopy for detection of pouchitis or neoplasm Receives: Diagnostic Test: Artificial intelligence used for image recognition in pouchoscopy |
What is being measured
The primary outcome is the main question the study is designed to answer.
AI versus endoscopist
Detection of pouchitis by AI versus assessment by endoscopist in pouchoscopy
Measured: Immediately after application of AI algorithm or after assessment of the endoscopic image by the endoscopist
AI versus pathologist
Detection of pouchitis by AI versus pathologist in pouchoscopy
Measured: Immediately after application of AI algorithm or after assessment of the microscopic image of the pouch biopsy by the pathologist
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted29 Apr 2021
- Study start1 Jun 2021
- Primary completion1 Jun 2023
- Study completion1 Jun 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Pouches, IleoanalStudies 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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 500 participants (actual)
Sponsor and investigators
- Lead sponsor
- Theresienkrankenhaus und St. Hedwig-Klinik GmbH
- Sponsor type
- University, hospital or other
- Collaborators
- Universitätsmedizin Mannheim
- Responsible party
- Sponsor
- Investigators
- Daniel Schmitz, PhD, Principal investigator, Theresienkrankenhaus Mannheim, University of Heidelberg
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04864587
- Sponsor's protocol ID
- PouchVision1.0
- Acronym
- PouchVision
- Status last verified
- Aug 2023
- First submitted
- 21 Apr 2021
- Last updated
- 29 Aug 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
van der Sommen F, de Groof J, Struyvenberg M, van der Putten J, Boers T, Fockens K, Schoon EJ, Curvers W, de With P, Mori Y, Byrne M, Bergman JJGHM. Machine learning in GI endoscopy: practical guidance in how to interpret a novel field. Gut. 2020 Nov;69(11):2035-2045. doi: 10.1136/gutjnl-2019-320466. Epub 2020 May 11.
PubMed 32393540Saifi M, Eisenmann U, Ringwald F, Liu R, Kienle P, Schmitz D. Development of a convolutional neural network for the endoscopic classification of pouchitis in patients after restorative proctocolectomy. Tech Coloproctol. 2026 Mar 17;30(1):46. doi: 10.1007/s10151-025-03273-6.
PubMed 41845084
Study at a glance
From the registry record, last updated by the sponsor on 29 Aug 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence in Image Recognition of Pouchoscopies in Patients With Restorative Proctocolectomy
- ClinicalTrials.gov ID
- NCT04864587
- Acronym / sponsor ID
- PouchVision / PouchVision1.0
- Conditions
- Pouches, Ileoanal
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 500 participants (actual)
- Lead sponsor
- Theresienkrankenhaus und St. Hedwig-Klinik GmbHUniversity, hospital or other
- Collaborators
- Universitätsmedizin Mannheim
- Study start
- 1 Jun 2021 (actual)
- Primary completion
- 1 Jun 2023 (actual)
- Study completion
- 1 Jun 2023 (actual)
- First posted
- 29 Apr 2021 (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.
The application of artificial intelligence in pouchoscopy of patients with restorative proctocolectomy might improve the diagnosis of pouchitis and neoplasms. The aim of this pilot study is to develop a convolutional neural network algorithm for pouchoscopy
Detailed description
Restorative proctocolectomy is the standard procedure for treatment of refractory severe colitis in inflammatory bowel disease as well as the standard procedure for carcinoma preventive treatment of patients with inflammatory bowel disease with colonic neoplasia and patients with familial adenomatous polyposis coli (FAP). Pouchoscopy can be used to monitor the success of therapy and to detect complications such as pouchitis or neoplasia. Artificial Intelligence assisted image recognition programs can support the examiner in finding a diagnosis and train physicians in training, objectify endoscopic findings in the context of studies and might make biopsies unnecessary, thus saving costs. The application of Artificial Intelligence in pouchoscopy has not been demonstrated to date. The aim of this study is to develop, an image recognition algorithm that reliably detects the different graduations of pouch inflammation. This requires training and fine-tuning of the image recognition program PiTorch using the largest possible amount of image data, which will be recruited from the image databases of the UMM and the Theresienkrankenhaus Mannheim. A test run for statistical evaluation will be performed on an independent cohort.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Restorative colectomy with ileoanal pouch | – | Diagnostic Test: Artificial intelligence used for image recognition in pouchoscopyPatients with restorative colectomy with ileoanal pouch who receive pouchoscopy for detection of pouchitis or neoplasm |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients with inflammatory bowel disease and status after restorative proctocolectomy with ileoanal pouch might develop pouchitis or neoplasia in the pouch.
Key inclusion criteria (1 listed)
- All patients aged ≥ 18 years with inflammatory bowel disease and status after restorative proctocolectomy with ileoanal pouch who had received a pouchoscopy
Key exclusion criteria (1 listed)
- Very poor endoscopic image quality
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 |
|---|---|---|
| Artificial intelligence used for image recognition in pouchoscopyThe aim of this study is to develop an image recognition algorithm that reliably detects the different graduations of pouch inflammation and neoplasms in the pouch | Diagnostic test | Restorative colectomy with ileoanal pouch |
Primary outcome
AI versus endoscopist
Time frame: Immediately after application of AI algorithm or after assessment of the endoscopic image by the endoscopist
Detection of pouchitis by AI versus assessment by endoscopist in pouchoscopy
AI versus pathologist
Time frame: Immediately after application of AI algorithm or after assessment of the microscopic image of the pouch biopsy by the pathologist
Detection of pouchitis by AI versus pathologist in pouchoscopy
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Aug 2023.
- Background: PubMed 32393540van der Sommen F, de Groof J, Struyvenberg M, van der Putten J, Boers T, Fockens K, Schoon EJ, Curvers W, de With P, Mori Y, Byrne M, Bergman JJGHM. Machine learning in GI endoscopy: practical guidance in how to interpret a novel field. Gut. 2020 Nov;69(11):2035-2045. doi: 10.1136/gutjnl-2019-320466. Epub 2020 May 11.
- Derived from this study: PubMed 41845084Saifi M, Eisenmann U, Ringwald F, Liu R, Kienle P, Schmitz D. Development of a convolutional neural network for the endoscopic classification of pouchitis in patients after restorative proctocolectomy. Tech Coloproctol. 2026 Mar 17;30(1):46. doi: 10.1007/s10151-025-03273-6.
- Individual participant dataSharing planned: No
Related trials for Pouches, Ileoanal
Active, not recruitingPhase 4
Mirikizumab in the Treatment of Chronic Inflammatory Conditions of the Pouch
Pouchitis, Pouches, Ileoanal
Not yet recruitingPhase 4
Tirzepatide for Ileal Pouch-anal Anastomosis (IPAA) and Chronic High Bowel Frequency (I8F-NS-X008)
Pouch, Ileal, Pouches, Ileoanal
Recruiting
Evaluation of the Ileo-anal Pouch in FAP (ENDOPOL)
Familial Adenomatous Polyposis (FAP), Pouches, Ileoanal
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.
Daniel Schmitz, PhD principal investigator
Theresienkrankenhaus Mannheim, University of Heidelberg
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 Pouches, Ileoanal, run by Theresienkrankenhaus und St. Hedwig-Klinik GmbH 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 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: finished, as of the sponsor's last update on 29 Aug 2023. 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?
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?
AI versus endoscopist (time frame: Immediately after application of AI algorithm or after assessment of the endoscopic image by the endoscopist). The study lists 2 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 NCT04864587, which also lists 2 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 29 Aug 2023.