Multiparametric magnetic resonance imaging in prostate... : Current Opinion in Urology (original) (raw)

New developments in imaging of urologic tumours: Edited by Hedvig Hricak

Multiparametric magnetic resonance imaging in prostate cancer: present and future

Kurhanewicz, Johna,b; Vigneron, Daniela; Carroll, Peterb; Coakley, Fergusa,b

aDepartment of Radiology, USA

bDepartment of Urology, University of California, San Francisco, California, USA

Correspondence to Dr John Kurhanewicz, Byers Hall, Room 203E, 1700 4th St, San Francisco, CA 94158-2330, USA Tel: +1 415 514 9711; fax: +1 415 514 4714; e-mail: [email protected]

Abstract

Purpose of review

The purpose of this article is to review the current status of advanced MRI techniques based on anatomic, metabolic and physiologic properties of prostate cancer with a focus on their impact in managing prostate cancer patients.

Recent findings

Prostate cancer can be identified based on reduced T2 signal intensity on MRI, increased choline and decreased citrate and polyamines on magnetic resonance spectroscopic imaging (MRSI), decreased diffusivity on diffusion tensor imaging (DTI), and increased uptake on dynamic contrast enhanced (DCE) imaging. All can be obtained within a 60-min 3T magnetic resonance exam. Each complementary method has inherent advantages and disadvantages: T2 MRI has high sensitivity but poor specificity; magnetic resonance spectroscopic imaging has high specificity but poor sensitivity; diffusion tensor imaging has high spatial resolution, is the fastest, but sensitivity/specificity needs to be established; dynamic contrast enhanced imaging has high spatial resolution, but requires a gadolinium based contrast agent injection, and sensitivity/specificity needs to be established.

Summary

The best characterization of prostate cancer in individual patients will most likely result from a multiparametric (MRI/MRSI/DTI/DCE) exam using 3T magnetic resonance scanners but questions remain as to how to analyze and display this large amount of imaging data, and how to optimally combine the data for the most accurate assessment of prostate cancer. Histological correlations or clinical outcomes are required to determine sensitivity/specificity for each method and optimal combinations of these approaches.