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| ID | Type | Description | Link |
|---|---|---|---|
| 12034 | Other Grant/Funding Number | Dutch Cancer Society |
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| Name | Class |
|---|---|
| Dutch Cancer Society | OTHER |
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With CT-perfusion(CTP) it is possible to visualize the enhancement pattern of the tumor. The perfusion CT, interleaved with a routine contrast enhanced CT (CECT) will be performed at diagnosis in all patients (goal: n=125 patients) and at the first follow-up at 3 months in patients treated with systemic therapy (goal: n=50 patients). Also, the histopathology will be collected for resected tumors to perform histopathology analysis. CTP parameters will be correlated to immunohistological findings and clinical outcome.
The main goal of the study is to create an AI-assisted method to classify patients with a vascular phenotype of pancreatic ductal adenocarcinoma (PDAC). The investigators expect that this phenotype can be used to predict overall survival and chemotherapy response.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| CT Perfusion | Experimental | All patients will receive a baseline CT Perfusion scan. A subgroup of patients with chemotherapy treatment will receive a follow-up CT Perfusion after 3 months. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| CT Perfusion | Diagnostic Test | CT Perfusion |
|
| Measure | Description | Time Frame |
|---|---|---|
| Classification of vascular phenotype using CT-perfusion | To classify a vascular phenotype with CTP using automated perfusion analysis in patients with pancreatic ductal adenocarcinoma | Baseline |
| Correlation of CT-perfusion features with histopathological features | To correlate the vascular phenotype with histopathologic features (stroma and microvessel density) in patients with pancreatic ductal adenocarcinoma | Baseline, Time of Resection |
| Measure | Description | Time Frame |
|---|---|---|
| Association between survival and CT-perfusion features | Automated AI analysis of survival using CT perfusion in patients with pancreatic ductal adenocarcinoma. | Baseline, at 2 Years |
| Prediction of chemotherapy response |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Tom Perik, Msc. | Contact | 024 3617899 | tom.perik@radboudumc.nl |
| Name | Affiliation | Role |
|---|---|---|
| John Hermans, MSc, MD, PhD | Radboud University Medical Center | Principal Investigator |
| Henkjan Huisman, MSc, PhD | Radboud University Medical Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Radboud University Medical Hospital | Recruiting | Nijmegen | Gelderland | 6525GA | Netherlands |
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| ID | Term |
|---|---|
| D010190 | Pancreatic Neoplasms |
| ID | Term |
|---|---|
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004701 | Endocrine Gland Neoplasms |
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Sensitivity and specificity of CT-perfusion parameters to predict chemotherapy response in patients with pancreatic ductal adenocarcinoma.
| Baseline, 3 Months |
| Prediction of chemotherapy response compared to RECIST | Sensitivity and specificity of CT-perfusion parameters to evaluate chemotherapy response in patients with pancreatic ductal adenocarcinoma, compared to RECIST 1.1 on conventional CECT. | Baseline, 3 Months, 6 Months |
| Lodewijk Brosens |
| Radboud University Medical Center |
| Principal Investigator |
| D004066 |
| Digestive System Diseases |
| D010182 | Pancreatic Diseases |
| D004700 | Endocrine System Diseases |