Abdominal Imaging

, Volume 39, Issue 5, pp 1027–1035 | Cite as

Abnormal findings on multiparametric prostate magnetic resonance imaging predict subsequent biopsy upgrade in patients with low risk prostate cancer managed with active surveillance

  • Robert R. Flavell
  • Antonio C. WestphalenEmail author
  • Carmin Liang
  • Christopher C. Sotto
  • Susan M. Noworolski
  • Daniel B. Vigneron
  • Zhen J. Wang
  • John Kurhanewicz



To determine the ability of multiparametric MR imaging to predict disease progression in patients with prostate cancer managed by active surveillance.


Sixty-four men with biopsy-proven prostate cancer managed by active surveillance were included in this HIPPA compliant, IRB approved study. We reviewed baseline MR imaging scans for the presence of a suspicious findings on T2-weighted imaging, MR spectroscopic imaging (MRSI), and diffusion-weighted MR imaging (DWI). The Gleason grades at subsequent biopsy were recorded. A Cox proportional hazard model was used to determine the predictive value of MR imaging for Gleason grades, and the model performance was described using Harrell’s C concordance statistic and 95% confidence intervals (CIs).


The Cox model that incorporated T2-weighted MR imaging, DWI, and MRSI showed that only T2-weighted MR imaging and DWI are independent predictors of biopsy upgrade (T2; HR = 2.46; 95% CI 1.36–4.46; P = 0.003—diffusion; HR = 2.76; 95% CI 1.13–6.71; P = 0.03; c statistic = 67.7%; 95% CI 61.1–74.3). There was an increasing rate of Gleason score upgrade with a greater number of concordant findings on multiple MR sequences (HR = 2.49; 95% CI 1.72–3.62; P < 0.001).


Abnormal results on multiparametric prostate MRI confer an increased risk for Gleason score upgrade at subsequent biopsy in men with localized prostate cancer managed by active surveillance. These results may be of help in appropriately selecting candidates for active surveillance.


Prostate cancer Active surveillance Magnetic resonance imaging Magnetic resonance spectroscopic imaging Diffusion-weighted magnetic resonance imaging 


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Robert R. Flavell
    • 1
  • Antonio C. Westphalen
    • 1
    Email author
  • Carmin Liang
    • 1
  • Christopher C. Sotto
    • 1
  • Susan M. Noworolski
    • 1
  • Daniel B. Vigneron
    • 1
  • Zhen J. Wang
    • 1
  • John Kurhanewicz
    • 1
  1. 1.Department of Radiology and Biomedical ImagingUniversity of California, San FranciscoSan FranciscoUSA

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