Real-Time Identification System of Magnetically Controlled Capsule Endoscopy Using Artificial Intelligence
NCT ID: NCT04203264
Last Updated: 2019-12-18
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
50 participants
OBSERVATIONAL
2019-12-16
2020-01-01
Brief Summary
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Detailed Description
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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.
Conditions
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Keywords
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Real-time artificial intelligence identification system
The patients swallowed the MCE with a small amount of water in the left lateral decubitus position. Once the capsule reached the stomach after investigating the esophagus, it was lifted away from the posterior wall, rotated and advanced to the fundus and cardiac regions, and then to the gastric body, angulus, antrum and pylorus. The magnetic steering time for passing through the pylorus was not allowed more than 15 min. The real-time auxiliary system implemented real-time processing for the output image of MCE 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.
Eligibility Criteria
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Inclusion Criteria
* Scheduled to undergo a capsule endoscopy for both stomach and small bowel
* Signed the informed consents before joining this study
Exclusion Criteria
* 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
18 Years
80 Years
ALL
Yes
Sponsors
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Changhai Hospital
OTHER
Responsible Party
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Zhuan Liao
Professor
Principal Investigators
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Zhuan Liao
Role: STUDY_CHAIR
Changhai Hospital
Locations
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Changhai Hospital
Shanghai, , China
Countries
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Central Contacts
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Facility Contacts
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Zhuan Liao
Role: primary
References
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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.
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.
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.
Other Identifiers
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20190411A
Identifier Type: -
Identifier Source: org_study_id