| Unique ID issued by UMIN | UMIN000056597 |
|---|---|
| Receipt number | R000064681 |
| Scientific Title | A Multimodal AI-Based System for Predicting the Grade of Pancreatic Neuroendocrine Tumors |
| Date of disclosure of the study information | 2024/12/28 |
| Last modified on | 2025/06/29 10:22:03 |
A Multimodal AI-Based System for Predicting the Grade of Pancreatic Neuroendocrine Tumors
A Multimodal AI-Based System for Predicting the Grade of Pancreatic Neuroendocrine Tumors
A Multimodal AI-Based System for Predicting the Grade of Pancreatic Neuroendocrine Tumors
A Multimodal AI-Based System for Predicting the Grade of Pancreatic Neuroendocrine Tumors
| Japan |
Pancreatic Neuroendocrine Tumors
| Medicine in general | Hepato-biliary-pancreatic medicine |
Malignancy
NO
This study aims to develop a multimodal AI-based system for predicting the grade of pancreatic neuroendocrine tumors.
Efficacy
Concordance rate between the prediction model and the Grade of resected specimens.
Observational
| Not applicable |
| Not applicable |
Male and Female
Eligible cases for registration must meet all of the following criteria
1. Preoperative contrast-enhanced CT and EUS examinations were performed, followed by definitive surgical resection between January 1996 and December 2024, with a final pathological diagnosis of pancreatic neuroendocrine tumor (including NEC G3 and MiNEN) based on the resected specimen. Surgical techniques are not restricted.
2. Ki-67 imuunostaining was performed on the resected specimen and the Ki-67 labeling index is available.
3. Malignancy grading (NET G1, G2, G3, NEC) based on the WHO 2019 classification is feasible using the resected specimen.
Cases meeting the following criteria will be excluded:
1. Surgical resection of recurrence lesions only (e.g., liver metastases, lymph nodes).
2. Surgical resection of metastatic lesions solely for the purpose of mass reduction or alleviation of hormone-producing symptoms.
3. Cases that are difficult to differentiate from conventional pancreatic cancer in pathological diagnosis.
4. MiNEN.
5. Cases deemed unsuitable for this study by the principal investigator or co-investigators.
400
| 1st name | Susumu |
| Middle name | |
| Last name | Hijioka |
National Cancer Center Hospital
Department of Hepatobiliary and Pancreatic Oncology
1040045
5-1-1 Tsukiji, Chuo-ku, Tokyo, Japan
03-3542-2511
shijioka@ncc.go.jp
| 1st name | Daiki |
| Middle name | |
| Last name | Yamashige |
National Cancer Center Hospital
Department of Hepatobiliary and Pancreatic Oncology
1040045
5-1-1 Tsukiji, Chuo-ku, Tokyo, Japan
03-3542-2511
dyamashi@ncc.go.jp
National Cancer Center Hospital
No funding
Other
National Cancer Center Hospital
5-1-1 Tsukiji, Chuo-ku, Tokyo, Japan
03-3542-2511
irst@ncc.go.jp
NO
| 2024 | Year | 12 | Month | 28 | Day |
Unpublished
Enrolling by invitation
| 2024 | Year | 12 | Month | 28 | Day |
| 2025 | Year | 03 | Month | 25 | Day |
| 2025 | Year | 04 | Month | 01 | Day |
| 2030 | Year | 03 | Month | 31 | Day |
This is a retrospective, multi-center, study.
The following contents will be observed retrospectively.
Patient characteristics (sex, age at the time of surgery)
Presence or absence of hormone-producing symptoms (functional NET)
Presence or absence of hereditary tumors (e.g., MEN1, VHL)
Tumor location, size, and imaging information
Clinical stage
Presence and type of preoperative treatments
Surgical details (date of surgery, surgical procedure)
Detailed pathological diagnosis of pancreatic NET (e.g., progression based on pancreatic cancer guidelines, presence of vascular invasion, lymph node metastasis)
Presence or absence of recurrence
Recurrence patterns
Overall survival (OS)
Recurrence-free survival (RFS)
| 2024 | Year | 12 | Month | 28 | Day |
| 2025 | Year | 06 | Month | 29 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000064681