PSMA-PET: Deep Radiomic Biomarkers of Progression and Response Prediction in Prostate Cancer
Primary Purpose
Prostate Cancer
Status
Recruiting
Phase
Phase 3
Locations
Canada
Study Type
Interventional
Intervention
18F-DCFPyL IV injection
Sponsored by
About this trial
This is an interventional diagnostic trial for Prostate Cancer
Eligibility Criteria
Inclusion Criteria:
- Patients with prostate cancer, being followed and treated at CHUM, whose treating physician at CHUM has requested a PSMA-PET scan.
Exclusion Criteria:
- Claustrophobia/inability to complete imaging procedure.
Sites / Locations
- Centre Hospitalier de l'université de MontréalRecruiting
Arms of the Study
Arm 1
Arm Type
Experimental
Arm Label
Main arm
Arm Description
PET-CT imaging following 18F-DCFPyL injection, 1 injection, IV, 10 mCi
Outcomes
Primary Outcome Measures
Overall survival
Images from the 18F-DCFPyL PET-CT scans will be combined with patient follow-up data in a deep learning algorithm to discover radiomics features predicting outcomes (overall survival).
Secondary Outcome Measures
Progression free survival
Images from the 18F-DCFPyL PET-CT scans will be combined with patient follow-up data in a deep learning algorithm to discover radiomics features predicting outcomes (progression free survival).
Full Information
NCT ID
NCT03594760
First Posted
July 9, 2018
Last Updated
June 12, 2023
Sponsor
Centre hospitalier de l'Université de Montréal (CHUM)
1. Study Identification
Unique Protocol Identification Number
NCT03594760
Brief Title
PSMA-PET: Deep Radiomic Biomarkers of Progression and Response Prediction in Prostate Cancer
Official Title
PSMA-PET: Deep Radiomic Biomarkers of Progression and Response Prediction in Prostate Cancer
Study Type
Interventional
2. Study Status
Record Verification Date
June 2023
Overall Recruitment Status
Recruiting
Study Start Date
December 1, 2018 (Actual)
Primary Completion Date
December 2023 (Anticipated)
Study Completion Date
December 2024 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Centre hospitalier de l'Université de Montréal (CHUM)
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
5. Study Description
Brief Summary
Prostate cancer (PCa) is the most common non-skin malignancy and the third leading cause of cancer death in North American men. The accurately mapped metastatic state is a necessary prerequisite to guiding treatment in practice and in clinical trials. Imaging biomarkers (BMs) can provide information on disease volume and distribution, prognosis, changes in biologic behavior, therapy-induced changes (both responders and non-responders), durations of response, emergence of treatment resistance, and the host reaction to the therapies.
Of particular relevance to metastatic prostate cancer is the emergence of a promising imaging technique involving new prostate specific membrane antigen (PSMA) positron emission tomography (PET) tracers. This approach has demonstrated higher sensitivity in detecting metastases, prior to and during therapy, than current imaging standard of care (CT and bone scan), and is not widely clinically available outside of the research realm in North America.
Positron emission tomography / computer tomography (PET/CT) is a nuclear medicine diagnostic imaging procedure based on the measurement of positron emission from radiolabeled tracer molecules in vivo. PSMA is a homodimeric type II membrane metalloenzyme that functions as a glutamate carboxypeptidase/folate hydrolase and is overexpressed in PCa. PSMA is expressed in the vast majority of PCa tissue specimens and its degree of expression correlates with a number of important metrics of PCa tumor aggressiveness including Gleason score, propensity to metastasize and the development of castration resistance.
[18F]DCFPyL is a promising high-sensitivity second generation PSMA-targeted urea-based PET probe. Studies employing second-generation PSMA PET/CT imaging in men with biochemical progression after definitive therapy suggest detection of metastases in over 60% of men imaged.
Deep learning is defined as a variant of artificial neural networks, using multiple layers of 'neurons'. Deep learning has been investigated in medical imaging in numerous applications across organ systems. In oncology, basic artificial neural networks to support decision-making have previously been developed retrospectively in breast cancer and prostate cancer, but have not been validated or integrated prospectively. Novel data-driven methods are needed to predict outcomes as early as possible in order to guide the duration and the aggressiveness of a particular therapy. They are also needed for optimal patient selection based on the patient's response to a given therapy.
Here the investigators hypothesize that the combination of a highly performing prostate cancer imaging technique combined with machine learning has high potential. The main objective of this study is to acquire PSMA-PET data in patients with prostate cancer who receive treatment and follow-up in order to enable the discovery of predictive imaging biomarkers through deep learning techniques.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Prostate Cancer
7. Study Design
Primary Purpose
Diagnostic
Study Phase
Phase 3
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
1000 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Main arm
Arm Type
Experimental
Arm Description
PET-CT imaging following 18F-DCFPyL injection, 1 injection, IV, 10 mCi
Intervention Type
Diagnostic Test
Intervention Name(s)
18F-DCFPyL IV injection
Intervention Description
Patient will receive one injection of 18F-DCFPyL and undergo PET-CT imaging
Primary Outcome Measure Information:
Title
Overall survival
Description
Images from the 18F-DCFPyL PET-CT scans will be combined with patient follow-up data in a deep learning algorithm to discover radiomics features predicting outcomes (overall survival).
Time Frame
5 years
Secondary Outcome Measure Information:
Title
Progression free survival
Description
Images from the 18F-DCFPyL PET-CT scans will be combined with patient follow-up data in a deep learning algorithm to discover radiomics features predicting outcomes (progression free survival).
Time Frame
5 years
10. Eligibility
Sex
Male
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
Patients with prostate cancer, being followed and treated at CHUM, whose treating physician at CHUM has requested a PSMA-PET scan.
Exclusion Criteria:
Claustrophobia/inability to complete imaging procedure.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Daniel Juneau, MD
Phone
1-514-890-8180
Email
daniel.juneau@umontreal.ca
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Daniel Juneau, MD
Organizational Affiliation
Centre hospitalier de l'Université de Montréal (CHUM)
Official's Role
Principal Investigator
Facility Information:
Facility Name
Centre Hospitalier de l'université de Montréal
City
Montréal
State/Province
Quebec
ZIP/Postal Code
H2X 0C1
Country
Canada
Individual Site Status
Recruiting
12. IPD Sharing Statement
Learn more about this trial
PSMA-PET: Deep Radiomic Biomarkers of Progression and Response Prediction in Prostate Cancer
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