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A Real-time Quality Control System of Magnetic-controlled Capsule Gastroscopy

A Prospective Randomized Controlled Trial of AI-box , a Real-time Quality Control System of Magnetic-controlled Capsule Gastroscopy.

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT04954677
Enrollment
194
Registered
2021-07-08
Start date
2021-08-27
Completion date
2022-08-04
Last updated
2025-01-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Magnet Controlled Capsule Endoscopy

Keywords

Artificial intelligence, Deep learning

Brief summary

With the rapid development of artificial intelligence technology, more and more deep learning technology has been applied to medicine. Our research is to develop a set of quality control system for magnetic capsule gastroscope using deep learning technology, and conduct a randomized controlled trial to verify its practical efficiency.

Detailed description

The accuracy of magnetic controlled capsule endoscopy(MCCE) in the diagnosis of stomach lesions is highly consistent with the traditional electronic gastroscopy. It has become a new comfortable and safe form for screening and It is also the beneficial complementarity of the traditional electronic gastroscope. To ensure the medical quality of magnetic controlled capsule endoscopy system, Based on Artificial Intelligence Deep Learning Technology ,investigators developed the Magnetic-controlled Capsule Endoscopic Assisted Quality Control System(AI-box).Randomized controlled trials will be conducted on prospective subjects to verify the quality control efficiency.

Interventions

OTHERAI-box

Automatic quality-control system(AI-box)could real-time measure endoscopic inspection completeness, evaluate gastric cleanliness.

Sponsors

Ancon Technologies Ltd
CollaboratorINDUSTRY
Shandong Provincial Hospital
CollaboratorOTHER_GOV
Binzhou Medical University
CollaboratorOTHER
Shandong University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SCREENING
Masking
DOUBLE (Subject, Outcomes Assessor)

Masking description

Both participates and outcomes Assesors will be masked

Eligibility

Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No

Inclusion criteria

* Consecutive patients aged 18-75 years old who underwent MCCG examination in Qilu Hospital of Shandong University, Shandong Provincial Hospital affilated to Shandong First Medican University, and the Binzhou Medical University Hospital.

Exclusion criteria

* People who are allergic to the ingredients prepared in the stomach before examination; * Patients with astrointestinal bleeding or ulcers, or prior gastrointestinal bleeding or ulcers within the last 24 months; * Patients with esophageal and gastric tumor diseases that are undergoing active surgical treatment; * Contraindications to the MCE test, including suspected or known gastrointestinal obstruction, stenosis, fistula, diverticula, etc; presence of gastrointestinal obstruction symptoms such as pain or dysphagia; * Prior gastrointestinal tract or abdominal surgery other than simple procedures which would not change the gastrointestinal tract anatomy, such as polyp removal, cholecystectomy or appendectomy; * Inoperative conditions or refusal to undergo abdominal surgery if required (ie, if the capsule will not pass and cannot be removed by endoscopy); * A cardiac pacemaker is installed in the body, except when the pacemaker is a new MRE-compatible product; * Electronic devices such as cochlear implant, magnetic metal drug infusion pump, nerve stimulator and magnetic metal foreign body are implanted in vivo; * Planned MRI examination before capsule endoscopy discharge; * Pregnant women; * Patients with deglutition disorders or gastric emptizing disorders.

Design outcomes

Primary

MeasureTime frameDescription
Mean inspection completeness4 monthsAfter the inspection,investigators will review the whole process of inspection and record the sites observed as well as unobserved sites,then calculate the inspection completeness(number of observed sites in each patient/10)besides the the blind spot rate(number of unobserved sites in each patient/10 ) per procedure in control group and AI-assisted group.

Secondary

MeasureTime frameDescription
Cleanliness judgement consistency between expert and AI-box4 monthsAfter the inspection,investigators will review the whole process of inspection and make a judgement of cleanliness of different sites of gastric then compared with the cleanliness judgement of AI-box. So at last investigators will calculate the accuracy of the AI result.

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026