Pancreatic Cancer
Conditions
Keywords
Pancreatic Cancer, Machine Learning, Radiomics, CT, MRI, Ultrasound
Brief summary
This prospective cohort study is designed to investigate the diagnostic ability and prediction accuracy of pancreatic cancer by radiomics data and clinical data.
Detailed description
In this study, investigators aimed to investigate the diagnostic performance and prediction accuracy of pancreatic cancer by radiomics data and clinical data, which include CT scan, MRI, PET-CT, PET-MR, ultrasound, and clinical data.
Interventions
None listed
Sponsors
RenJi Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 90 Years
Inclusion criteria
Clinical diagnosis of pancreatic tumor; Must have CT / MRI / ultrasound data and pathology diagnosis
Exclusion criteria
Have other tumors along with pancreatic tumor; Clinical information missing
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Patient overall survival | up to 3 years | Patient overall survival, from the time of diagnosis of pancreatic tumor to the death of the patient. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Pathology diagnosis | intraoperative | Pathology diagnosis of the patient, such as adenocarcinoma, pancreatic neuroendocrine tumors, intraductal Papillary Mucinous Neoplasm, et al. |
Other
| Measure | Time frame | Description |
|---|---|---|
| Progression-free Survival | up to 3 years | Patient progression-free survival, the length of time during and after the treatment of the tumor, that a patient lives with the disease but it does not get worse. |
Countries
China
Contacts
Primary ContactXinsen Xu, Dr
Backup ContactTao Chen, Dr
Outcome results
None listed