UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000059076 |
|---|---|
| Receipt number | R000067571 |
| Scientific Title | Validation of an Artificial Intelligence-Based Imaging Algorithm for Early Pancreatic Cancer: A Multicenter Retrospective Study |
| Date of disclosure of the study information | 2025/09/15 |
| Last modified on | 2025/09/12 17:02:41 |
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Basic information
Public title
Validation of AI Imaging for Early Pancreatic Cancer: A Multicenter Study
Acronym
Validation of AI Imaging for Early Pancreatic Cancer
Scientific Title
Validation of an Artificial Intelligence-Based Imaging Algorithm for Early Pancreatic Cancer: A Multicenter Retrospective Study
Scientific Title:Acronym
Validation of an Artificial Intelligence-Based Imaging Algorithm for Early Pancreatic Cancer
Region
| Japan |
Condition
Condition
Pancreatic cancer
Classification by specialty
| Hepato-biliary-pancreatic medicine | Adult |
Classification by malignancy
Malignancy
Genomic information
NO
Objectives
Narrative objectives1
The objective of this study is to validate the diagnostic performance of an artificial intelligence (AI)-based imaging algorithm for the early detection of pancreatic cancer. Using contrast-enhanced and non-contrast CT images from patients with pancreatic cancer and from normal controls, the established AI algorithm will be applied to assess its accuracy, sensitivity, and specificity. This study aims to clarify whether the AI system can serve as a reliable screening tool for detecting pancreatic cancer at an early stage, which may ultimately contribute to improved patient prognosis.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Concordance between the presence or absence of pancreatic cancer as determined by the AI-based imaging algorithm and the definitive diagnosis based on the pathological findings.
Key secondary outcomes
Presence or absence of pancreatic cancer as determined by expert radiologists (pancreatic cancer present/pancreatic cancer absent)
Detection of direct findings (tumor mass) by the AI-based imaging algorithm
Detection of direct findings (tumor mass) by expert radiologists
Detection of indirect findings (e.g., main pancreatic duct dilatation, localized pancreatic atrophy) by the AI-based imaging algorithm
Detection of indirect findings (e.g., main pancreatic duct dilatation, localized pancreatic atrophy) by expert radiologists
Presence or absence of pancreatic cancer in past imaging as determined by the AI-based imaging algorithm
Presence or absence of pancreatic cancer in past imaging as determined by the reference standard (consensus of two expert radiologists)
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
Pancreatic cancer group: Patients diagnosed with pancreatic cancer with a primary tumor diameter of <=20 mm between January 1, 2014 and December 31, 2024.
Pancreatic cancer is defined as either of the following:
Histological diagnosis of adenocarcinoma of the pancreas.
Histological diagnosis of pancreatic intraepithelial neoplasia grade 3 (PanIN-3)/high-grade PanIN.
Subgroup: Tis/<=10 mm pancreatic cancer group
Among the pancreatic cancer group, patients who meet all of the following:
Diagnosed with pancreatic carcinoma in situ/PanIN-3/high-grade PanIN.
Tumor size diagnosed as <=10 mm.
Normal control group: Patients who underwent contrast-enhanced or non-contrast abdominal CT between January 1, 2014 and December 31, 2024 for the diagnosis of diseases other than pancreatic cancer, and who had no pancrea
Key exclusion criteria
Patients who requested not to participate in this study based on publicly available information
Patients without pancreatic CT imaging data or with poor image quality that precludes evaluation
Patients younger than 18 years (for cases prior to March 31, 2022, patients younger than 20 years)
Target sample size
400
Research contact person
Name of lead principal investigator
| 1st name | Atsuhiro |
| Middle name | |
| Last name | Masuda |
Organization
Kobe University Graduate School of Medicine
Division name
Division of Gastroenterology, Department of Internal Medicine
Zip code
650-0017
Address
7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, Japan
TEL
+81-78-382-6305
atmasuda@med.kobe-u.ac.jp
Public contact
Name of contact person
| 1st name | Atsuhiro |
| Middle name | |
| Last name | Masuda |
Organization
Kobe University Graduate School of Medicine
Division name
Division of Gastroenterology, Department of Internal Medicine
Zip code
650-0017
Address
7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, Japan
TEL
+81-78-382-6305
Homepage URL
gastro@med.kobe-u.ac.jp
Sponsor or person
Institute
Kobe University
Institute
Department
Personal name
Funding Source
Organization
Fujifilm Corporation
Organization
Division
Category of Funding Organization
Profit organization
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
the Ethics Committee of Kobe University Hospital
Address
7-5-1 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, Japan
Tel
078-382-6669
kansatsu@med.kobe-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 | 09 | Month | 15 | 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 | 07 | Month | 30 | Day |
Date of IRB
| 2025 | Year | 07 | Month | 30 | Day |
Anticipated trial start date
| 2025 | Year | 09 | Month | 01 | Day |
Last follow-up date
| 2027 | Year | 03 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
None
Management information
Registered date
| 2025 | Year | 09 | Month | 12 | Day |
Last modified on
| 2025 | Year | 09 | Month | 12 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000067571
