Development and Validation of an Artificial Intelligence-assisted Strategy Selection System for Colonoscopy Cleaning

November 14, 2020 updated by: Renmin Hospital of Wuhan University
Patients with poor inadequate bowel preparation need to undergo secondary colonoscopy. but the evaluation of intestinal cleanliness is judged by doctors subjectively. there are no objective and effective criteria to guide the evaluation. We use the deep learning technique to develop the EndoAngel with real-time intestinal cleanliness assessment. It can derive a decision curve for bowel cleanliness based on the relationship between the percentage of bowel segments with a Boston score of 1 and the adenoma detection rate. It can help doctors to identify patients who need a second colonoscopy, and provide a new way for artificial intelligence in improving the detection rate of colonoscopic adenomas.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Unknown

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Detailed Description

Colorectal disease as a common human disease seriously affects the health of human life. With the aging of the population, the change of diet structure and the aggravation of environmental pollution, the incidence of colorectal diseases, such as colon cancer, Colon Polyp and inflammatory bowel disease, has gradually increased.

Colonoscopy is the simplest and most widely available screening procedure for colorectal cancer(CRC) prevention and early detection. Colonoscopy can clearly observe the small changes in the terminal ileum and the colorectal, such as erosion, ulcers, bleeding, congestion, edema, polyps, early cancer, and so on. Colonoscopy can biopsy the lesion site for pathological examination, to histologically qualitative the characterization of mucosal lesions, such as inflammation, polyp nature, the degree of differentiation of cancer, and so on. It is helpful to understand the severity of the lesion and guide the formulation of the correct treatment plan or judgment of treatment effect. Colonoscopy can also be the minimally invasive endoscopic treatment of colorectal polyps, early cancer, bleeding, foreign bodies and other diseases.

Because the quality of bowel preparation affects the colonoscopy's ability to detect adenomas and polyps, adequate bowel preparation is necessary to ensure optimal use of colonoscopy in CRC prevention. Almost all clinical guidelines recommend adequate bowel preparation before colonoscopy. However, up to one third of colonoscopies have been found to show inadequate bowel preparation, which is estimated to increase the cost of colonoscopies by 12% to 22%. And there are 20% of patients' bowel is not adequately prepared. When the patient's bowel preparation is inadequate, the difficulty of flushing may lead to missed detection of adenomas. so doctors need to accurately identify such patients and tell them to have a second colonoscopy after a full bowel cleanse. However, the evaluation of intestinal cleanliness is decided by doctors subjectively, and there is no objective and effective scoring standard to guide the patients to accept the second colonoscopy.

Deep learning is an important breakthrough in the field of artificial intelligence in the past decade. It has great potential in extracting tiny features in image analysis and image classification. In 2017, the journal Nature published a paper showing that using artificial intelligence to diagnose skin diseases can reach the level of experts. Subsequently, in the field of digestive endoscopy, more and more studies began to apply artificial intelligence to assist doctors to find polyps and improve the detection rate of polyps and adenomas.Urban, G. team used artificial intelligence to identify polyps with 95% sensitivity. Misawa, M team used artificial intelligence to identify polyps with 90% sensitivity. The purpose of our research group is to develop the EndoAngel with real-time intestinal cleanliness assessment. It can derive a decision curve for bowel cleanliness based on the relationship between the percentage of bowel segments with a Boston score of 0-1 and the detection rate of adenomas. It can help endoscopists to identify patients who need a second colonoscopy, to avoid the missed adenomas and the high cost of cleaning time caused by the wrong decision-making. At the same time, artificial intelligence is in the preliminary research stage in the field of digestive endoscopy, our research results are expected to provide new ideas in improving the detection rate of colonoscopic adenomas.

The study Process is: Subjects who met all inclusion criteria and did not meet all exclusion criteria were included in the study before colonoscopy. During the colonoscopy, the endoscopists need to remain in the same without withdrawal while flushing the bowel. The biopsied patients are followed up for one week. the non-biopsied patients are followed up at the end of their colonoscopy , and the results are sent to an independent data analysis team for review. We will collect the patients' video and exclude the clips of irrigation, biopsy, and observation of polyp. Then the EndoAngel evaluates the Boston Bowel Preparation Scale of the ascending colon, transverse colon and descending colon, and calculates the proportion of 1 Score.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Anticipated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
657

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Contact Backup

Study Locations

  • China
    • Hubei
      • Wuhan, Hubei, China, 430000
        • Recruiting
        • Renmin Hospital
        • Contact:
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

The primary endpoint was the detection rate of Adenomas and the percentage of 1 score to get a correlation curve. In order to calculate the sample size more accurately, we prepare to collect 200 colonoscopies to explore the sample distribution, and then calculate the sample size according to the sample distribution.

Description

Inclusion Criteria:

  • Male or female aged 18 or above;
  • Colonoscopy is needed to further clarify the characteristics of digestive tract diseases;
  • Patients able to give informed consent were eligible to participate.
  • Able and willing to comply with all study process.
  • No intestinal organic disease.

Exclusion Criteria:

  • Has participated in other clinical trials, signed informed consent and was in the follow-up period of other clinical trials.
  • Has participated in clinical trials of the drug and is in the elution period of the experimental drug or control drug.
  • Drug or alcohol abuse or psychological disorder in the last 5 years.
  • Patients in pregnancy or lactation.
  • Known polyposis syndromes.
  • Gastrointestinal Bleeding.
  • A history of inflammatory bowel disease, colorectal cancer and colorectal surgery.
  • A history of colorectal surgery.
  • Patients with a contraindication for biopsy.
  • Previous history of allergy to ingredient of bowel cleanser.
  • Patients with intestinal obstruction or perforation, toxic megacolon, Colectomy, heart failure (Grade III or IV) , severe cardiovascular disease, severe liver failure or renal insufficiency, etc. .
  • Researchers believe that the patient is not suitable to participate in the trial.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
The adenoma detection rate (ADR)
Time Frame: 2020.08.7
ADR was calculated by dividing the total number of patients being detected adenomas by the number of colonoscopies.
2020.08.7
Cleanliness assessment of different intestinal segment in the artificial intelligence system
Time Frame: 2020.08.7
The Artificial intelligence evaluates the Boston Bowel Preparation score of the ascending colon, transverse colon and descending colon in real-time, and calculates the proportion of 1 Score
2020.08.7

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
The polyp detection rate (PDR)
Time Frame: 2020.08.7
PDR was calculated by dividing the total number of patients being detected polyps by the number of colonoscopies
2020.08.7
The mean number of polyps per patient (MNP)
Time Frame: 2020.08.7
MNP was calculated by dividing the total number of polyps by the number of colonoscopies.
2020.08.7
The mean number of adenomas per patient (MAP)
Time Frame: 2020.08.7
MAP was calculated by dividing the total number of adenomas by the number of colonoscopies
2020.08.7
PDR of different sizes
Time Frame: 2020.08.7
It was calculated by dividing the number of patients with polyps that large (≥10 mm), small (6-9 mm) and diminutive (≤5 mm) by the number of patients undergoing colonoscopy.
2020.08.7
MNP of different sizes
Time Frame: 2020.08.07
It was calculated by dividing the number of polyps that large (≥10 mm), small (6-9 mm) and diminutive≤5 mm) by the number of patients undergoing colonoscopy.
2020.08.07
ADR of different sizes
Time Frame: 2020.08.07
It was calculated by dividing the number of patients with adenomas that large (≥10 mm), small (6-9 mm) and diminutive≤5 mm) by the number of patients undergoing colonoscopy.
2020.08.07
MAP of different sizes
Time Frame: 2020.08.07
It was calculated by dividing the number of adenomas that large (≥10 mm), small (6-9 mm) and diminutive≤5 mm) by the number of patients undergoing colonoscopy.
2020.08.07
ADR of different location
Time Frame: 2020.08.07
It was calculated by dividing the number of patients with adenomas detected in the rectum, sigmoid colon, descending colon, transverse colon, ascending colon, ileocecal region etc. by the Total number of patients undergoing colonoscopy.
2020.08.07
MAP of different location
Time Frame: 2020.08.07
It was calculated by dividing the number of adenomas detected in the rectum, sigmoid colon, descending colon, transverse colon, ascending colon, ileocecal region etc. by the Total number of patients undergoing colonoscopy.
2020.08.07
Scope-forward time and Withdrawal time
Time Frame: 2020.08.07
Scope-forward time: The time is taken to go from the the rectum to the ileocecal region. Withdrawal time. The time is taken to finish the examination from the beginning of the ileocecal region.
2020.08.07
Boston Bowel Preparation Score of endoscopists
Time Frame: 2020.08.07
Endoscopists evaluate the different intestinal segment according Boston Bowel Preparation Scale(BBPS)
2020.08.07
Cecal intubation rate
Time Frame: 2020.08.07
It was calculated by dividing the number of colonoscopies that get to the ileocecal region by the total number of colonoscopies.
2020.08.07

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Renmin Hospital of Wuhan University

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Principal Investigator: Honggang Yu, Doctor, Renmin Hospital of Wuhan University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
May 11, 2020

Primary Completion (Actual)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
October 15, 2020

Study Completion (Anticipated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
November 16, 2020

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
June 20, 2020

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
June 20, 2020

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
June 24, 2020

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
November 17, 2020

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
November 14, 2020

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
November 1, 2020

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • WDRY2019-KK073

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

Yes

IPD Plan Description

Individual de-identified participant data that underlie the results reported in this article and study protocol will be shared for investigators whose proposed use of the data has been approved by an independent review committee. Data can only be used to achieve aims in the approved proposal. Data disclosure begins 9 months and ends 36 months after article publication. To gain access, data requesters will need to sign a data access agreement. Proposals should be directed to the corresponding author.

IPD Sharing Time Frame

Data disclosure begins 9 months and ends 36 months after article publication.

IPD Sharing Access Criteria

To gain access, data requesters will need to sign a data access agreement. Proposals should be directed to the corresponding author.

IPD Sharing Supporting Information Type

  • Study Protocol

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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