Colonic DiseasesNCT04216901
A Single Center Study on the Effectiveness and Safety of Polyp Classification With Artificial Intelligence
An observational study of Colonic Diseases and Artificial Intelligence, run by Renmin Hospital of Wuhan University at 1 site in China.
Trial summary
This is an artificial intelligence-based optical endoscopic polyp diagnosis system that can assist endoscopic doctors in diagnosing polyps and improve the quality of training in clinical Settings. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Colonic Diseases, Artificial Intelligence
- What is being tested?
- Endoscopists refer to AI for diagnosis
- How many people
- 70 participants
- Where
- 1 siteChina
- Study dates
- 24 Dec 2019to 30 Jun 2021
- 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
- Adult, Older adult
Study population: Patients with larger than 10mm in size intestinal polyps.
Who may be able to join
- male or female aged 18 or above;
- colonoscopy and related examinations should be performed to further clarify the characteristics of digestive tract diseases;
- be able to read, understand and sign the informed consent;
- the researcher believes that the subject can understand the process of the clinical study, is willing and able to complete all the study procedures and follow-up visits, and cooperate with the study procedures;
- patients with > 1cm lesion detected by colonoscopy, requiring magnification staining or surgical resection.
Who cannot join
- have participated in other clinical trials, signed the informed consent and have been in the follow-up period of other clinical trials;
- drug or alcohol abuse or psychological disorder in the last 5 years;
- pregnant or nursing women;
- subjects with previous history of intestinal surgery;
- the researcher considers that the subject is not suitable for colonoscopy and related examination;
- high-risk diseases or other special conditions that the investigator considers inappropriate for the subject to participate in the clinical trial.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Renmin Hospital of Wuhan University
Wuhan, Hubei, 430060
Honggang Yu, MD, +8613871281899, yuhonggang1968@163.com
About this study
Official title: A Single Center Study on the Effectiveness and Safety of Polyp Detection and Polyp Classification With Artificial Intelligence
This is an artificial intelligence-based optical endoscopic polyp diagnosis system that can assist endoscopic doctors in diagnosing polyps and improve the quality of training in clinical Settings.
Read the detailed description
Large sessile and laterally spreading colorectal lesions(LSLs) are increasingly encountered during colonoscopy. LSLs have an increased risk of harbouring invasive cancer and can be challenging to excise endoscopically. Wide-field endoscopic mucosal resection (WF-EMR) is widely used in treating LSLs. In the East, meanwhile endoscopic submucosal dissection (ESD) is the dominant technique due to its ability to achieve en bloc resection in over 80% of cases. Many papers have demonstrated that selective-esd has the highest economic benefit. The key is to find a reliable way to select.
- Conditions
- Colonic Diseases, Artificial Intelligence
- Being tested
- Endoscopists refer to AI for diagnosis
- Keywords
- Colonic Neoplasms
- Medical subject headings
- Colonic Diseases, Colonic Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Endoscopists refer to AI for diagnosisDiagnostic test
The AI will provide a pathological prediction of the lesion during colonoscopy.
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of evaluating the feasibility of selective-ESD
Calculate the accuracy of ai's judgment on whether ESD should be implemented.Accuracy is: the machine over a period of time to judge the results are consistent with the pathological lesion number of molecules, all lesions detected by a period of time for the denominator expressed as a percentage.The gold standard is the pathological results of diagnostic treatment. After the specimen was removed, the area suspected by endoscopists of early cancer was marked with Indian ink for pathological recovery.The specimens were then placed in formalin and fixed for 24 hours until the ink was a little dry.Even if the specimen is cut into 2mm-wide shapes, the suspected area can be identified by Indian ink staining under a microscope.The doctor suspected cancer patients were followed up for 60 days.
Measured: 2019.12.24-2020.12.31
Accuracy of Vision location
Calculate the accuracy of the machine in locating the field of vision.The accuracy was as follows: the visual field localization results of the machine on the ESD intraoperative lesion screen captures were the numerator consistent with the number of visual fields determined by multiple endoscopists, and the number of visual fields of all localization in the same operation was the denominator, and the result was expressed as a percentage.The consistent results of visual field positioning by multiple endoscopic physicians watching the operation video were the gold standard.Patients with suspected cancer were followed up for 60 days, and the most serious pathological diagnosis within 60 days was taken as the diagnosis of the patient's disease.Patients whose doctors deemed no risk were followed until the end of colonoscopy.
Measured: 2019.12.24-2020.12.31
Secondary outcomes (3)
Consistent of classification among different endoscopists
Consistent of classification among different endoscopists
Measured: 2019.12.24-2020.12.31
Consistent of classification between diagnostic system and endoscopists
Consistent of classification between diagnostic system and endoscopists
Measured: 2019.12.24-2020.12.31
Consistent of vision positioning between diagnostic system and endoscopists
Consistent of vision positioning between diagnostic system and endoscopists
Measured: 2019.12.24-2020.12.31
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Jan 2020
- Study start24 Dec 2019
- Primary completion31 Dec 2020 (estimated)
- Study completion30 Jun 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colonic DiseasesStudies 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
- Prospective
- Enrolment
- 70 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Renmin Hospital of Wuhan University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Yu Honggang, MD, Principal investigator, Wuhan University Renmin Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04216901
- Sponsor's protocol ID
- EA-19-003
- Status last verified
- Oct 2020
- First submitted
- 31 Dec 2019
- Last updated
- 20 Oct 2020
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 20 Oct 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Single Center Study on the Effectiveness and Safety of Polyp Detection and Polyp Classification With Artificial Intelligence
- ClinicalTrials.gov ID
- NCT04216901
- Acronym / sponsor ID
- EA-19-003
- Conditions
- Colonic Diseases, Artificial Intelligence
- Keywords
- Colonic Neoplasms
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 70 participants (estimated)
- Lead sponsor
- Renmin Hospital of Wuhan UniversityUniversity, hospital or other
- Study start
- 24 Dec 2019 (actual)
- Primary completion
- 31 Dec 2020 (estimated)
- Study completion
- 30 Jun 2021 (estimated)
- First posted
- 3 Jan 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.
This is an artificial intelligence-based optical endoscopic polyp diagnosis system that can assist endoscopic doctors in diagnosing polyps and improve the quality of training in clinical Settings.
Detailed description
Large sessile and laterally spreading colorectal lesions(LSLs) are increasingly encountered during colonoscopy. LSLs have an increased risk of harbouring invasive cancer and can be challenging to excise endoscopically. Wide-field endoscopic mucosal resection (WF-EMR) is widely used in treating LSLs. In the East, meanwhile endoscopic submucosal dissection (ESD) is the dominant technique due to its ability to achieve en bloc resection in over 80% of cases. Many papers have demonstrated that selective-esd has the highest economic benefit. The key is to find a reliable way to select.
Study design
- Observational model
- Other
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Patients with larger than 10mm in size intestinal polyps.
Key inclusion criteria (5 listed)
- male or female aged 18 or above;
- colonoscopy and related examinations should be performed to further clarify the characteristics of digestive tract diseases;
- be able to read, understand and sign the informed consent;
- the researcher believes that the subject can understand the process of the clinical study, is willing and able to complete all the study procedures and follow-up visits, and cooperate with the study procedures;
- patients with > 1cm lesion detected by colonoscopy, requiring magnification staining or surgical resection.
Key exclusion criteria (6 listed)
- have participated in other clinical trials, signed the informed consent and have been in the follow-up period of other clinical trials;
- drug or alcohol abuse or psychological disorder in the last 5 years;
- pregnant or nursing women;
- subjects with previous history of intestinal surgery;
- the researcher considers that the subject is not suitable for colonoscopy and related examination;
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 |
|---|---|---|
| Endoscopists refer to AI for diagnosisThe AI will provide a pathological prediction of the lesion during colonoscopy. | Diagnostic test | – |
Primary outcome
Accuracy of evaluating the feasibility of selective-ESD
Time frame: 2019.12.24-2020.12.31
Calculate the accuracy of ai's judgment on whether ESD should be implemented.Accuracy is: the machine over a period of time to judge the results are consistent with the pathological lesion number of molecules, all lesions detected by a period of time for the denominator expressed as a percentage.The gold standard is the pathological results of diagnostic treatment. After the specimen was removed, the area suspected by endoscopists of early cancer was marked with Indian ink for pathological recovery.The specimens were then placed in formalin and fixed for 24 hours until the ink was a little dry.Even if the specimen is cut into 2mm-wide shapes, the suspected area can be identified by Indian ink staining under a microscope.The doctor suspected cancer patients were followed up for 60 days.
Accuracy of Vision location
Time frame: 2019.12.24-2020.12.31
Calculate the accuracy of the machine in locating the field of vision.The accuracy was as follows: the visual field localization results of the machine on the ESD intraoperative lesion screen captures were the numerator consistent with the number of visual fields determined by multiple endoscopists, and the number of visual fields of all localization in the same operation was the denominator, and the result was expressed as a percentage.The consistent results of visual field positioning by multiple endoscopic physicians watching the operation video were the gold standard.Patients with suspected cancer were followed up for 60 days, and the most serious pathological diagnosis within 60 days was taken as the diagnosis of the patient's disease.Patients whose doctors deemed no risk were followed until the end of colonoscopy.
3 secondary outcomes
Consistent of classification among different endoscopists
Time frame: 2019.12.24-2020.12.31
Consistent of classification between diagnostic system and endoscopists
Time frame: 2019.12.24-2020.12.31
Consistent of vision positioning between diagnostic system and endoscopists
Time frame: 2019.12.24-2020.12.31
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Oct 2020.
- Individual participant dataSharing planned: No
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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.
Yu Honggang, MD principal investigator
Wuhan University Renmin Hospital
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 Colonic Diseases and Artificial Intelligence, run by Renmin Hospital of Wuhan 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 5 inclusion and 6 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 20 Oct 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 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 Yu Honggang, MD (+86 13871281899, yuhonggang1968@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of evaluating the feasibility of selective-ESD (time frame: 2019.12.24-2020.12.31). 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?
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 20 Oct 2020.