Ulcerative ColitisNCT04131530
Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using pCLE With Artificial Intelligence
An observational study of Ulcerative Colitis and Artificial Intelligence, run by Shandong University at 1 site in China.
Trial summary
Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables to evaluate the inflammation activity of ulcerative colitis with excellent correlation with histopathology. However this requires much experience, which limits the application of pCLE. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Ulcerative Colitis, Artificial Intelligence, Confocal Laser Endomicroscopy
- What is being tested?
- The diagnosis of Artificial Intelligence and endoscopist
- How many people
- 60 participants
- Where
- 1 siteChina
- Study dates
- Oct 2019to Dec 2019
- 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 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Consecutive patients who receive the endoscopy pCLE examination and screened that fulfill the eligibility criteria at Qilu Hospital, Shandong University will be enrolled into the study
Who may be able to join
- aged between 18 and 80; diagnosed as UC
Who cannot join
- Patients under conditions unsuitable for performing CLE including coagulopathy , impaired renal or hepatic function, pregnancy or breastfeeding, and known allergy to fluorescein sodium; Inability to provide informed consent
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Department of Gastroenterology, Qilu Hospital, Shandong University
Jinan, Shandong, 250012
Yanqing Li, PhD. MD., 053182169385, liyanqing@sdu.edu.cn
About this study
Official title: Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using Probe-based Confocal Laser Endomicroscopy With Artificial Intelligence
Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables to evaluate the inflammation activity of ulcerative colitis with excellent correlation with histopathology. However this requires much experience, which limits the application of pCLE. The investigators designed a computer-aided diagnosis program using deep neural network to make diagnosis automatically in pCLE examination and contrast its performance with endoscopists.
- Being tested
- The diagnosis of Artificial Intelligence and endoscopist
- Medical subject headings
- Colitis, Ulcerative
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
The diagnosis of Artificial Intelligence and endoscopistDiagnostic test
When the colon mucosa is observed using pCLE, endoscopist and AI will make a diagnosis independently. In addition, the endoscopist can not see the diagnosis of AI.
| Study group | Role | What they receive |
|---|---|---|
| Colon mucosa observed by pCLE | pCLE is used to evaluate the inflammation activity in different parts of the colon mucosa Receives: Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist |
What is being measured
The primary outcome is the main question the study is designed to answer.
The diagnosis efficiency of Artificial Intelligence
The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for evaluation of inflammation activity of UC on pCLE examination.
Measured: 3 months
Secondary outcomes (1)
Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists
The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV ) between Artificial Intelligence and endoscopists.
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Oct 2019
- Study startOct 2019 (estimated)
- Primary completionDec 2019 (estimated)
- Study completionDec 2019 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Ulcerative ColitisStudies 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
- Prospective
- Enrolment
- 60 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shandong University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yanqing Li, Shandong University
- Investigators
- Yanqing Li, Principal investigator, Qilu Hospital of Shandong University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04131530
- Sponsor's protocol ID
- 2019SDU-QILU-10
- Status last verified
- Oct 2019
- First submitted
- 17 Oct 2019
- Last updated
- 18 Oct 2019
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 18 Oct 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Automatic Evaluation of Inflammation Activity in Ulcerative Colitis Using Probe-based Confocal Laser Endomicroscopy With Artificial Intelligence
- ClinicalTrials.gov ID
- NCT04131530
- Acronym / sponsor ID
- 2019SDU-QILU-10
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 60 participants (estimated)
- Lead sponsor
- Shandong UniversityUniversity, hospital or other
- Study start
- Oct 2019 (estimated)
- Primary completion
- Dec 2019 (estimated)
- Study completion
- Dec 2019 (estimated)
- First posted
- 18 Oct 2019 (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.
Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables to evaluate the inflammation activity of ulcerative colitis with excellent correlation with histopathology. However this requires much experience, which limits the application of pCLE. The investigators designed a computer-aided diagnosis program using deep neural network to make diagnosis automatically in pCLE examination and contrast its performance with endoscopists.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Colon mucosa observed by pCLE | – | Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopistpCLE is used to evaluate the inflammation activity in different parts of the colon mucosa |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Consecutive patients who receive the endoscopy pCLE examination and screened that fulfill the eligibility criteria at Qilu Hospital, Shandong University will be enrolled into the study
Key inclusion criteria (1 listed)
- aged between 18 and 80; diagnosed as UC
Key exclusion criteria (1 listed)
- Patients under conditions unsuitable for performing CLE including coagulopathy , impaired renal or hepatic function, pregnancy or breastfeeding, and known allergy to fluorescein sodium; Inability to provide informed consent
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 |
|---|---|---|
| The diagnosis of Artificial Intelligence and endoscopistWhen the colon mucosa is observed using pCLE, endoscopist and AI will make a diagnosis independently. In addition, the endoscopist can not see the diagnosis of AI. | Diagnostic test | Colon mucosa observed by pCLE |
Primary outcome
The diagnosis efficiency of Artificial Intelligence
Time frame: 3 months
The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for evaluation of inflammation activity of UC on pCLE examination.
1 secondary outcome
Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists
Time frame: 3 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Oct 2019.
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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. This study is not recruiting at the moment.
Yanqing Li principal investigator
Qilu Hospital of Shandong University
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 Ulcerative Colitis and Artificial Intelligence, run by Shandong University at 1 site in China.
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: status not confirmed, as of the sponsor's last update on 18 Oct 2019. 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 China. 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?
Contact Yanqing Li (053182169385, liyanqing@sdu.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The diagnosis efficiency of Artificial Intelligence (time frame: 3 months). 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 18 Oct 2019.