UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000059336 |
|---|---|
| Receipt number | R000067866 |
| Scientific Title | Development of an AI-based Diagnostic System for Oral Diseases Using a Gastrointestinal Endoscopy System and Its Application to the Stratification of Gastrointestinal Cancer Risk |
| Date of disclosure of the study information | 2025/10/09 |
| Last modified on | 2025/11/12 10:59:21 |
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Basic information
Public title
Development of an AI-based Diagnostic System for Oral Diseases Using a Gastrointestinal Endoscopy System and Its Application to the Stratification of Gastrointestinal Cancer Risk
Acronym
Diagnosis of Oral Diseases Using a Gastrointestinal Endoscopy System
Scientific Title
Development of an AI-based Diagnostic System for Oral Diseases Using a Gastrointestinal Endoscopy System and Its Application to the Stratification of Gastrointestinal Cancer Risk
Scientific Title:Acronym
Diagnosis of Oral Diseases Using a Gastrointestinal Endoscopy System
Region
| Japan |
Condition
Condition
Dental caries, periodontal disease, esophageal cancer, and gastric cancer
Classification by specialty
| Gastroenterology | Dental medicine |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
In this study, we aim to evaluate oral diseases such as periodontal disease and dental caries using a gastrointestinal endoscopy system, and to investigate the usefulness of this approach as a means of early identification of patients who require dental intervention. Furthermore, we aim to develop an AI-based system for the automatic assessment of oral health status. As a further objective, since oral health conditions are known risk factors for head and neck, esophageal, and gastric cancers, we will also examine whether the oral findings obtained from gastrointestinal endoscopy can be utilized for risk stratification of these gastrointestinal cancers.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Exploratory
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Diagnostic concordance between oral assessments based on intraoral images (white-light, NBI, and TXI modes) captured by a gastrointestinal endoscopy system and those obtained through direct clinical examinations by dentists
Key secondary outcomes
1. Diagnostic performance of AI-based oral disease detection using endoscopic images
2. Association between oral findings and gastrointestinal or head and neck cancers
Base
Study type
Observational
Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| 18 | years-old | <= |
Age-upper limit
| Not applicable |
Gender
Male and Female
Key inclusion criteria
1. Patients scheduled to undergo upper gastrointestinal endoscopy at our hospital
2. Patients currently receiving treatment at the Department of Periodontology in our hospital
3. Volunteers who wish to participate in this study
4. Patients aged 18 years or older, regardless of sex
Key exclusion criteria
1. Individuals who express a desire not to participate in the study
2. Individuals deemed inappropriate for inclusion in the study at the discretion of the physician
Target sample size
600
Research contact person
Name of lead principal investigator
| 1st name | Kazuya |
| Middle name | |
| Last name | Takahashi |
Organization
Graduate School of Medical and Dental Sciences,Niigata University
Division name
Division of Gastroenterology and Hepatology
Zip code
9518510
Address
1-757, Asahimachidori, Chuo-ku, Niigata, Japan
TEL
0252272207
kazuya911@med.niigata-u.ac.jp
Public contact
Name of contact person
| 1st name | Kazuya |
| Middle name | |
| Last name | Takahashi |
Organization
Graduate School of Medical and Dental Sciences, Niigata University
Division name
Division of Gastroenterology and Hepatology
Zip code
9518510
Address
1-757, Asahimachidori, Chuo-ku, Niigata, Japan
TEL
0252272207
Homepage URL
kazuya911@med.niigata-u.ac.jp
Sponsor or person
Institute
Niigata University
Institute
Department
Personal name
Funding Source
Organization
Niigata University
Organization
Division
Category of Funding Organization
Self funding
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Niigata University Ethics Committee
Address
1-757, Asahimachidori, Chuo-ku, Niigata, Japan
Tel
0252272625
ethics@adm.niigata-u.ac.jp
Secondary IDs
Secondary IDs
NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
Other administrative information
Date of disclosure of the study information
| 2025 | Year | 10 | Month | 09 | Day |
Related information
URL releasing protocol
Publication of results
Unpublished
Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Open public recruiting
Date of protocol fixation
| 2025 | Year | 09 | Month | 18 | Day |
Date of IRB
| 2025 | Year | 10 | Month | 01 | Day |
Anticipated trial start date
| 2025 | Year | 10 | Month | 10 | Day |
Last follow-up date
| 2030 | Year | 12 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
An AI-based model for the automatic assessment of oral health status will be developed using intraoral endoscopic images. Although a strict statistical calculation of sample size is not required for AI model development, we aim to construct a highly accurate model by enrolling approximately 500 participants, recruiting as many eligible subjects as possible during the study period. After model construction, an additional 100 participants will be prospectively recruited to perform validation of the AI model using a prospective cohort.
Many patients attending our department undergo annual follow-up esophagogastroduodenoscopy (EGD) for various reasons. For participants registered in this study via the Department of Gastroenterology, routine EGD follow-up will be continued as part of their standard medical care, and the occurrence of gastrointestinal diseases will be prospectively monitored. The relationship between the baseline intraoral findings at registration and the subsequent occurrence of gastrointestinal diseases will be analyzed.
Management information
Registered date
| 2025 | Year | 10 | Month | 08 | Day |
Last modified on
| 2025 | Year | 11 | Month | 12 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000067866
