UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000060076 |
|---|---|
| Receipt number | R000068704 |
| Scientific Title | A Study on AI-Based Assessment of Ulcerative Colitis Severity Using Abdominal CT Images |
| Date of disclosure of the study information | 2025/12/13 |
| Last modified on | 2025/12/13 21:19:54 |
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Basic information
Public title
A Study on AI-Based Assessment of Ulcerative Colitis Severity Using Abdominal CT Images
Acronym
AI-Based Assessment of UC Severity Using CT
Scientific Title
A Study on AI-Based Assessment of Ulcerative Colitis Severity Using Abdominal CT Images
Scientific Title:Acronym
AI-Based Assessment of UC Severity Using CT
Region
| Japan |
Condition
Condition
Ulcerative colitis patients
Classification by specialty
| Gastroenterology | Radiology |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
To develop an artificial intelligence (AI) model with diagnostic accuracy comparable to that of expert physicians for assessing the severity of ulcerative colitis using abdominal CT images.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Confirmatory
Trial characteristics_2
Pragmatic
Developmental phase
Not applicable
Assessment
Primary outcomes
Association Between AI-Based Assessment of Intestinal Inflammation Using CT Images and Clinical and Endoscopic Disease Activity
Key secondary outcomes
1. Association Between CT Findings and Clinical Disease Activity (MHLW Criteria and Partial Mayo Score)
2. Association Between CT Findings and Endoscopic Disease Activity (Mayo Endoscopic Subscore [MES])
3. Association Between CT Findings and Laboratory Biomarkers, Including Blood Tests (CRP, LRG), Stool Tests (Fecal Calprotectin [FCP]), and Urine Tests (PEG-MUM)
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
| 100 | years-old | >= |
Gender
Male and Female
Key inclusion criteria
1. Derivation Dataset for AI Model Development:
Patients with ulcerative colitis who underwent abdominal CT examinations at Aizu Medical Center Hospital between May 2013 and August 2025.
2. Test Dataset for AI Model Validation:
Patients with ulcerative colitis who underwent abdominal CT examinations at Jichi Medical University Hospital or Takeda General Hospital between May 2013 and August 2025.
Key exclusion criteria
Patients whose ulcerative colitis disease activity was not evaluated by colonoscopy within +-2 weeks of the CT examination.
Target sample size
200
Research contact person
Name of lead principal investigator
| 1st name | Kazutomo |
| Middle name | |
| Last name | Togashi |
Organization
Fukushima Medical University, Aizu Medical Center
Division name
Department of Gastroenterology
Zip code
969-3492
Address
21-2 Maeda, Tanisawa, Kawahigashi-machi, Aizuwakamatsu-shi, Fukushima, Japan
TEL
0242-75-2100
togashik@fmu.ac.jp
Public contact
Name of contact person
| 1st name | Masato |
| Middle name | |
| Last name | Aizawa |
Organization
Fukushima Medical University, Aizu Medical Center
Division name
Department of Gastroenterology
Zip code
969-3492
Address
21-2 Maeda, Tanisawa, Kawahigashi-machi, Aizuwakamatsu-shi, Fukushima, Japan
TEL
0242-75-2100
Homepage URL
aizawa-m@fmu.ac.jp
Sponsor or person
Institute
Fukushima Medical University
Institute
Department
Personal name
Funding Source
Organization
Fukushima Medical 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
Institutional Review Board of Fukushima Medical University
Address
1 Hikarigaoka, Fukushima-city, Japan
Tel
024-547-1825
fmucrb@fmu.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
会津医療センター（福島県）、自治医科大学（栃木県）、竹田綜合病院（福島県）
Other administrative information
Date of disclosure of the study information
| 2025 | Year | 12 | Month | 13 | 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
Enrolling by invitation
Date of protocol fixation
| 2025 | Year | 08 | Month | 31 | Day |
Date of IRB
| 2025 | Year | 10 | Month | 27 | Day |
Anticipated trial start date
| 2025 | Year | 10 | Month | 27 | Day |
Last follow-up date
| 2026 | Year | 09 | Month | 30 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
We will develop an artificial intelligence system to automatically assess disease activity in ulcerative colitis using CT imaging data from Aizu Medical Center Hospital, and evaluate its diagnostic performance using CT imaging data from Jichi Medical University Hospital and Takeda General Hospital.
Management information
Registered date
| 2025 | Year | 12 | Month | 13 | Day |
Last modified on
| 2025 | Year | 12 | Month | 13 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000068704
