JOURNAL ARTICLE

Added Value of Multiparametric Ultrasonography in Magnetic Resonance Imaging and Ultrasonography Fusion-guided Biopsy of the Prostate in Patients With Suspicion for Prostate Cancer

Andreas Maxeiner, Carsten Stephan, Tahir Durmus, Torsten Slowinski, Hannes Cash, Thomas Fischer
Urology 2015, 86 (1): 108-14
26142593

OBJECTIVE: To analyze whether magnetic resonance imaging-ultrasonography (MRI-US) fusion-guided biopsy detects more and clinical significant prostate cancer (PCa) in comparison to conventional transrectal US-guided prostate biopsy (PBX) and to investigate if multiparametric (mp) US during MRI-US fusion can further characterize mpMRI-suspected lesions according to the prostate MRI reporting and data system (PI-RADS).

METHODS: From January 2012 to January 2014, 169 patients with a median of 2 negative conventional PBX and/or initially or consistently elevated prostate-specific antigen levels were prospectively included and underwent 3 T mpMRI. Real-time MRI-US fusion scan was used to biopsy the mpMRI-targeted lesions (n = 316). Scanning by mpUS, including B-mode, power Doppler, strain elastography, and contrast-enhanced US was performed to further characterize those lesions and to score by US modalities resulting in an mpUS score. Afterward, a conventional 10-core PBX was performed. PCa detection based on the results of targeted and conventional PBX was estimated. Performances of single US modalities were analyzed. The mpUS score was also investigated for PCa and PI-RADS score prediction.

RESULTS: Among 169 patients, 71 PCa (42%) were detected. From these 71 cases, clinically significant PCa (Gleason score ≥7) were detected exclusively by MRI-US fusion in 31 from 46 cases (67.4%). The highest sensitivity was observed in contrast-enhanced US (85%) and elastography (80%). The mpUS score predicts PCa and PI-RADS score with an overall accuracy of 86% and 80%, respectively.

CONCLUSION: MRI-US fusion-guided PBX detects more clinically significant PCa compared with conventional TRUS. The mpUS score correlates with PI-RADS in PCa prediction.

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