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

Status

UNKNOWN

Phases

Study type

Interventional

Source

ClinicalTrials.gov

Registry ID

NCT03787784

Enrollment

200

Registered

2018-12-26

Start date

2018-05-01

Completion date

2019-03-30

Last updated

2018-12-26

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

Conditions

Artificial Intelligence, Colorectal Polyps, Probe-based Confocal Laser Endomicroscopy

Brief summary

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.

Interventions

OTHERAI presentation

Automatic diagnosis information of AI is visible to endoscopist

Study design

Allocation

RANDOMIZED

Intervention model

PARALLEL

Primary purpose

DIAGNOSTIC

Masking

TRIPLE (Subject, Investigator, Outcomes Assessor)

Eligibility

Sex/Gender

ALL

Age

18 Years to 80 Years

Healthy volunteers

Yes

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

Design outcomes

Primary

Measure	Time frame	Description
The accuracy of classifying colorectal Polyps using Probe-based endomicroscopy with deep neural networks	4 months	The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for diagnosing Colorectal Polyps on real-time pCLE examination.

Secondary

Measure	Time frame	Description
Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists	3 month	The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV for diagnosing Colorectal Polyps on real-time pCLE examination) between Artificial Intelligence and endoscopists.

Countries

China

Contacts

Primary ContactYangqing Li, PHD.MD.

liyanqing@sdu.edu.cn053182169385

Outcome results

None listed

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