- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03761771
Artificial Intelligence Identifying Polyps in Real-world Colonoscopy
December 14, 2018 updated by: Zhaoshen Li
Validating the Performance of Artificial Intelligence in Identifying Polyps in Real-world Colonoscopy
Recently, artificial intelligence (AI) assisted image recognition has made remarkable breakthroughs in various medical fields with the developing of deep learning and conventional neural networks (CNNs).
However, all current AI assisted-diagnosis systems (ADSs) were established and validated on endoscopic images or selected videos, while its actual assisted-diagnosis performance in real-world colonoscopy is up to now unknown.
Therefore, we validated the performance of an ADS in real-world colonoscopy, which is based on deep learning algorithm and CNNs, trained and tested in multicenter datasets of 20 endoscopy centers.
Study Overview
Status
Completed
Conditions
Intervention / Treatment
Detailed Description
The ADS were established in changhai digestive endoscopy center to assess its efficacy in clinical practice.
The ADS automatically initiated once the ileocecal valve was pictured by the colonoscopist or the colonoscopist recorded any image of colon during the insertion.
When colonoscopists withdrew the colonoscopies and inspect the colons, the video streaming of colonoscopies was real-time switched to the ADS, which made it feasible to identify and classify lesions in real time.
Colonoscopists were invited to respond if they doubted potential polyps in the screen, and the ADS also made a voice when identifying potential polyps, followed by repeatedly inspecting to confirm the existence of lesions.
The voice of ADS could be real-time heard by colonoscopists, while the screen of ADS was placed right behind colonoscopists, where polyps identified by ADS could be seen after the colonoscopists' turning but not simultaneously.
The lesion detection by ADS or colonoscopists were determined as follow: A. polyps only identified by ADS, which was considered to be missed by colonoscopists: polyps were reported by the ADS and the colonoscopists did not know the location of polyps without reminder of the ADS until the polyps disappeared from the view; B. polyps first identified by ADS: polyps were first reported by the ADS and the colonoscopists also later knew the location of polyps by themselves; C. polyps simultaneously identified by the ADS and colonoscopists: the time of reporting polyps was closely synchronal (within 1 second); D. polyps first reported by colonoscopists: polyps were first reported by the colonoscopists and the ADS also later identified the location of polyps before the colonoscopists unfolded and pictured the polyps; E. polyps only reported by colonoscopists, which was considered to be missed by the ADS: polyps were reported by the colonoscopists and the ADS did not identify the location of polyps until colonoscopists unfolded and pictured the polyps.
Besides, the false-positives of real-world ADS were also reported with potential causes analyzed by colonoscopists.
Study Type
Observational
Enrollment (Actual)
209
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
-
-
Shanghai, China, 200433
- Changhai Hospital, Second Military Medical University
-
Shanghai, China, 200433
- Changhai Hospital
-
-
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
Ages Eligible for Study
18 years to 75 years (Adult, Older Adult)
Accepts Healthy Volunteers
No
Genders Eligible for Study
All
Sampling Method
Non-Probability Sample
Study Population
consecutive outpatient who recieved colonoscopy
Description
Inclusion Criteria:
- patients receiving screening colonoscopy
- patients receiving surveillance colonoscopy
- patients receiving diagnostic colonoscopy
Exclusion Criteria:
- patients with declined consent
- patients with poor bowel preparation
- patients with failed cecal intubation
- patients with colonic resection
- patients with inflammatory bowel diseases
- patients with polyposis
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: Case-Only
- Time Perspectives: Prospective
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
colonoscopy withdrawal with the ADS monitoring
The ADS automatically initiated once the ileocecal valve was pictured by the colonoscopist or the colonoscopist recorded any image of colon during the insertion.
When colonoscopists withdrew the colonoscopies and inspect the colons, the video streaming of colonoscopies was real-time switched to the ADS, which made it feasible to identify and classify lesions in real time.
|
During the testing of trained ADS, when the system doubts colonic lesions from the input data of the test images, a rectangular frame was displayed in the endoscopic image to surround the lesion.
If the system confirmed it as the colonic lesions, a sound of reminder will be played and the types of lesions (non-adenomatous polyps, adenomatous polyps and colorectal cancers) will be classified by the system.
We adopted several standards to define the identification and classification of colonic lesions: 1) when the system identified and confirmed any lesion in the images of no polyps or cancers, the results were judged to be false-positive.
2) when the system both confirmed and correctly localized the lesions in images (IoU > 0.3), the results were judged to be true-positive.
3) when the system did not confirm or correctly localize the lesions, the results were judged as false-negative.
4) when system confirmed no lesions in the normal images, the results were judged to be true-negative.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
sensitivity of the ADS in identifying polyps
Time Frame: 1 hour
|
Polyps that were only reported by colonoscopists were considered to be missed by the ADS (polyps were reported by the colonoscopists and the ADS did not identify the location of polyps until colonoscopists unfolded and pictured the polyps.)
|
1 hour
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
false positves of the ADS per colonoscopy withdrawal
Time Frame: 1 hour
|
when the system identified and confirmed any lesion in the images with no polyps or cancers appearing, the results were judged to be false-positive.
|
1 hour
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Byrne MF, Chapados N, Soudan F, Oertel C, Linares Perez M, Kelly R, Iqbal N, Chandelier F, Rex DK. Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model. Gut. 2019 Jan;68(1):94-100. doi: 10.1136/gutjnl-2017-314547. Epub 2017 Oct 24.
- Wang Z, Meng Q, Wang S, Li Z, Bai Y, Wang D. Deep learning-based endoscopic image recognition for detection of early gastric cancer: a Chinese perspective. Gastrointest Endosc. 2018 Jul;88(1):198-199. doi: 10.1016/j.gie.2018.01.029. No abstract available.
- Urban G, Tripathi P, Alkayali T, Mittal M, Jalali F, Karnes W, Baldi P. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy. Gastroenterology. 2018 Oct;155(4):1069-1078.e8. doi: 10.1053/j.gastro.2018.06.037. Epub 2018 Jun 18.
- Wang Z, Zhao S, Bai Y. Artificial Intelligence as a Third Eye in Lesion Detection by Endoscopy. Clin Gastroenterol Hepatol. 2018 Sep;16(9):1537. doi: 10.1016/j.cgh.2018.04.032. No abstract available.
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)
November 1, 2018
Primary Completion (Actual)
December 10, 2018
Study Completion (Actual)
December 10, 2018
Study Registration Dates
First Submitted
November 30, 2018
First Submitted That Met QC Criteria
November 30, 2018
First Posted (Actual)
December 3, 2018
Study Record Updates
Last Update Posted (Actual)
December 17, 2018
Last Update Submitted That Met QC Criteria
December 14, 2018
Last Verified
December 1, 2018
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- AI-1
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.
Clinical Trials on Sensitivity of the ADS in Identifying Polyps in Real-world Colonoscopy
-
National Health Research Institutes, TaiwanCompleted
-
Inje UniversityCompletedThe Timing of Bowel Preparation in Outpatient ColonoscopyKorea, Republic of
-
Mayo ClinicCompletedEvaluate the Role of Real-time Imaging in Needle Placement | Evaluate the Workflow and Effectiveness of Realtime Imaging Versus Standard MR ImagingUnited States
-
University Hospital, Clermont-FerrandInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement and other collaboratorsTerminatedThe Objective is to Confirm the Role of Gluten in Triggering the Digestive and Extradigestive Symptoms of NCGSFrance
-
Aaron FensterCompletedDetermine the Number of Anatomical Sites at Which Successful Thermoacoustic Fat Measurements Can be Made From Five Acquisitions Using the FLIP ITA Device | Determine the Correlation of Fat Measures Obtained by the FLIP Device and Those Obtained From Quantitative MRI | Provide Insight...Canada
-
Johannes Gutenberg University MainzUnknownFocus of the Study is to Evaluate a New Developed Deep-learning Computer-aided Detection System in Combination With LCI for Colorectal Polyp DetectionGermany
-
Chinese University of Hong KongUnknownTo Evaluate the Sensitivity and Specificity of a Test Kit in Hong KongHong Kong
Clinical Trials on colonoscopy withdrawal with the ADS monitoring
-
Washington University School of MedicineTerminatedColorectal Cancer | Rectal Cancer | Colon CancerUnited States
-
Renmin Hospital of Wuhan UniversityUnknown
-
Instituto Ecuatoriano de Enfermedades DigestivasCompletedColonic Polyp | Colonic Neoplasms | Colonic AdenomaEcuador
-
Istituto Clinico HumanitasRecruiting
-
Oslo University HospitalSouth-Eastern Norway Regional Health AuthorityRecruitingLabor Pain | Hemodynamic Instability | Fetal Distress | Myocardium; Ischemic | Newborn AsphyxiaNorway
-
University Hospital FreiburgCompletedArrhythmias, Cardiac | MonitoringSwitzerland
-
The First Affiliated Hospital of Guangzhou Medical...Guangdong Provincial Hospital of Traditional Chinese Medicine; Guangzhou First... and other collaboratorsRecruitingCOPD | Hypercapnic Respiratory FailureChina
-
Maxima Medical CenterZonMw: The Netherlands Organisation for Health Research and DevelopmentRecruitingCaesarean Section | Electrocardiography | Cardiotocography | Fetal Monitoring | Non-invasiveNetherlands
-
Mental Health Services in the Capital Region, DenmarkMaria Faurholt-Jepsen, MD, DMSc; The Mental Health Services in the Capital...RecruitingBipolar DisorderDenmark