A Clinical Study To Measure The Effect Of Use Of Artificial Intelligence (AI) Enabled Computer Aided Detection (CADe) Assistance Software In Detecting Colon Polyps During Standard Colonoscopy Procedures

NCT04555135 | Terminated FDA Device

• 1 other identifier: EV-03-0001
• Study Type: interventional
• Target: 769
• Locations: 1 country
• Sites: 4

Brief Summary

EndoVigilant software device augments existing colonoscopy procedure video in real-time by highlighting colon polyps and mucosal abnormalities. It is intended to assist gastroenterologists in detection of adenomas and serrated polyps. The device is an adjunctive tool and is not intended to replace physicians' decision making related to detection, diagnosis or treatment. This study with an adaptive design measures the clinical benefit (increase in detection of adenomatous and serrated polyps) and increased risk (increased extraction of non-adenomas) during standard colonoscopy procedures when EndoVigilant software device is used.

Conditions

Colon Polyp; Colon Neoplasm; Colon Adenoma

Keywords

Colonoscopy; Artificial Intelligence; Computer Aided Detection

Outcome Measures

Primary Outcomes (2)

• Average Number of Adenomas Per Colonoscopy

  Average Number of Adenomas Per Colonoscopy for all study subjects undergoing colonoscopy procedures, separately calculated for each of the study arms.

  Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)

• Average Number of Adenomas Per Extraction

  Percent of extractions that are adenomas per Colonoscopy for all study subjects undergoing colonoscopy procedures, separately calculated for each of the study arms.

  Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)

Secondary Outcomes (11)

• Average Number of Serrated Polyps per Colonoscopy

  Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)

• Average Number of Non-adenomatous, non-serrated polyps per colonoscopy

  Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)

• Adenoma Detection Rate in Screening Colonoscopies

  Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)

• Serrated Polyp Detection Rate in Screening Colonoscopies

  Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)

• Adenoma Detection Rate in All Colonoscopies

  Receipt of pathology results for procedure findings (typically within 2 weeks after the procedure)

Study Arms (2)

Colonoscopy Procedure with EndoVigilant Software

EXPERIMENTAL

Colonoscopy Procedure is performed with EndoVigilant Software assisting the gastroenterologist during colonoscopy procedure.

Device: EndoVigilant Software

Colonoscopy Procedure without EndoVigilant Software

NO INTERVENTION

Colonoscopy Procedure is performed without EndoVigilant Software assisting the gastroenterologist during colonoscopy procedure.

Interventions

EndoVigilant Software DEVICE

While using this device, colonoscopy will continue to be performed in the standard manner as is done without the use of this device. The video signal from the colonoscope will be fed into a computer running the EndoVigilant software in addition to the standard video output to the procedure monitor. The gastroenterologist performing the procedure will therefore be able to observe a standard colonoscopy video on the primary monitor and the augmented video on the second monitor. The gastroenterologist may rely on the second monitor (with augmented video generated from EndoVigilant software) for polyp detection, but the standard procedure monitor with the original feed will always be operational and available for maneuvers such as fast insertion, polypectomy etc.

Colonoscopy Procedure with EndoVigilant Software

Eligibility Criteria

• Age: 45 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patient is 45 years old or older.
• Patient is presenting for colon cancer screening or low-risk surveillance colonoscopy. Low risk surveillance is defined as the patient qualifying for a colonoscopy surveillance interval of 5 years based on US Multi-Society Task Force 2020 Guidelines (i.e., up to 4 tubular adenomas \<1cm, up to 4 sessile serrated polyps \<1cm on most recent colonoscopy).
• Informed consent document for participating in the study signed by patient or patient's guardian.

You may not qualify if:

• Patient has known history of inflammatory bowel disease (ulcerative colitis, Crohn's disease).
• Patient has known or suspected polyposis or hereditary colon cancer syndrome (such as familial adenomatous polyposis, hereditary nonpolyposis colorectal cancer).
• Patient referred for diagnostic colonoscopy to work up symptoms (such as abdominal pain or bleeding), laboratory abnormalities (such as anemia) or imaging findings (such as masses found on imaging).
• Patient has history of colon resection (not including appendectomy).

Sponsors & Collaborators

• EndoVigilant Inc: lead

Study Sites (4)

Pacific Gastroenterology Endoscopy Center

Mission Viejo, California, 92691, United States

Location

Naugatuck Valley Surgical Center

Waterbury, Connecticut, 06708, United States

Location

Greenbelt Endoscopy Center

Greenbelt, Maryland, 20706, United States

Location

Dr. Satya Kastuar Gastroenterology Practice

North Brunswick, New Jersey, 08902, United States

Location

Related Publications (10)

• Zauber AG, Winawer SJ, O'Brien MJ, Lansdorp-Vogelaar I, van Ballegooijen M, Hankey BF, Shi W, Bond JH, Schapiro M, Panish JF, Stewart ET, Waye JD. Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths. N Engl J Med. 2012 Feb 23;366(8):687-96. doi: 10.1056/NEJMoa1100370.

  PMID: 22356322 BACKGROUND

• Klare P, Sander C, Prinzen M, Haller B, Nowack S, Abdelhafez M, Poszler A, Brown H, Wilhelm D, Schmid RM, von Delius S, Wittenberg T. Automated polyp detection in the colorectum: a prospective study (with videos). Gastrointest Endosc. 2019 Mar;89(3):576-582.e1. doi: 10.1016/j.gie.2018.09.042. Epub 2018 Oct 17.

  PMID: 30342029 BACKGROUND

• Singh S, Singh PP, Murad MH, Singh H, Samadder NJ. Prevalence, risk factors, and outcomes of interval colorectal cancers: a systematic review and meta-analysis. Am J Gastroenterol. 2014 Sep;109(9):1375-89. doi: 10.1038/ajg.2014.171. Epub 2014 Jun 24.

  PMID: 24957158 BACKGROUND

• Zhao S, Wang S, Pan P, Xia T, Chang X, Yang X, Guo L, Meng Q, Yang F, Qian W, Xu Z, Wang Y, Wang Z, Gu L, Wang R, Jia F, Yao J, Li Z, Bai Y. Magnitude, Risk Factors, and Factors Associated With Adenoma Miss Rate of Tandem Colonoscopy: A Systematic Review and Meta-analysis. Gastroenterology. 2019 May;156(6):1661-1674.e11. doi: 10.1053/j.gastro.2019.01.260. Epub 2019 Feb 6.

  PMID: 30738046 BACKGROUND

• Fernandez-Esparrach G, Bernal J, Lopez-Ceron M, Cordova H, Sanchez-Montes C, Rodriguez de Miguel C, Sanchez FJ. Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps. Endoscopy. 2016 Sep;48(9):837-42. doi: 10.1055/s-0042-108434. Epub 2016 Jun 10.

  PMID: 27285900 BACKGROUND

• Misawa M, Kudo SE, Mori Y, Cho T, Kataoka S, Yamauchi A, Ogawa Y, Maeda Y, Takeda K, Ichimasa K, Nakamura H, Yagawa Y, Toyoshima N, Ogata N, Kudo T, Hisayuki T, Hayashi T, Wakamura K, Baba T, Ishida F, Itoh H, Roth H, Oda M, Mori K. Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience. Gastroenterology. 2018 Jun;154(8):2027-2029.e3. doi: 10.1053/j.gastro.2018.04.003. Epub 2018 Apr 11. No abstract available.

  PMID: 29653147 BACKGROUND

• 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: 29928897 BACKGROUND

• Wang P, Xiao X, Glissen Brown JR, Berzin TM, Tu M, Xiong F, Hu X, Liu P, Song Y, Zhang D, Yang X, Li L, He J, Yi X, Liu J, Liu X. Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy. Nat Biomed Eng. 2018 Oct;2(10):741-748. doi: 10.1038/s41551-018-0301-3. Epub 2018 Oct 10.

  PMID: 31015647 BACKGROUND

• Wang P, Berzin TM, Glissen Brown JR, Bharadwaj S, Becq A, Xiao X, Liu P, Li L, Song Y, Zhang D, Li Y, Xu G, Tu M, Liu X. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.

  PMID: 30814121 BACKGROUND

• Wei MT, Shankar U, Parvin R, Abbas SH, Chaudhary S, Friedlander Y, Friedland S. Evaluation of Computer-Aided Detection During Colonoscopy in the Community (AI-SEE): A Multicenter Randomized Clinical Trial. Am J Gastroenterol. 2023 Oct 1;118(10):1841-1847. doi: 10.14309/ajg.0000000000002239. Epub 2023 Mar 9.

  PMID: 36892545 DERIVED

MeSH Terms

Conditions

Colonic Polyps; Colonic Neoplasms

Condition Hierarchy (Ancestors)

Intestinal Polyps; Polyps; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms; Colorectal Neoplasms; Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases

Study Officials

• Shai Friedland, MD

  VA Palo Alto Health Care System

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Model Details: Random allocation stratified by gastroenterologist 50% randomized to colonoscopy procedure with device and 50% randomized to colonoscopy procedure without device

Study Record Dates

• First Submitted: September 11, 2020
• First Posted: September 18, 2020
• Study Start: September 28, 2020
• Primary Completion: September 24, 2021
• Study Completion: November 30, 2021
• Last Updated: April 1, 2022

Record last verified: 2022-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (4)