RITUAL Ultivision AI CADe Randomized Controlled Trial

NCT ID: NCT05732233

Last Updated: 2024-05-13

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

TERMINATED

Clinical Phase

NA

Total Enrollment

137 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-07-21

Study Completion Date

2024-02-23

Brief Summary

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Ultivision AI is a computer-assisted detection (CADe) device intended to aid endoscopists in the real-time identification of colonic mucosal lesions (such as polyps and adenomas).

Ultivision AI CADe is indicated for white light colonoscopy only.

Detailed Description

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Ultivision AI contains an image processing software and algorithm based on machine learning technology and convolutional neural networks (CNN).

The algorithm's primary function is to identify and highlight the likelihood of the presence of a colon polyp.

Conditions

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Colon Adenoma Polyp of Colon Adenoma Colon

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Parallel trial design
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

SINGLE

Outcome Assessors
Pathologist is blind to group assignment

Study Groups

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Ultivision AI colonoscopy (CADe Arm)

Ultivision AI is used to aid in real-time detection of adenomas.

Group Type EXPERIMENTAL

Ultivision AI

Intervention Type DEVICE

Ultivision AI is a computer-assisted detection (CADe) device intended to aid endoscopists in the real-time identification of colonic mucosal lesions (such as polyps and adenomas) in adult patients undergoing colorectal cancer screening and surveillance examinations.

Standard colonoscopy (Control Arm)

Patients will undergo standard colonoscopy without AI.

Group Type ACTIVE_COMPARATOR

Ultivision AI

Intervention Type DEVICE

Ultivision AI is a computer-assisted detection (CADe) device intended to aid endoscopists in the real-time identification of colonic mucosal lesions (such as polyps and adenomas) in adult patients undergoing colorectal cancer screening and surveillance examinations.

Interventions

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Ultivision AI

Ultivision AI is a computer-assisted detection (CADe) device intended to aid endoscopists in the real-time identification of colonic mucosal lesions (such as polyps and adenomas) in adult patients undergoing colorectal cancer screening and surveillance examinations.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

1. Age 45 to 75 years;
2. Screening or surveillance colonoscopy.
3. Iinformed consent

Exclusion Criteria

1. Colorectal cancer;
2. Inflammatory bowel disease, including Crohn's disease or ulcerative colitis;
3. Polyposis syndrome including Familial Adenomatous Polyposis, Cowden syndome, Linch syndrome, Peutz-Jeghers syndrome, MUITYH associated polyposis, familial Colorectal Cancer type X;
4. Positive Fecal Immunochemical Test;
5. Use anti-platelet agents or anticoagulants that prevent polyps removal;
6. Colon resection, not including the appendix;
7. Subject is pregnant or lactating.
Minimum Eligible Age

45 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Meditrial USA Inc.

INDUSTRY

Sponsor Role collaborator

Satisfai Health, Inc.

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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UC Irvine

Irvine, California, United States

Site Status

University of Kansas Medical Center

Kansas City, Kansas, United States

Site Status

University of Montreal Research Center (CRCHUM)

Montréal (Québec), Montreal, Canada

Site Status

Humanitas Research Hospital

Milan, , Italy

Site Status

Countries

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United States Canada Italy

References

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Urban G, Tripathi P, Alkayali T, Mittal M, Jalali F, Karnes W, Baldi P. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy. Gastroenterology. 2018 Oct;155(4):1069-1078.e8. doi: 10.1053/j.gastro.2018.06.037. Epub 2018 Jun 18.

Reference Type RESULT
PMID: 29928897 (View on PubMed)

Related Links

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https://www.meditrial.net/

Meditrial Clinical Research Organization

Other Identifiers

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STF-2023-01

Identifier Type: -

Identifier Source: org_study_id

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