Computer Aided Detection of Polyps During Colonoscopy Procedures
1 other identifier
interventional
300
1 country
2
Brief Summary
The focus of the study is to evaluate impact on Adenomas Per Colonoscopy (APC) with a Computer Aided Detection (CAD) software assisting the gastroenterologist during a colonoscopy procedure.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for not_applicable colorectal-cancer
Started Oct 2019
Shorter than P25 for not_applicable colorectal-cancer
2 active sites
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
Study Start
First participant enrolled
October 1, 2019
CompletedFirst Submitted
Initial submission to the registry
December 10, 2019
CompletedFirst Posted
Study publicly available on registry
December 12, 2019
CompletedPrimary Completion
Last participant's last visit for primary outcome
February 15, 2020
CompletedStudy Completion
Last participant's last visit for all outcomes
February 28, 2020
CompletedSeptember 2, 2021
September 1, 2021
5 months
December 10, 2019
September 1, 2021
Conditions
Outcome Measures
Primary Outcomes (1)
Adenomas Per Colonoscopy
Averaged Adenomas Per Colonoscopy (APC), to determine if the use of CAD software identifies more adenomas per colonoscopy. This will be generated for the entire study as well as each investigator. This prospectively collected data will be compared against APC for same number of past procedures performed without use of EndoVigilant CAD system, both at aggregate and physician level.
1 hour
Study Arms (1)
EndoVigilant CAD Software assisted Colonoscopy Procedure
EXPERIMENTALThe gastroenterologist performing the colonoscopy procedure will be able to observe a standard colonoscopy video on the primary monitor and video augmented by EndoVigilant CAD software on the second monitor. The gastroenterologist will primarily rely on the second monitor but the standard procedure monitor will be always operational and available for maneuvers such as fast insertion, polypectomy etc.
Interventions
The CAD software is deep learning algorithm used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. In its current form, the CAD software is installed on a computer system unit that utilizes an an operating system.
Eligibility Criteria
You may qualify if:
- Patient presenting for routine colonoscopy for screening and/or surveillance purposes
- Ability to provide written, informed consent and understand the responsibilities of study participation
You may not qualify if:
- Patients with diminished cognitive capacity
- Patients with inflammatory bowel disease, ulcerative colitis or Crohn's colitis
- Patients with incomplete colonoscopies (due to technical difficulties or poor bowel prep)
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- EndoVigilant Inclead
Study Sites (2)
VA Palo Alto Healthcare
Palo Alto, California, 94304, United States
Greenbelt Endoscopy Center
Greenbelt, Maryland, 20706, United States
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- DEVICE FEASIBILITY
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
December 10, 2019
First Posted
December 12, 2019
Study Start
October 1, 2019
Primary Completion
February 15, 2020
Study Completion
February 28, 2020
Last Updated
September 2, 2021
Record last verified: 2021-09
Data Sharing
- IPD Sharing
- Will not share