Profiling of Radiological Factors in Treatment and Outcomes in Prostate Cancer

Обзор

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

Подробное описание

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.

Первичные конечные точки

• Associations between imaging features and clinicopathological factors [Срок оценки: 10 years]

Критерии участия

• 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.

Критерии исключения

-none

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

США · 1 центр

• National Institutes of Health Clinical Center — Bethesda

Публикации

• 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. PMID 27088600
• 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. PMID 25525604
• 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. PMID 27998677
• 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 PMID 39996409
• 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. PMID 38713024
• 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. PMID 37129493

Идентификаторы

NCT: NCT03354416 · 180017 · 18-C-0017

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

Открыть это исследование на ClinicalTrials.gov ↗