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Parametric PET/MR Fusion Imaging to Differentiate Aggressive from Indolent Primary Prostate Cancer with Application for Image-Guided Prostate Cancer Biopsies.

机译:参数化pET / mR融合成像以区分侵袭性和惰性前列腺癌与应用于图像引导的前列腺癌活组织检查。

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The study investigates whether fusion PET/MRI imaging with 18F- choline PET/CT and diffusion-weighted MRI can be successfully applied to target prostate cancer using image-guided prostate biopsies. The study further aims to establish whether fusion PET/MRI-derived parametric imaging parameters identify significant prostate cancer better than standard prostate biopsies. In order to achieve these objectives, prostate cancer patients will undergo PET and MR imaging, followed by standard prostate biopsy with additional targeted prostate biopsies. Biopsy samples will undergo histological evaluation and target metabolite analysis to evaluate underlying metabolic changes observed with prostate cancer progression. Depending on the pathology result of biopsies, some subjects will undergo prostatectomy involving additional MRI of the prostate specimen and registration of imaging to whole mount pathology. We obtained IRB approval prior to the start of the project. During the first year of the 4 year study, we established and optimized various aspects of the study procedures. The 18F-choline radiotracer synthesis was established, we obtained a 3T endorectal coil, tested and optimized immunohistochemistry of prostatectomy specimen, modified existing mass spectrometry methods for choline pathway metabolite analyses, implemented multi-modality image fusion to generate PET/MR fusion images for targeted prostate biopsies using mutual information software and performed such targeted biopsies. PET/MRI volumes were loaded into the GE Logic E9 ultrasound system and a rigid fusion with real-time ultrasound was obtained. The procedural steps for the prostate biopsy were optimized to allow for sufficient registration with real-time ultrasound. To date, 11 subjects have been enrolled (recruitment goal is 40 subjects in 4 years).

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