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

Primary Purpose

Screening Colonoscopy, Colonoscopic Control After Polypectomy, Suspected Colon Polyps

Status
Recruiting
Phase
Not Applicable
Locations
Germany
Study Type
Interventional
Intervention
colonoscopy
Sponsored by
Universitätsklinikum Hamburg-Eppendorf
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Screening Colonoscopy

Eligibility Criteria

35 Years - undefined (Adult, Older Adult)All SexesAccepts Healthy Volunteers

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

Sites / Locations

  • Gastroenterologiepraxis Dr. Moog
  • Universitätsklinikum LeipzigRecruiting
  • GastroZentrum Lippe
  • Gastroenterologie am Bayerischen PlatzRecruiting
  • University Hospital BonnRecruiting
  • University Hospital EppendorfRecruiting
  • St. Vinzenz-Hospital / Akademisches Lehrkrankenhaus der Universität zu KölnRecruiting
  • University Hospital MagdeburgRecruiting
  • Marienhospital OsnabrückRecruiting
  • Asklepios Paulinen Klinik WiesbadenRecruiting

Arms of the Study

Arm 1

Arm 2

Arm Type

Other

Sham Comparator

Arm Label

AI colonoscopy

conventional colonoscopy

Arm Description

colonoscopy with artificial intelligence added

conventional colonoscopy

Outcomes

Primary Outcome Measures

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

Secondary Outcome Measures

Patient rate difference
Differences in the patient rate with adenomas (adenoma detection rate, i.e. rate of patients with at least one adenoma)
Adenoma subgroup differences
Differences subgroups of adenomas (flat, small, high-grade dysplasia)
rate of hyperplastic polyp detection in both groups
Differences in the detection of hyperplastic polyps
rate of polyp detection in preventive and diagnostic colonoscopy
Differences in preventive vs. diagnostic colonoscopy
Switching number (BLI, LCI) in both groups
number of switches to visual support by colour filters
incidence of reasons for switching to BLI/LCI
reasons for switching to visual support by colour filters
quality of polyp detection rate by image evaluation
differential diagnosis of colon polyps in both groups with/without CADEYE)

Full Information

First Posted
December 1, 2020
Last Updated
June 27, 2023
Sponsor
Universitätsklinikum Hamburg-Eppendorf
Collaborators
FUJIFILM Deutschland, Branch office of FUJIFILM Europe GmbH
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1. Study Identification

Unique Protocol Identification Number
NCT04894708
Brief Title
Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy
Acronym
Fuji AI
Official Title
Prospective Randomized Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy
Study Type
Interventional

2. Study Status

Record Verification Date
June 2023
Overall Recruitment Status
Recruiting
Study Start Date
October 28, 2020 (Actual)
Primary Completion Date
May 2024 (Anticipated)
Study Completion Date
September 2024 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Universitätsklinikum Hamburg-Eppendorf
Collaborators
FUJIFILM Deutschland, Branch office of FUJIFILM Europe GmbH

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. 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.
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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Screening Colonoscopy, Colonoscopic Control After Polypectomy, Suspected Colon Polyps

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
None (Open Label)
Allocation
Randomized
Enrollment
1572 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
AI colonoscopy
Arm Type
Other
Arm Description
colonoscopy with artificial intelligence added
Arm Title
conventional colonoscopy
Arm Type
Sham Comparator
Arm Description
conventional colonoscopy
Intervention Type
Procedure
Intervention Name(s)
colonoscopy
Intervention Description
addition of polyp detection algorithm by Fujifilm
Primary Outcome Measure Information:
Title
Adenoma detection rate
Description
Difference in adenoma detection rate (all adenomas/all patients) between the two groups
Time Frame
during procedure to histological examination result, approximately 2 days
Secondary Outcome Measure Information:
Title
Patient rate difference
Description
Differences in the patient rate with adenomas (adenoma detection rate, i.e. rate of patients with at least one adenoma)
Time Frame
during procedure to histological examination result, approximately 2 days
Title
Adenoma subgroup differences
Description
Differences subgroups of adenomas (flat, small, high-grade dysplasia)
Time Frame
histological examination result, approximately 2 days
Title
rate of hyperplastic polyp detection in both groups
Description
Differences in the detection of hyperplastic polyps
Time Frame
histological examination result, approximately 2 days
Title
rate of polyp detection in preventive and diagnostic colonoscopy
Description
Differences in preventive vs. diagnostic colonoscopy
Time Frame
during procedure to histological examination result, approximately 2 days
Title
Switching number (BLI, LCI) in both groups
Description
number of switches to visual support by colour filters
Time Frame
during procedure
Title
incidence of reasons for switching to BLI/LCI
Description
reasons for switching to visual support by colour filters
Time Frame
during procedure
Title
quality of polyp detection rate by image evaluation
Description
differential diagnosis of colon polyps in both groups with/without CADEYE)
Time Frame
until 2 months after recruitment stop

10. Eligibility

Sex
All
Minimum Age & Unit of Time
35 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
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
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Thomas Rösch, Prof. Dr.
Phone
+49 40 7410
Ext
50098
Email
t.roesch@uke.de
First Name & Middle Initial & Last Name or Official Title & Degree
Guido Schachschal, PD Dr.
Phone
+49 40 7410
Ext
50814
Email
g.schachschal@uke.de
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Thomas Rösch, Prof. dr.
Organizational Affiliation
Universitätsklinikum Hamburg-Eppendorf
Official's Role
Principal Investigator
Facility Information:
Facility Name
Gastroenterologiepraxis Dr. Moog
City
Kassel
State/Province
Hessen
ZIP/Postal Code
34127
Country
Germany
Individual Site Status
Terminated
Facility Name
Universitätsklinikum Leipzig
City
Leipzig
State/Province
Sachsen
ZIP/Postal Code
04103
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Albrecht Hoffmeister, Prof. Dr.
Phone
+49 341 97
Ext
12240
Email
albrecht.hoffmeister@medizin.uni-leipzig.de
First Name & Middle Initial & Last Name & Degree
Marcus Hollenbach, Dr.
Email
Marcus.Hollenbach@medizin.uni-leipzig.de
First Name & Middle Initial & Last Name & Degree
Marcus Hollenbach, Dr.
Facility Name
GastroZentrum Lippe
City
Bad Salzuflen
ZIP/Postal Code
32105
Country
Germany
Individual Site Status
Terminated
Facility Name
Gastroenterologie am Bayerischen Platz
City
Berlin
ZIP/Postal Code
10825
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Stefan Schubert, Dr.
Phone
+49 30 814 59
Ext
190
Email
gastroenterologen@berlin.de
First Name & Middle Initial & Last Name & Degree
Peter Amerding, Dr.
Phone
+49 30 814 59
Ext
190
Email
gastroenterologen@berlin.de
First Name & Middle Initial & Last Name & Degree
Stefan Schubert, Dr.
First Name & Middle Initial & Last Name & Degree
Peter Amerding, Dr.
First Name & Middle Initial & Last Name & Degree
Thomas Liceni, Dr.
Facility Name
University Hospital Bonn
City
Bonn
ZIP/Postal Code
53127
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Dominik J Kaczmarek, PD Dr.
Phone
+49 228-287
Ext
14338
Email
Dominik.Kaczmarek@ukbonn.de
First Name & Middle Initial & Last Name & Degree
Dominik J Kaczmarek, PD Dr.
Facility Name
University Hospital Eppendorf
City
Hamburg
ZIP/Postal Code
20246
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Thomas Rösch, Prof. Dr
Phone
+49 40 7410
Ext
50098
Email
t.roesch@uke.de
First Name & Middle Initial & Last Name & Degree
Guido Schachschal, Dr.
Phone
+49 40 7410
Ext
50814
Email
g.schachschal@uke.de
First Name & Middle Initial & Last Name & Degree
Thomas Rösch, Prof. Dr.
First Name & Middle Initial & Last Name & Degree
Guido Schachschal, Dr.
First Name & Middle Initial & Last Name & Degree
Katharina Zimmermann-Fraedrich, Dr.
Facility Name
St. Vinzenz-Hospital / Akademisches Lehrkrankenhaus der Universität zu Köln
City
Köln
ZIP/Postal Code
50733
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Philipp Zervoulakos, Dr.
Phone
+49 221 7712
Ext
4660
Email
philipp.zervoulakos@cellitinnen.de
First Name & Middle Initial & Last Name & Degree
Philipp Zervoulakos, Dr.
Facility Name
University Hospital Magdeburg
City
Magdeburg
ZIP/Postal Code
39120
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Jochen Weigt, PD Dr.
Email
jochen.weigt@med.ovgu.de
First Name & Middle Initial & Last Name & Degree
Jochen Weigt, PD Dr.
Facility Name
Marienhospital Osnabrück
City
Osnabrück
ZIP/Postal Code
49074
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Oliver Möschler, Dr.
Phone
+49 541 326
Ext
4100
Email
Oliver.Moeschler@niels-stensen-kliniken.de
First Name & Middle Initial & Last Name & Degree
Oliver Möschler, Dr.
Facility Name
Asklepios Paulinen Klinik Wiesbaden
City
Wiesbaden
ZIP/Postal Code
65197
Country
Germany
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Andrea May, Prof. Dr.
Phone
+49 611 847
Ext
2331
Email
an.may@asklepios.com
First Name & Middle Initial & Last Name & Degree
Andrea May, Prof. Dr.

12. IPD Sharing Statement

Plan to Share IPD
No
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Study on the Use of Artificial Intelligence (Fujifilm) for Polyp Detection in Colonoscopy

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