PSMA-PET: Deep Radiomic Biomarkers of Progression and Response Prediction in Prostate Cancer

NCT ID: NCT03594760

Last Updated: 2024-06-04

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: PHASE3
• Total Enrollment: 1000 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2018-12-01
• Study Completion Date: 2029-12-31

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.

Conditions

Prostate Cancer

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Main arm

PET-CT imaging following 18F-DCFPyL injection, 1 injection, IV, 10 mCi

Group Type: EXPERIMENTAL

18F-DCFPyL IV injection

Intervention Type: DIAGNOSTIC_TEST

Patient will receive one injection of 18F-DCFPyL and undergo PET-CT imaging

Interventions

18F-DCFPyL IV injection

Patient will receive one injection of 18F-DCFPyL and undergo PET-CT imaging

Intervention Type: DIAGNOSTIC_TEST

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.

• Minimum Eligible Age: 18 Years
• Eligible Sex: MALE
• Accepts Healthy Volunteers: No

Sponsors

Centre hospitalier de l'Université de Montréal (CHUM)

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Daniel Juneau, MD

Role: PRINCIPAL_INVESTIGATOR

Centre hospitalier de l'Université de Montréal (CHUM)

Locations

Centre Hospitalier de l'université de Montréal

Montreal, Quebec, Canada

Site Status: RECRUITING

Countries

Canada

Central Contacts

Daniel Juneau, MD

Role: CONTACT

daniel.juneau@umontreal.ca

1-514-890-8180

Other Identifiers

18.068

Identifier Type: -

Identifier Source: org_study_id