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Recruiting Phase 3 NCT03594760

NCT03594760 PSMA-PET: Deep Radiomic Biomarkers of Progression and Response Prediction in Prostate Cancer

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Clinical Trial Summary
NCT ID NCT03594760
Status Recruiting
Phase Phase 3
Sponsor Centre hospitalier de l'Université de Montréal (CHUM)
Condition Prostate Cancer
Study Type INTERVENTIONAL
Enrollment 1,000 participants
Start Date 2018-12-01
Primary Completion 2028-12

Eligibility & Interventions

Sex Male only
Min Age 18 Years
Max Age N/A
Study Type INTERVENTIONAL
Interventions
18F-DCFPyL IV injection

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

You will actively receive the study intervention — which may be a drug, biologic, device, or procedure.

Phase 3 trials are large pivotal studies comparing the treatment to current standard of care or placebo. Your participation directly contributes to the evidence needed for regulatory approval.

This trial targets 1,000 participants in total. It began in 2018-12-01 with a primary completion date of 2028-12.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

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.

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.

Contact & Investigator

Central Contact

Daniel Juneau, MD

✉ daniel.juneau@umontreal.ca

📞 1-514-890-8180

Principal Investigator

Daniel Juneau, MD

PRINCIPAL INVESTIGATOR

Centre hospitalier de l'Université de Montréal (CHUM)

Frequently Asked Questions

Who can join the NCT03594760 clinical trial?

This trial is open to male participants only, aged 18 Years or older, studying Prostate Cancer. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

What phase is the NCT03594760 trial and what does that mean for participants?

Phase 3 trials are large-scale studies comparing the new treatment to existing standards of care or a placebo. They provide the evidence needed for regulatory approval. This trial targets 1,000 participants.

Is NCT03594760 currently recruiting?

Yes, NCT03594760 is actively recruiting participants. Contact the research team at daniel.juneau@umontreal.ca for enrollment information.

Where is the NCT03594760 trial being conducted?

This trial is being conducted at Montreal, Canada.

Who is sponsoring the NCT03594760 clinical trial?

NCT03594760 is sponsored by Centre hospitalier de l'Université de Montréal (CHUM). The principal investigator is Daniel Juneau, MD at Centre hospitalier de l'Université de Montréal (CHUM). The trial plans to enroll 1,000 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: July 2026  ·  Data Methodology