Prostate Cancer Clinical Trial
Official title:
Pretreatment Staging of High-Risk Prostate Cancer With 18F-Fluciclovine PET/MRI
There is great need for improved preoperative imaging in men with high-risk prostate cancer. Investigators propose to develop and validate an optimized simultaneous PET/MRI protocol for local, regional and whole body preoperative staging in a single imaging session using the amino acid PET tracer, F-18 fluciclovine. Despite advances in the diagnosis and treatment of prostate cancer, the preoperative staging of men with prostate carcinoma (PCa) is currently problematic. Conventional imaging is falsely negative for regional lymph node metastases in a substantial fraction of men. In particular, approximately 35% of men with high-risk prostate cancer will have biochemical recurrence even after optimal surgical resection. A major benefit of simultaneous acquisition of a multiparametric prostate MRI (mpMRI) and F-18 fluciclovine PET includes having the patient undergo a single imaging study which provides both anatomic and molecular characterization of the tumor, including metastases which would potentially be missed by conventional anatomic imaging and size criteria. Additionally, simultaneous acquisition will improve co-registration of the PET and MR data which is valuable for small lesions and in anatomically complex regions. Although the use of fluciclovine in the characterization of the primary PCa remains to be established, the anatomic detail provided by conventional mpMRI will complement the detection of small volume metastatic disease by fluciclovine PET. Additionally, the use of hybrid PET/MRI technology allows for the assessment of dynamic tracer uptake and washout during the whole body and regional PET/MRI scan, which may demonstrate the ability to increase detection of the primary PCa on fluciclovine PET. If F-18 fluciclovine PET/MRI can reliably and accurately detect nodal metastases in high-risk prostate cancer patients, surgeons may use this new technology to develop new treatment algorithms for the optimal management of these patients.
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