Prostate Cancer Clinical Trial
— NA_00067284Official title:
Multiparametric MRI for Assessing Radiotherapy Treatment Response of Prostate Cancer
Prostate cancer is one of most common cancers in America, affecting 1 in 6 men. External beam radiation therapy is one of the common methods to treat prostate cancer. Although radiotherapy is effective, side effects to the adjacent normal organs limit the therapeutic ratio. Those side effects are usually associated with the radiation damage of the normal tissue surrounding prostate, e.g. bladder, urethra and rectum etc. Both effectiveness and the side effects of radiation treatment are often accessed after whole course of radiotherapy, which makes the early intervention difficult. The current research project is a feasibility study of utilizing advanced magnetic resonance imaging (MRI) techniques to access radiotherapy treatment response of prostate cancer during and right after radiotherapy. Many advanced MRI techniques, e.g. spectroscopy (MRS), diffusion-weighted (DWI), dynamic contrast enhanced (DCE) perfusion weighted images, have been used in radiology departments for diagnostic purpose. This research project is to study the feasibility of using advanced MRI sequences to monitor tissue response during and after radiotherapy. The tissue changes revealed from MRI can provide physicians early information on possible tumor recurrence and normal tissue toxicity, therefore, the early intervention may be possible to spare normal tissue and cure the patient. The project is designed to combine several different advanced MRI imaging techniques systematically to study tissue changes during radiotherapy, which has not been seen elsewhere to date. Another important goal of this research project is to study the feasibility of associating functional MRI with radiation treatment dose distribution. Tissue response during radiation treatment depends on dose. The functional MRI can provide more information than simple anatomic information. Mapping the functional MRI spatially and associating them with 3D dose distribution in radiation treatment planning system is one important step to quantitative assess the relationship between radiation treatment and tissue changes due to the radiation.
Status | Recruiting |
Enrollment | 20 |
Est. completion date | December 2027 |
Est. primary completion date | December 2025 |
Accepts healthy volunteers | No |
Gender | Male |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Histologically-confirmed prostate cancer - Plan to undergo external radiation treatment of prostate cancer Exclusion Criteria: - Patients who cannot undergo an MRIs - Patients who are allergic to gadolinium based contrast agent - Patients who have cardiac pacemaker or other electronic or metal implant - Patients who have chronic kidney disease |
Country | Name | City | State |
---|---|---|---|
United States | The Sidney Kimmel Comprehsensive Cancer Center at Johns Hopkins | Baltimore | Maryland |
Lead Sponsor | Collaborator |
---|---|
Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | MRI use to predict treatment response | To study the feasibility of using magnetic resonance imaging (MRI) to predict treatment response in patients with prostate cancer undergoing radiation therapy. The anatomical, functional, and location changes in tumor or normal tissues during the radiation will be assessed and correlated with MRI data and treatment dose. Hypothesis one: Functional or anatomical MRI signal changes during the radiotherapy can be used as predictors to assess treatment response. We anticipate observing dose dependent MRI signal changes during the radiation treatment. |
2 months | |
Secondary | Evaluating MRI use to predict functional radiation treatment dose distribution | Secondary objective: A secondary objective is evaluating the feasibility of associating functional MRI images with radiation treatment dose distribution. Both tumor control probability and normal tissue complication probability are related to the dose received by patient during the radiotherapy. Hypothesis two: With carefull data processing, resampling and registration, the functional MRI data can be imported into radiation treatment planning system. Quantitative analysis to assess tissue changes during radiotherapy and its correlation with radiation dose treatment can be performed. |
2 months |
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