NCT05732233

Brief Summary

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.

Trial Health

60
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
137

participants targeted

Target at P50-P75 for not_applicable

Timeline
Completed

Started Jul 2023

Shorter than P25 for not_applicable

Geographic Reach
3 countries

4 active sites

Status
terminated

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

February 7, 2023

Completed
9 days until next milestone

First Posted

Study publicly available on registry

February 16, 2023

Completed
5 months until next milestone

Study Start

First participant enrolled

July 21, 2023

Completed
7 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

February 23, 2024

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

February 23, 2024

Completed
Last Updated

May 13, 2024

Status Verified

February 1, 2023

Enrollment Period

7 months

First QC Date

February 7, 2023

Last Update Submit

May 9, 2024

Conditions

Colon AdenomaPolyp of ColonAdenoma Colon

Keywords

ScreeningSurveillanceArtificial IntelligenceColonoscopy

Outcome Measures

Primary Outcomes (2)

  • Adenoma per Colonoscopy (APC)

    Superiority of Ultivision-AI arm versus control arm. APC is defined as the total number of histologically confirmed adenomas resected divided by the total number of colonoscopies.

    During the procedure/surgery

  • Adenoma Per Extraction (APE).

    Non inferiority of Ultivision-AI arm versus control arm. Where APE is the fraction of adenoma, sessile serrated lesions, and large (\>10mm) hyperplastic polyps of the proximal colon (caecum, ascending colon, hepatic flexure, and transverse colon) out of total number of resections.

    During the procedure/surgery

Study Arms (2)

Ultivision AI colonoscopy (CADe Arm)

EXPERIMENTAL

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

Device: Ultivision AI

Standard colonoscopy (Control Arm)

ACTIVE COMPARATOR

Patients will undergo standard colonoscopy without AI.

Device: Ultivision AI

Interventions

Ultivision AIDEVICE

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)Ultivision AI colonoscopy (CADe Arm)

Eligibility Criteria

Age45 Years - 75 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Age 45 to 75 years;
  • Screening or surveillance colonoscopy.
  • Iinformed consent

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (4)

UC Irvine

Irvine, California, 92697, United States

Location

University of Kansas Medical Center

Kansas City, Kansas, 66160, United States

Location

University of Montreal Research Center (CRCHUM)

Montréal (Québec), Montreal, H2X 0A9, Canada

Location

Humanitas Research Hospital

Milan, Italy

Location

Related Publications (1)

  • 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.

    PMID: 29928897RESULT

Related Links

MeSH Terms

Conditions

Colonic Polyps

Condition Hierarchy (Ancestors)

Intestinal PolypsPolypsPathological Conditions, AnatomicalPathological Conditions, Signs and Symptoms

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
OUTCOMES ASSESSOR
Masking Details
Pathologist is blind to group assignment
Purpose
DIAGNOSTIC
Intervention Model
PARALLEL
Model Details: Parallel trial design
Sponsor Type
INDUSTRY
Responsible Party
SPONSOR

Study Record Dates

First Submitted

February 7, 2023

First Posted

February 16, 2023

Study Start

July 21, 2023

Primary Completion

February 23, 2024

Study Completion

February 23, 2024

Last Updated

May 13, 2024

Record last verified: 2023-02

Data Sharing

IPD Sharing
Will not share

Locations

IT(1)US(2)CA(1)