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

Sponsor
Universitätsklinikum Hamburg-Eppendorf (Other)
Overall Status
Recruiting
CT.gov ID
NCT04894708
Collaborator
FUJIFILM Deutschland, Branch office of FUJIFILM Europe GmbH (Other)
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Study Details

Study Description

Brief 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.

Condition or Disease Intervention/Treatment Phase
  • Procedure: colonoscopy
N/A

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 Design

Study Type:
Interventional
Anticipated Enrollment :
1572 participants
Allocation:
Randomized
Intervention Model:
Parallel Assignment
Masking:
None (Open Label)
Primary Purpose:
Diagnostic
Official Title:
Prospective Randomized Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy
Actual Study Start Date :
Oct 28, 2020
Anticipated Primary Completion Date :
May 1, 2022
Anticipated Study Completion Date :
Sep 1, 2022

Arms and Interventions

Arm Intervention/Treatment
Other: AI colonoscopy

colonoscopy with artificial intelligence added

Procedure: colonoscopy
addition of polyp detection algorithm by Fujifilm

Sham Comparator: conventional colonoscopy

conventional colonoscopy

Procedure: colonoscopy
addition of polyp detection algorithm by Fujifilm

Outcome Measures

Primary Outcome Measures

  1. Adenoma detection rate [during procedure to histological examination result, approximately 2 days]

    Difference in adenoma detection rate (all adenomas/all patients) between the two groups

Secondary Outcome Measures

  1. Patient rate difference [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)

  2. Adenoma subgroup differences [histological examination result, approximately 2 days]

    Differences subgroups of adenomas (flat, small, high-grade dysplasia)

  3. rate of hyperplastic polyp detection in both groups [histological examination result, approximately 2 days]

    Differences in the detection of hyperplastic polyps

  4. rate of polyp detection in preventive and diagnostic colonoscopy [during procedure to histological examination result, approximately 2 days]

    Differences in preventive vs. diagnostic colonoscopy

  5. Switching number (BLI, LCI) in both groups [during procedure]

    number of switches to visual support by colour filters

  6. incidence of reasons for switching to BLI/LCI [during procedure]

    reasons for switching to visual support by colour filters

  7. quality of polyp detection rate by image evaluation [until 2 months after recruitment stop]

    differential diagnosis of colon polyps in both groups with/without CADEYE)

Eligibility Criteria

Criteria

Ages Eligible for Study:
35 Years and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
Yes
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

Contacts and Locations

Locations

Site City State Country Postal Code
1 Gastroenterologiepraxis Dr. Moog Kassel Hessen Germany 34127
2 Universitätsklinikum Magdeburg Magdeburg Sachsen-Anhalt Germany 39120
3 Universitätsklinikum Leipzig Leipzig Sachsen Germany 04103
4 Gastroenterologie am Bayerischen Platz Berlin Germany 10825
5 Universitätsklinikum Bonn Bonn Germany 53127
6 University Hospital Eppendorf Hamburg Germany 20246
7 St. Vinzenz-Hospital / Akademisches Lehrkrankenhaus der Universität zu Köln Köln Germany 50733
8 Marienhospital Osnabrück Osnabrück Germany 49074
9 Asklepios Paulinen Klinik Wiesbaden Wiesbaden Germany 65197

Sponsors and Collaborators

  • Universitätsklinikum Hamburg-Eppendorf
  • FUJIFILM Deutschland, Branch office of FUJIFILM Europe GmbH

Investigators

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

Study Documents (Full-Text)

None provided.

More Information

Publications

Responsible Party:
Prof. Dr. Thomas Rösch, Director of Department of Interdisciplinary Endoscopy of University Hospital Hamburg Eppendorf, Universitätsklinikum Hamburg-Eppendorf
ClinicalTrials.gov Identifier:
NCT04894708
Other Study ID Numbers:
  • PV7284
First Posted:
May 20, 2021
Last Update Posted:
Jun 1, 2022
Last Verified:
May 1, 2022
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Additional relevant MeSH terms:

Study Results

No Results Posted as of Jun 1, 2022