- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04203264
Real-Time Identification System of Magnetically Controlled Capsule Endoscopy Using Artificial Intelligence
Real-Time Identification of Gastric Lesions and Anatomical Landmarks During Magnetically Controlled Capsule Endoscopy Using Artificial Intelligence
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Magnetically controlled capsule endoscopy (MCE) has been used in clinical practice for gastric examination, with high sensitivity and specificity of 90.4% and 94.7%, respectively.
Therefore, a real-time auxiliary system based on convolutional neural network deep learning framework was developed to assist clinicians to improve the quality in MCE examinations.
Patients referred for magnetically controlled capsule endoscopy (MCE) in the participating center were prospectively enrolled. After passage through the esophagus, physician will finish the gastric examination under magnetic steering with the real-time auxiliary system. Professional operators guarantee the integrity of the examination and the diagnostic results of professional endoscopist was used as the gold standard. The system diagnosis results was recorded at the same time. The sensitivity, delay time, specificity of lesions and anatomical landmarks will be analyzed.
Study Type
Enrollment (Anticipated)
Contacts and Locations
Study Contact
- Name: Zhuan Liao
- Phone Number: 008621-31161004
- Email: liaozhuan@smmu.edu.cn
Study Locations
-
-
-
Shanghai, China, 200433
- Recruiting
- Changhai Hospital
-
Sub-Investigator:
- Jun Pan
-
Contact:
- Zhuan Liao
- Phone Number: 008621-31161004
- Email: liaozhuan@smmu.edu.cn
-
Sub-Investigator:
- Ji Xia
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- With or without gastrointestinal complaints
- Scheduled to undergo a capsule endoscopy for both stomach and small bowel
- Signed the informed consents before joining this study
Exclusion Criteria:
- Dysphagia or symptoms of gastric outlet obstruction, suspected or known intestinal stenosis, overt gastrointestinal bleeding, history of upper gastrointestinal surgery or abdominal surgery altering gastrointestinal anatomy
- Refused abdominal surgery to take out the capsule in case of capsule retention
- Implanted pacemaker, except the pacemaker is compatible with MRI
- Other implanted electromedical devices or magnetic metal foreign bodies
- Pregnancy or suspected pregnancy
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Prospective
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Sensitivity
Time Frame: up to 2 weeks
|
The sensitivity of lesions detected by system
|
up to 2 weeks
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Delay time
Time Frame: up to 2 weeks
|
Average preprocessing and displaying times before and after the execution of system
|
up to 2 weeks
|
Specificity
Time Frame: up to 2 weeks
|
The specificity of detected by system
|
up to 2 weeks
|
Accuracy of anatomic landmarks identification
Time Frame: up to 2 weeks
|
Accuracy of anatomic landmarks ( cardia, fundus, body, lesser curvature, greater curvature, angle, antrum and pylorus) identified by real-time identification system
|
up to 2 weeks
|
Completeness of real-time observation with assistance
Time Frame: up to 2 weeks
|
Whether the clinician observed all anatomic landmarks of stomach (cardia, fundus, body, angulus, antrum and pylorus).
|
up to 2 weeks
|
Accuracy of heat map
Time Frame: up to 2 weeks
|
The rate of the highlighted area indicated in the lesion
|
up to 2 weeks
|
Lesion detection yield
Time Frame: up to 2 weeks
|
The ratio of lesions detected by system to all lesions
|
up to 2 weeks
|
Collaborators and Investigators
Sponsor
Investigators
- Study Chair: Zhuan Liao, Changhai Hospital
Publications and helpful links
General Publications
- Liao Z, Hou X, Lin-Hu EQ, Sheng JQ, Ge ZZ, Jiang B, Hou XH, Liu JY, Li Z, Huang QY, Zhao XJ, Li N, Gao YJ, Zhang Y, Zhou JQ, Wang XY, Liu J, Xie XP, Yang CM, Liu HL, Sun XT, Zou WB, Li ZS. Accuracy of Magnetically Controlled Capsule Endoscopy, Compared With Conventional Gastroscopy, in Detection of Gastric Diseases. Clin Gastroenterol Hepatol. 2016 Sep;14(9):1266-1273.e1. doi: 10.1016/j.cgh.2016.05.013. Epub 2016 May 20.
- Liao Z, Duan XD, Xin L, Bo LM, Wang XH, Xiao GH, Hu LH, Zhuang SL, Li ZS. Feasibility and safety of magnetic-controlled capsule endoscopy system in examination of human stomach: a pilot study in healthy volunteers. J Interv Gastroenterol. 2012 Oct-Dec;2(4):155-160. doi: 10.4161/jig.23751. Epub 2012 Oct 1.
- Wu L, Zhang J, Zhou W, An P, Shen L, Liu J, Jiang X, Huang X, Mu G, Wan X, Lv X, Gao J, Cui N, Hu S, Chen Y, Hu X, Li J, Chen D, Gong D, He X, Ding Q, Zhu X, Li S, Wei X, Li X, Wang X, Zhou J, Zhang M, Yu HG. Randomised controlled trial of WISENSE, a real-time quality improving system for monitoring blind spots during esophagogastroduodenoscopy. Gut. 2019 Dec;68(12):2161-2169. doi: 10.1136/gutjnl-2018-317366. Epub 2019 Mar 11.
- Ding Z, Shi H, Zhang H, Meng L, Fan M, Han C, Zhang K, Ming F, Xie X, Liu H, Liu J, Lin R, Hou X. Gastroenterologist-Level Identification of Small-Bowel Diseases and Normal Variants by Capsule Endoscopy Using a Deep-Learning Model. Gastroenterology. 2019 Oct;157(4):1044-1054.e5. doi: 10.1053/j.gastro.2019.06.025. Epub 2019 Jun 25.
Study record dates
Study Major Dates
Study Start (Anticipated)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
- 20190411A
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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 Capsule Endoscopy
-
Changhai HospitalQilu Hospital of Shandong UniversityCompleted
-
Zhuan LiaoUnknown
-
Changhai HospitalCompleted
-
Shandong UniversityRecruiting
-
Shandong UniversityRecruiting
-
Children's Hospital of Fudan UniversityCompletedCapsule EndoscopyChina
-
Changhai HospitalCompleted
-
University of British ColumbiaCompleted
-
Nanfang Hospital of Southern Medical UniversityUnknown
Clinical Trials on Real-time artificial intelligence identification system
-
Xiangya Hospital of Central South UniversityRecruitingA Multi-centric Clinical Trial in China for Skin Diseases Intelligent Diagnosis and Treatment SystemSkin Diseases | Artificial Intelligence | Augmented Reality | Medical ImagingChina
-
The University of Hong KongCompletedColonic Polyp | Colon Cancer | Colon AdenomaHong Kong
-
The Third Xiangya Hospital of Central South UniversityRecruitingClinical Research on a Novel Deep-learning Based System in Pancreatic Endoscopic Ultrasound ScanningPancreatic DiseaseChina
-
Renmin Hospital of Wuhan UniversityCompletedTraining | Artificial Intelligence | GastroscopyChina
-
Hospital General de México Dr. Eduardo LiceagaUnknownHPV DNA | Human Papillomavirus (HPV)-Related Cervical CancerMexico
-
Renmin Hospital of Wuhan UniversityNot yet recruitingArtificial Intelligence | ColonoscopyChina
-
Renmin Hospital of Wuhan UniversityRecruitingArtificial Intelligence | EndoscopyChina
-
Renmin Hospital of Wuhan UniversityNot yet recruiting
-
Renmin Hospital of Wuhan UniversityRecruitingArtificial Intelligence | Colonoscopy | Gastrointestinal DiseaseChina
-
Renmin Hospital of Wuhan UniversityCompletedArtificial Intelligence | Colonoscopy | Gastrointestinal Disease | Deep LearningChina