Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy (Fuji AI)

June 27, 2023 updated by: Prof. Dr. Thomas Rösch, Universitätsklinikum Hamburg-Eppendorf

Prospective Randomized Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy

Colonoscopy is currently the best method of detection of intestinal tumors and polyps, particularly because polyps can also be biopsied and removed. There is a clear correlation between the adenoma detection rate and prevented carcinomas, so adenoma detection rate is the main parameter for the outcome quality of diagnostic colonoscopy. The efficiency of preventive colonoscopy needs optimisation by increase in adenoma detection rate, as it is known from many studies that approximately 15-30% of all adenomas can be overlooked. This mainly applies to smaller and flat adenomas. However, since even smaller polyps may be relevant for colorectal cancer development, the aim of colonoscopy should be to preferably be able to recognize all polyps and other changes.The latest and by far the most interesting development in this field is the use of artificial intelligence systems. They consist of a switched-on software with a small computer connected to the endoscope processor; the patient's introduced endoscope is completely unchanged.

The present study therefore compares the adenoma detection rate (ADR) of the latest generation of devices with high-resolution imaging from Fujifilm with and without the connection of artificial intelligence.

Study Overview

Detailed Description

Methods of Computer Vision (CV) and Artificial Intelligence (AI) provide completely new opportunities, e.g. in the automatic polyp detection and differentiation of a lesion based on its endoscopic image. Computer vision using artificial intelligence methods means the application of "trained" so-called deep neural net (DNN) with a set of defined images (e.g. everyday scenes) and well-known solutions ( e.g. name of the pictured item; c.f. e.g. the "ImageNet Challenge"). The technical feasibility of using AI algorithms in endoscopy has already been proven in many cases. In the present study, it is an AI system from Fujifilm, which is already clinically usable. By using Fujifilm high-resolution imaging devices in colonoscopies, AI will be added randomly.

Study Type

Interventional

Enrollment (Estimated)

1572

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Thomas Rösch, Prof. Dr.
  • Phone Number: 50098 +49 40 7410
  • Email: t.roesch@uke.de

Study Contact Backup

Study Locations

      • Bad Salzuflen, Germany, 32105
        • Terminated
        • GastroZentrum Lippe
      • Berlin, Germany, 10825
        • Recruiting
        • Gastroenterologie am Bayerischen Platz
        • Contact:
        • Contact:
        • Sub-Investigator:
          • Stefan Schubert, Dr.
        • Sub-Investigator:
          • Peter Amerding, Dr.
        • Sub-Investigator:
          • Thomas Liceni, Dr.
      • Bonn, Germany, 53127
        • Recruiting
        • University Hospital Bonn
        • Contact:
        • Principal Investigator:
          • Dominik J Kaczmarek, PD Dr.
      • Hamburg, Germany, 20246
        • Recruiting
        • University Hospital Eppendorf
        • Contact:
          • Thomas Rösch, Prof. Dr
          • Phone Number: 50098 +49 40 7410
          • Email: t.roesch@uke.de
        • Contact:
        • Sub-Investigator:
          • Guido Schachschal, Dr.
        • Sub-Investigator:
          • Katharina Zimmermann-Fraedrich, Dr.
        • Principal Investigator:
          • Thomas Rösch, Prof. Dr.
      • Köln, Germany, 50733
        • Recruiting
        • St. Vinzenz-Hospital / Akademisches Lehrkrankenhaus der Universität zu Köln
        • Contact:
        • Principal Investigator:
          • Philipp Zervoulakos, Dr.
      • Magdeburg, Germany, 39120
        • Recruiting
        • University Hospital Magdeburg
        • Contact:
        • Principal Investigator:
          • Jochen Weigt, PD Dr.
      • Osnabrück, Germany, 49074
      • Wiesbaden, Germany, 65197
        • Recruiting
        • Asklepios Paulinen Klinik Wiesbaden
        • Contact:
        • Principal Investigator:
          • Andrea May, Prof. Dr.
    • Hessen
      • Kassel, Hessen, Germany, 34127
        • Terminated
        • Gastroenterologiepraxis Dr. Moog
    • Sachsen

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

35 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Persons> 35 years of age who are capable of giving informed consent
  • Planned diagnostic colonoscopy (clarification of symptoms, polyp follow-up)
  • Screening colonoscopy for men >50 or women > 55 years of age

Exclusion Criteria:

  • Colon bleeding
  • Colon carcinoma
  • Known polyps for removal
  • Inflammatory bowel disease
  • Colonic stenosis
  • Other suspected colon disease for further clarification
  • Follow-up care after colon cancer surgery (partial colon resection)
  • Anticoagulant drugs that make a biopsy or polypectomy impossible
  • Poor general condition (ASA IV)
  • Incomplete colonoscopy planned

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: AI colonoscopy
colonoscopy with artificial intelligence added
addition of polyp detection algorithm by Fujifilm
Sham Comparator: conventional colonoscopy
addition of polyp detection algorithm by Fujifilm

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Adenoma detection rate
Time Frame: during procedure to histological examination result, approximately 2 days
Difference in adenoma detection rate (all adenomas/all patients) between the two groups
during procedure to histological examination result, approximately 2 days

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Patient rate difference
Time Frame: during procedure to histological examination result, approximately 2 days
Differences in the patient rate with adenomas (adenoma detection rate, i.e. rate of patients with at least one adenoma)
during procedure to histological examination result, approximately 2 days
Adenoma subgroup differences
Time Frame: histological examination result, approximately 2 days
Differences subgroups of adenomas (flat, small, high-grade dysplasia)
histological examination result, approximately 2 days
rate of hyperplastic polyp detection in both groups
Time Frame: histological examination result, approximately 2 days
Differences in the detection of hyperplastic polyps
histological examination result, approximately 2 days
rate of polyp detection in preventive and diagnostic colonoscopy
Time Frame: during procedure to histological examination result, approximately 2 days
Differences in preventive vs. diagnostic colonoscopy
during procedure to histological examination result, approximately 2 days
Switching number (BLI, LCI) in both groups
Time Frame: during procedure
number of switches to visual support by colour filters
during procedure
incidence of reasons for switching to BLI/LCI
Time Frame: during procedure
reasons for switching to visual support by colour filters
during procedure
quality of polyp detection rate by image evaluation
Time Frame: until 2 months after recruitment stop
differential diagnosis of colon polyps in both groups with/without CADEYE)
until 2 months after recruitment stop

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Thomas Rösch, Prof. Dr., Universitätsklinikum Hamburg-Eppendorf

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 28, 2020

Primary Completion (Estimated)

May 1, 2024

Study Completion (Estimated)

September 1, 2024

Study Registration Dates

First Submitted

December 1, 2020

First Submitted That Met QC Criteria

May 18, 2021

First Posted (Actual)

May 20, 2021

Study Record Updates

Last Update Posted (Actual)

June 28, 2023

Last Update Submitted That Met QC Criteria

June 27, 2023

Last Verified

June 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • PV7284

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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