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Defining a Vascular Phenotype of Pancreatic Ductal Adenocarcinoma With CT Perfusion Using Quantitative Radiomics

Primary Purpose

PDAC - Pancreatic Ductal Adenocarcinoma

Status
Recruiting
Phase
Not Applicable
Locations
Netherlands
Study Type
Interventional
Intervention
CT Perfusion
Sponsored by
Radboud University Medical Center
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for PDAC - Pancreatic Ductal Adenocarcinoma focused on measuring Pancreas, Pancreatic cancer, CT perfusion, Histopathology, Imaging Biomarker

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria: Clinical suspicion of pancreatic cancer 18 years and older written (signed and dated) informed consent Exclusion Criteria: Contra-indications to undergo CT (due to untreatable contrast allergy or renal function impairment) Previous treatment for pancreatic cancer Concomitant malignancies. Subjects with prior malignancies must be disease-free for at least 5 years Insufficient command of the Dutch language to be able to understand the patient information

Sites / Locations

  • Radboud University Medical HospitalRecruiting

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

CT Perfusion

Arm Description

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.

Outcomes

Primary Outcome Measures

Classification of vascular phenotype using CT-perfusion
To classify a vascular phenotype with CTP using automated perfusion analysis in patients with pancreatic ductal adenocarcinoma
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

Secondary Outcome Measures

Association between survival and CT-perfusion features
Automated AI analysis of survival using CT perfusion in patients with pancreatic ductal adenocarcinoma.
Prediction of chemotherapy response
Sensitivity and specificity of CT-perfusion parameters to predict chemotherapy response in patients with pancreatic ductal adenocarcinoma.
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.

Full Information

First Posted
December 20, 2022
Last Updated
May 1, 2023
Sponsor
Radboud University Medical Center
Collaborators
Dutch Cancer Society
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1. Study Identification

Unique Protocol Identification Number
NCT05669287
Brief Title
Defining a Vascular Phenotype of Pancreatic Ductal Adenocarcinoma With CT Perfusion Using Quantitative Radiomics
Official Title
Defining a Vascular Phenotype of Pancreatic Ductal Adenocarcinoma With CT Perfusion Using Quantitative Radiomics
Study Type
Interventional

2. Study Status

Record Verification Date
December 2022
Overall Recruitment Status
Recruiting
Study Start Date
December 22, 2017 (Actual)
Primary Completion Date
December 31, 2022 (Actual)
Study Completion Date
June 1, 2023 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Radboud University Medical Center
Collaborators
Dutch Cancer Society

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes

5. Study Description

Brief Summary
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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
PDAC - Pancreatic Ductal Adenocarcinoma
Keywords
Pancreas, Pancreatic cancer, CT perfusion, Histopathology, Imaging Biomarker

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
125 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
CT Perfusion
Arm Type
Experimental
Arm Description
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.
Intervention Type
Diagnostic Test
Intervention Name(s)
CT Perfusion
Intervention Description
CT Perfusion
Primary Outcome Measure Information:
Title
Classification of vascular phenotype using CT-perfusion
Description
To classify a vascular phenotype with CTP using automated perfusion analysis in patients with pancreatic ductal adenocarcinoma
Time Frame
Baseline
Title
Correlation of CT-perfusion features with histopathological features
Description
To correlate the vascular phenotype with histopathologic features (stroma and microvessel density) in patients with pancreatic ductal adenocarcinoma
Time Frame
Baseline, Time of Resection
Secondary Outcome Measure Information:
Title
Association between survival and CT-perfusion features
Description
Automated AI analysis of survival using CT perfusion in patients with pancreatic ductal adenocarcinoma.
Time Frame
Baseline, at 2 Years
Title
Prediction of chemotherapy response
Description
Sensitivity and specificity of CT-perfusion parameters to predict chemotherapy response in patients with pancreatic ductal adenocarcinoma.
Time Frame
Baseline, 3 Months
Title
Prediction of chemotherapy response compared to RECIST
Description
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.
Time Frame
Baseline, 3 Months, 6 Months

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: Clinical suspicion of pancreatic cancer 18 years and older written (signed and dated) informed consent Exclusion Criteria: Contra-indications to undergo CT (due to untreatable contrast allergy or renal function impairment) Previous treatment for pancreatic cancer Concomitant malignancies. Subjects with prior malignancies must be disease-free for at least 5 years Insufficient command of the Dutch language to be able to understand the patient information
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Tom Perik, Msc.
Phone
024 3617899
Email
tom.perik@radboudumc.nl
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
John Hermans, MSc, MD, PhD
Organizational Affiliation
Radboud University Medical Center
Official's Role
Principal Investigator
First Name & Middle Initial & Last Name & Degree
Henkjan Huisman, MSc, PhD
Organizational Affiliation
Radboud University Medical Center
Official's Role
Principal Investigator
First Name & Middle Initial & Last Name & Degree
Lodewijk Brosens
Organizational Affiliation
Radboud University Medical Center
Official's Role
Principal Investigator
Facility Information:
Facility Name
Radboud University Medical Hospital
City
Nijmegen
State/Province
Gelderland
ZIP/Postal Code
6525GA
Country
Netherlands
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
John Hermans
Email
john.hermans@radboudumc.nl

12. IPD Sharing Statement

Learn more about this trial

Defining a Vascular Phenotype of Pancreatic Ductal Adenocarcinoma With CT Perfusion Using Quantitative Radiomics

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