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Automatic Classification of Colorectal Polyps Using Probe-based Endomicroscopy With Artificial Intelligence

NCT ID: NCT03787784

Last Updated: 2018-12-26

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

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

200 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-05-01

Study Completion Date

2019-03-30

Brief Summary

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Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables real-time histological evaluation of gastrointestinal mucosa during ongoing endoscopy examination. It can predict the classification of Colorectal Polyps accurately. However this requires much experience, which limits the application of pCLE. The investigators designed a computer program using deep neural networks to differentiate hyperplastic from neoplastic polyps automatically in pCLE examination.

Detailed Description

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Conditions

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Probe-based Confocal Laser Endomicroscopy Artificial Intelligence Colorectal Polyps

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

TRIPLE

Participants Investigators Outcome Assessors

Study Groups

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AI visible group

Group Type EXPERIMENTAL

AI presentation

Intervention Type OTHER

Automatic diagnosis information of AI is visible to endoscopist

AI invisible group

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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AI presentation

Automatic diagnosis information of AI is visible to endoscopist

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

aged between 18 and 80; agree to give written informed consent.

Exclusion Criteria

Patients under conditions unsuitable for performing CLE including coagulopathy , impaired renal or hepatic function, pregnancy or breastfeeding, and known allergy to fluorescein sodium; Inability to provide informed consent
Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Shandong University

OTHER

Sponsor Role lead

Responsible Party

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Yanqing Li

Vice president of QiLu Hospital

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Endoscopic unit of Qilu Hospital Shandong University

Jinan, Shandong, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Yangqing Li, PHD.MD.

Role: CONTACT

Phone: 053182169385

Email: [email protected]

Facility Contacts

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Yanqing Li, PhD,MD

Role: primary

Other Identifiers

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2018SDU-QILU-8

Identifier Type: -

Identifier Source: org_study_id