Unique ID issued by UMIN | UMIN000046457 |
---|---|
Receipt number | R000052802 |
Scientific Title | Multi-institutional study on the efficacy of computer-aided diagnosis of pancreatic EUS |
Date of disclosure of the study information | 2022/12/23 |
Last modified on | 2021/12/23 22:56:56 |
Multi-institutional prospective study on the efficacy of computer-aided diagnosis (CAD) for ultrasound endoscopic imaging of pancreatic diseases
MeCAD
Multi-institutional study on the efficacy of computer-aided diagnosis of pancreatic EUS
MeCAD
Japan |
Pancreatic disorders
Hepato-biliary-pancreatic medicine |
Malignancy
NO
Constructing a computer-aided diagnosis model of EUS images of the pancreas using deep learning, one of the methods of AI.
Efficacy
Not applicable
Diagnostic performance of the EUS-CAD model [Receiver Operating Characteristic (ROC) curve, Area under the curve (AUC), sensitivity, specificity, positive predictive value, positive predictive value, negative predictive value)
(1) Comparison of diagnostic performance in each disease category
(2) Univariate and multivariate analysis of factors related to the diagnosis of EUS-CAD model
Observational
20 | years-old | <= |
90 | years-old | > |
Male and Female
Patients who underwent or had undergone EUS as deemed necessary for the treatment of gastrointestinal diseases at the research submitting institution during the study period.
(1) Patients whose imaging data are deemed to be inappropriate for analysis
(2) Patients who have requested not to participate in the study
1620
1st name | Ryosuke |
Middle name | |
Last name | Tonozuka |
Tokyo Medical University
Gastroenterology and Hepatology
160-0023
Nishishinjuku 6-7-1, Shinjuku-ku Tokyo Japan
03-3342-6111
tonozuka@tokyo-med.ac.jp
1st name | Ryosuke |
Middle name | |
Last name | Tonozuka |
Tokyo Medical University
Gastroenterology and Hepatology
160-0023
Nishishinjuku 6-7-1, Shinjuku-ku Tokyo Japan
03-3342-6111
tonozuka@tokyo-med.ac.jp
Tokyo Medical University
Tokyo Medical University
Self funding
Tokyo Medical University Institutional Review Board
Nishishinjuku 6-7-1, Shinjuku-ku Tokyo Japan
03-3342-6111
IRB@tokyo-med.ac.jp
NO
2022 | Year | 12 | Month | 23 | Day |
Unpublished
Open public recruiting
2021 | Year | 09 | Month | 14 | Day |
2021 | Year | 11 | Month | 12 | Day |
2021 | Year | 12 | Month | 23 | Day |
2024 | Year | 12 | Month | 31 | Day |
This research is a study on the feasibility of computer-aided diagnosis using artificial intelligence for EUS images of the pancreas. Video and still image data from endoscopic ultrasound (EUS) performed at the research-sharing facilities listed in 1)-6) below as necessary in daily medical care will be obtained from electronic medical records, and the images will be analyzed using computers at Olympus Medical Systems Corporation, the research-sharing facility, under anonymized conditions. The results of the analysis are then sent back to Tokyo Medical University Hospital, the principal research facility, for evaluation and review by the contributing researchers. Informed consent will be obtained in writing from all eligible patients before or after the EUS examination.
1) Department of Gastroenterology, Tokyo Medical University Hospital, 2) Department of Gastroenterology, International Medical Center, Saitama Medical School, 3) Department of Gastroenterology, Kitasato University Hospital, 4) Department of Gastroenterology, Teinaken-Keijinkai Hospital, 5) Department of Gastroenterology, Dokkyo Medical University Hospital, 6) Third Department of Internal Medicine, Faculty of Medicine, University of Toyama
2021 | Year | 12 | Month | 23 | Day |
2021 | Year | 12 | Month | 23 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000052802