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REVIEWS AN UPDATE ON MOLECULAR IMAGING OF PROSTATE CANCER (Part I)
The Quarterly Journal of Nuclear Medicine and Molecular Imaging 2012 August;56(4):331-42
Copyright © 2012 EDIZIONI MINERVA MEDICA
lingua: Inglese
Conventional imaging and Multiparametric Magnetic Resonance (MRI, MRS, DWI, MRP) in the diagnosis of prostate cancer
Panebianco V. 1, Sciarra A. 2, Marcantonio A. 1, Forte V. 1, Biondi T. 1, Laghi A. 1, Catalano C. 1 ✉
1 Department of Radiological Sciences, Oncology and Pathology, Sapienza University, Rome, Italy; 2 Department of Urology, Sapienza University, Rome, Italy
The evaluation and management of prostate cancer (PCa) are based mainly on parameters such as the serum prostate-specific antigen level, clinical stage, and pathologic findings at biopsy or after surgery. The aim of this paper was to review the current roles of conventional imaging and multiparametric magnetic resonance imaging (mpMRI) techniques in the diagnosis of PCa. A non systematic literature search using the Medline and Cochrane Library databases was performed up to January 2012. Bibliographies of retrieved articles and review articles were also examined. Only those articles reporting complete data with clinical relevance for the present review (i.e., diagnosis, staging) were selected. The advent of a high performance (1.5T) and higher fields strength (3T), and thus, higher spatial resolution, increased the potentiality and the diffusion of MR examinations. Intense research has focused on the use of complementary techniques to improve the detection, characterization, and staging of PCa by MRI. This review article is divided into two major parts: the first one considers the technical aspects of mpMRI; the second part is intended to provide the impact of this technique on patients with PCa. Published data indicate an emerging role for MRI (particularly mpMRI combining T2 weighted imaging, diffusion weighted imaging, contrast enhanced MR, and spectroscopy) as the most sensitive and specific tool available for imaging PCa. MpMRI can provide metabolic information, characterize tissue and tumor vascularity, as well as tissue cellularity and correlate with tumor aggressiveness.