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

Last updated: June 27, 2023
Sponsor: Universitätsklinikum Hamburg-Eppendorf
Overall Status: Active - Recruiting

Phase

N/A

Condition

Polyps

Treatment

colonoscopy

Clinical Study ID

NCT04894708
PV7284
  • Ages > 35
  • All Genders
  • Accepts Healthy Volunteers

Study Summary

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.

Eligibility Criteria

Inclusion

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

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 Design

Total Participants: 1572
Treatment Group(s): 1
Primary Treatment: colonoscopy
Phase:
Study Start date:
October 28, 2020
Estimated Completion Date:
September 30, 2024

Study 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.

Connect with a study center

  • Gastroenterologiepraxis Dr. Moog

    Kassel, Hessen 34127
    Germany

    Terminated

  • Universitätsklinikum Leipzig

    Leipzig, Sachsen 04103
    Germany

    Active - Recruiting

  • Universitätsklinikum Magdeburg

    Magdeburg, Sachsen-Anhalt 39120
    Germany

    Site Not Available

  • GastroZentrum Lippe

    Bad Salzuflen, 32105
    Germany

    Terminated

  • Gastroenterologie am Bayerischen Platz

    Berlin, 10825
    Germany

    Active - Recruiting

  • Dominik Kaczmarek

    Bonn, 53127
    Germany

    Active - Recruiting

  • University Hospital Bonn

    Bonn, 53127
    Germany

    Active - Recruiting

  • University Hospital Eppendorf

    Hamburg, 20246
    Germany

    Active - Recruiting

  • St. Vinzenz-Hospital / Akademisches Lehrkrankenhaus der Universität zu Köln

    Köln, 50733
    Germany

    Active - Recruiting

  • University Hospital Magdeburg

    Magdeburg, 39120
    Germany

    Active - Recruiting

  • Marienhospital Osnabrück

    Osnabrück, 49074
    Germany

    Active - Recruiting

  • Asklepios Paulinen Klinik Wiesbaden

    Wiesbaden, 65197
    Germany

    Active - Recruiting

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