- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03354416
Profiling of Radiological Factors in Treatment and Outcomes in Prostate Cancer
Background:
Prostate cancer is one of the most common cancers for men in the U.S. There are some new ways to take pictures of the cancer. There are also new ways to use image-guided biopsy and therapy. These could help manage prostate cancer. Researchers want to study how imaging can provide a profile of prostate cancer. They want to collect data to make diagnosis and treatments better.
Objectives:
To gather data about the radiological and clinical course of prostate cancer. To study imaging-based biomarkers of prostate cancer.
Eligibility:
Men ages 18 and older with diagnosed or suspected prostate cancer
Design:
Participants will give permission for researchers to use their medical history and records. Their data will be reviewed, collected, and analyzed. These include results of their tests and scans.
Sponsoring Institution: National Cancer Institute
Study Overview
Status
Detailed Description
Background:
- Multiparametric MRI (mpMRI) has become an established method for localizing clinically significant prostate cancer, and identification of imaging-based prognostic markers represents an active research area.
- Multiple treatments are available for patients with localized prostate cancer, including radical prostatectomy, external beam radiotherapy, brachytherapy, and focal ablation; however, therapy-specific indication and imaging-based response biomarkers are poorly understood.
- As mpMRI is considered a standard of care , there is no patient consent for research related to imaging biomarkers and their correlation with other clinical and pathologic features.
- Translation of imaging, clinical, and pathological-based features into treatment decisions has yet to be fully characterized for development of a decision-support system.
- Therefore, the purpose of this protocol is to enable the collection of data to enable research in the development of computer aided diagnosis, decision support and deep learning/artificial intelligence research.
Objective:
-To evaluate radiological profiling of patients with prostate cancer in support of the Molecular Imaging Branch (MIB) for identification of imaging-based prognostic markers in prostate cancer.
Eligibility:
- Patients with an increased risk for prostate cancer, with a diagnosis of prostatic cancer or suspicious for prostatic cancer lesions.
- Age > 18 years.
Design:
-Imaging evaluation and clinical profiling of patients with an increased risk of prostate cancer, with prostate cancer or suspected of prostate cancer (obtained during visits to NIH or from external providers) will be collected over the course of at least 5 years and analyzed.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Ismail B Turkbey, M.D.
- Phone Number: (240) 760-6112
- Email: turkbeyi@mail.nih.gov
Study Contact Backup
- Name: Yolanda L McKinney, R.N.
- Phone Number: (240) 760-6095
- Email: ymckinney@mail.nih.gov
Study Locations
-
-
Maryland
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Bethesda, Maryland, United States, 20892
- Recruiting
- National Institutes of Health Clinical Center
-
Contact:
- For more information at the NIH Clinical Center contact National Cancer Institute Referral Office
- Phone Number: 888-624-1937
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
- INCLUSION CRITERIA:
- Patients with an increased risk for prostate cancer (strong family history and/or germline mutation in DNA repair genes), or with a diagnosis of prostatic cancer or suspicious for prostatic cancer lesions.
- Age greater than or equal to 18 years
- Ability of subject to understand and the willingness to sign a written informed consent document.
EXCLUSION CRITERIA:
-none
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Other
Cohorts and Interventions
Group / Cohort |
|---|
|
1/ Cohort 1
Subjects with an increased risk of prostate cancer or a diagnosis of prostatic cancer or suspicious for prostatic cancer lesions.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Associations between imaging features and clinicopathological factors
Time Frame: 10 years
|
Radiological profiling of patients with prostate cancer
|
10 years
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Ismail B Turkbey, M.D., National Cancer Institute (NCI)
Publications and helpful links
General Publications
- Toth R, Sperling D, Madabhushi A. Quantifying Post- Laser Ablation Prostate Therapy Changes on MRI via a Domain-Specific Biomechanical Model: Preliminary Findings. PLoS One. 2016 Apr 18;11(4):e0150016. doi: 10.1371/journal.pone.0150016. eCollection 2016.
- Wang S, Burtt K, Turkbey B, Choyke P, Summers RM. Computer aided-diagnosis of prostate cancer on multiparametric MRI: a technical review of current research. Biomed Res Int. 2014;2014:789561. doi: 10.1155/2014/789561. Epub 2014 Dec 1.
- Lavery HJ, Cooperberg MR. Clinically localized prostate cancer in 2017: A review of comparative effectiveness. Urol Oncol. 2017 Feb;35(2):40-41. doi: 10.1016/j.urolonc.2016.11.013. Epub 2016 Dec 18.
- Esengur OT, Stevenson E, Stecko H, Lay NS, Yang D, Tetreault J, Xu Z, Xu D, Yilmaz EC, Gelikman DG, Harmon SA, Merino MJ, Gurram S, Wood BJ, Choyke PL, Pinto PA, Turkbey B. Assessing the Impact of Transition and Peripheral Zone PSA Densities Over Whole-Gland PSA Density for Prostate Cancer Detection on Multiparametric MRI. Prostate. 2025 May;85(6):612-624. doi: 10.1002/pros.24863. Epub 2025 Feb 25.
- Lin Y, Yilmaz EC, Belue MJ, Harmon SA, Tetreault J, Phelps TE, Merriman KM, Hazen L, Garcia C, Yang D, Xu Z, Lay NS, Toubaji A, Merino MJ, Xu D, Law YM, Gurram S, Wood BJ, Choyke PL, Pinto PA, Turkbey B. Evaluation of a Cascaded Deep Learning-based Algorithm for Prostate Lesion Detection at Biparametric MRI. Radiology. 2024 May;311(2):e230750. doi: 10.1148/radiol.230750.
- Yilmaz EC, Shih JH, Belue MJ, Harmon SA, Phelps TE, Garcia C, Hazen LA, Toubaji A, Merino MJ, Gurram S, Choyke PL, Wood BJ, Pinto PA, Turkbey B. Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection and Investigation of Multiparametric MRI-derived Markers. Radiology. 2023 May;307(4):e221309. doi: 10.1148/radiol.221309. Epub 2023 May 2.
Helpful Links
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- 180017
- 18-C-0017
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ICF
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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