UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000054533 |
|---|---|
| Receipt number | R000062263 |
| Scientific Title | Verification and Effect of Gastric Cancer Diagnosis by Endoscopic AI Diagnosis |
| Date of disclosure of the study information | 2024/06/01 |
| Last modified on | 2025/12/31 11:02:06 |
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Basic information
Public title
Early detection of gastric cancer by AI diagnosis of endoscope
Acronym
AI diagnosis of early gastric cancer
Scientific Title
Verification and Effect of Gastric Cancer Diagnosis by Endoscopic AI Diagnosis
Scientific Title:Acronym
AI diagnosis of early gastric cancer
Region
| Japan |
Condition
Condition
Early gastric cancer
Classification by specialty
| Gastroenterology |
Classification by malignancy
Malignancy
Genomic information
NO
Objectives
Narrative objectives1
AI diagnosis in endoscopic diagnosis is progressing day by day, but current AI diagnosis mainly focuses on picking up lesions. This time, we introduce gastro AI model-G provided by AI Medical Services (AIM), and examine whether it is possible to improve the detection rate of gastric cancer by using AI of the company as an auxiliary for qualitative diagnosis such as biopsy necessity.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Gastric Cancer Discovery Rate
Key secondary outcomes
Differences in Gastric Cancer Detection Rates Between Endoscopists and Nonspecialists
Difference in detection rate depending on the nature of the lesion
Base
Study type
Interventional
Study design
Basic design
Parallel
Randomization
Randomized
Randomization unit
Individual
Blinding
Single blind -participants are blinded
Control
Active
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
2
Purpose of intervention
Diagnosis
Type of intervention
| Device,equipment |
Interventions/Control_1
Upper endoscopy is performed, and in the endoscopy group with AI, biopsy is performed when the examiner or AI, or both recognize the lesion to evaluate the lesion. The duration of the intervention is during one endoscopy, and auxiliary diagnosis with AI can be used repeatedly as necessary during the examination.
Interventions/Control_2
In the endoscopy group without AI, biopsy is performed only when the examiner determines that it is necessary to evaluate the lesion.
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
| Not applicable |
Age-upper limit
| Not applicable |
Gender
Male and Female
Key inclusion criteria
All patients who have not been diagnosed with stomach cancer
Key exclusion criteria
Patients who have already been diagnosed with stomach cancer.
Target sample size
1000
Research contact person
Name of lead principal investigator
| 1st name | Kouji |
| Middle name | |
| Last name | Ikegami |
Organization
Matsuyama Red Cross Hospital
Division name
Gastroenterology
Zip code
7908524
Address
1 Bunkyo-cho, Matsuyama City, Ehime Prefecture
TEL
089-924-1111
kikegami56@aol.com
Public contact
Name of contact person
| 1st name | Shimpei |
| Middle name | |
| Last name | Shirai |
Organization
Matsuyama Red Cross Hospital
Division name
Gastroenterology
Zip code
7908524
Address
1 Bunkyo-cho, Matsuyama City, Ehime Prefecture
TEL
089-924-1111
Homepage URL
shimpei_shirai85@outlook.com
Sponsor or person
Institute
Matsuyama Red Cross Hospital
Institute
Department
Personal name
Funding Source
Organization
None
Organization
Division
Category of Funding Organization
Other
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Matsuyama Red Cross Hospital
Address
1 Bunkyo-cho, Matsuyama City, Ehime Prefecture
Tel
089-924-1111
shimpei_shirai85@outlook.com
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
| 2024 | Year | 06 | Month | 01 | 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
768
Results
Results date posted
Results Delayed
| Delay expected |
Results Delay Reason
Because we have not yet completed the analysis.
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
No longer recruiting
Date of protocol fixation
| 2024 | Year | 06 | Month | 01 | Day |
Date of IRB
| 2024 | Year | 05 | Month | 22 | Day |
Anticipated trial start date
| 2024 | Year | 06 | Month | 01 | Day |
Last follow-up date
| 2025 | Year | 05 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
Management information
Registered date
| 2024 | Year | 05 | Month | 31 | Day |
Last modified on
| 2025 | Year | 12 | Month | 31 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000062263
