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J Magn Reson Imaging ; 41(5): 1365-73, 2015 May.
Article in English | MEDLINE | ID: mdl-24833417

ABSTRACT

PURPOSE: To demonstrate dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of the prostate with both high spatial and temporal resolution via a combination of golden-angle radial k-space sampling, compressed sensing, and parallel-imaging reconstruction (GRASP), and to compare image quality and lesion depiction between GRASP and conventional DCE in prostate cancer patients. MATERIALS AND METHODS: Twenty prostate cancer patients underwent two 3T prostate MRI examinations on separate dates, one using standard DCE (spatial resolution 3.0 × 1.9 × 1.9 mm, temporal resolution 5.5 sec) and the other using GRASP (spatial resolution 3.0 × 1.1 × 1.1 mm, temporal resolution 2.3 sec). Two radiologists assessed measures of image quality and dominant lesion size. The experienced reader recorded differences in contrast arrival times between the dominant lesion and benign prostate. RESULTS: Compared with standard DCE, GRASP demonstrated significantly better clarity of the capsule, peripheral/transition zone boundary, urethra, and periprostatic vessels; image sharpness; and lesion conspicuity for both readers (P < 0.001-0.020). GRASP showed improved interreader correlation for lesion size (GRASP: r = 0.691-0.824, standard: r = 0.495-0.542). In 8/20 cases, only GRASP showed earlier contrast arrival in tumor than benign; in no case did only standard DCE show earlier contrast arrival in tumor. CONCLUSION: High spatiotemporal resolution prostate DCE is possible with GRASP, which has the potential to improve image quality and lesion depiction as compared with standard DCE.


Subject(s)
Gadolinium DTPA , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Prostate/pathology , Prostatic Neoplasms/pathology , Aged , Algorithms , Contrast Media , Data Compression/methods , Humans , Male , Numerical Analysis, Computer-Assisted , Reproducibility of Results , Sample Size , Sensitivity and Specificity , Signal Processing, Computer-Assisted , Spatio-Temporal Analysis
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