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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

194 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-08-27

Study Completion Date

2022-08-04

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

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.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

Computer Assisted Quality-monitoring for Magnet-controlled Capsule Endoscopy: a Prospective Case-control Study.

NCT04278196

Magnet Controlled Capsule Endoscopy

COMPLETED

Real-Time Identification System of Magnetically Controlled Capsule Endoscopy Using Artificial Intelligence

NCT04203264

Capsule Endoscopy

UNKNOWN

Prospective Multicenter Study of Artificial Intelligence-assisted Quality Evaluation System for Colonoscopy

NCT04610177

Quality Evaluation System for Colonoscopy

UNKNOWN

Efficacy of Artificial Intelligence-assisted Colonic Polyp Detection System

NCT05941689

Adenoma Colon

COMPLETED NA

Gastrointestinal Endoscopy Artificial Intelligence Cloud Platform in Gastrointestinal Endoscopy Screening

NCT05435872

Diagnoses Disease Quality Control Endoscopy +1 more

UNKNOWN NA

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Magnet Controlled Capsule Endoscopy

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

DOUBLE

Participants Outcome Assessors

Both participates and outcomes Assesors will be masked

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Participates being subjected to capsule endoscopy (AI-box assistant)

In this group ,Participates will be subjected to magnetically controlled capsule gastroscopy with AI-box assistant.

Group Type EXPERIMENTAL

AI-box

Intervention Type OTHER

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

Participates being subjected to capsule endoscopy

In this group ,Participates will be subjected to magnetically controlled capsule gastroscopy without AI-box assistant.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

AI-box

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

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

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.

Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No