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

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Abstract

Purpose

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

Methods

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).

Results

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).

Conclusions

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.

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References

  1. Dall’era MA, Albertsen PC, Bangma C, et al. (2012) Active surveillance for prostate cancer: a systematic review of the literature. Eur Urol 62(6):976–983. doi:10.1016/j.eururo.2012.05.072

    Article  PubMed  Google Scholar 

  2. Duffield AS, Lee TK, Miyamoto H, Carter HB, Epstein JI (2009) Radical prostatectomy findings in patients in whom active surveillance of prostate cancer fails. J Urol 182(5):2274–2278. doi:10.1016/j.juro.2009.07.024

    Article  PubMed  Google Scholar 

  3. Klotz L, Zhang L, Lam A, et al. (2010) Clinical results of long-term follow-up of a large, active surveillance cohort with localized prostate cancer. J Clin Oncol 28(1):126–131. doi:10.1200/JCO.2009.24.2180

    Article  PubMed  Google Scholar 

  4. Yakar D, Debats OA, Bomers JG, et al. (2012) Predictive value of MRI in the localization, staging, volume estimation, assessment of aggressiveness, and guidance of radiotherapy and biopsies in prostate cancer. J Magn Reson Imaging 35(1):20–31. doi:10.1002/jmri.22790

    Article  PubMed  Google Scholar 

  5. Hoeks CM, Barentsz JO, Hambrock T, et al. (2011) Prostate cancer: multiparametric MR imaging for detection, localization, and staging. Radiology 261(1):46–66. doi:10.1148/radiol.11091822

    Article  PubMed  Google Scholar 

  6. Hegde JV, Mulkern RV, Panych LP, et al. (2013) Multiparametric MRI of prostate cancer: an update on state-of-the-art techniques and their performance in detecting and localizing prostate cancer. J Magn Reson Imaging 37(5):1035–1054. doi:10.1002/jmri.23860

    Article  PubMed  PubMed Central  Google Scholar 

  7. Bonekamp D, Jacobs MA, El-Khouli R, Stoianovici D, Macura KJ (2011) Advancements in MR imaging of the prostate: from diagnosis to interventions. Radiographics 31(3):677–703. doi:10.1148/rg.313105139

    Article  PubMed  PubMed Central  Google Scholar 

  8. Moore CM, Ridout A, Emberton M (2013) The role of MRI in active surveillance of prostate cancer. Curr Opin Urol 23(3):261–267. doi:10.1097/MOU.0b013e32835f899f

    PubMed  Google Scholar 

  9. Ouzzane A, Puech P, Villers A (2012) MRI and surveillance. Curr Opin Urol 22(3):231–236. doi:10.1097/MOU.0b013e328351dcf7

    Article  PubMed  Google Scholar 

  10. Dianat SS, Carter HB, Macura KJ (2013) Performance of multiparametric magnetic resonance imaging in the evaluation and management of clinically low-risk prostate cancer. Urol Oncol . doi:10.1016/j.urolonc.2013.04.002

    PubMed  PubMed Central  Google Scholar 

  11. Chen AP, Cunningham CH, Kurhanewicz J, et al. (2006) High-resolution 3D MR spectroscopic imaging of the prostate at 3 T with the MLEV-PRESS sequence. Magn Reson Imaging 24(7):825–832

    Article  PubMed  CAS  Google Scholar 

  12. Barentsz JO, Richenberg J, Clements R, et al. (2012) ESUR prostate MR guidelines 2012. Eur Radiol 22(4):746–757. doi:10.1007/s00330-011-2377-y

    Article  PubMed  PubMed Central  Google Scholar 

  13. Kozlowski P, Chang SD, Goldenberg SL (2008) Diffusion-weighted MRI in prostate cancer—comparison between single-shot fast spin echo and echo planar imaging sequences. Magn Reson Imaging 26(1):72–76. doi:10.1016/j.mri.2007.04.008

    Article  PubMed  Google Scholar 

  14. Somford DM, Hambrock T, Hulsbergen-van de Kaa CA, et al. (2012) Initial experience with identifying high-grade prostate cancer using diffusion-weighted MR imaging (DWI) in patients with a Gleason score ≤ 3 + 3 = 6 upon schematic TRUS-guided biopsy: a radical prostatectomy correlated series. Investig Radiol 47(3):153–158. doi:10.1097/RLI.0b013e31823ea1f0

    Google Scholar 

  15. Hambrock T, Somford DM, Huisman HJ, et al. (2011) Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer. Radiology 259(2):453–461. doi:10.1148/radiol.11091409

    Article  PubMed  Google Scholar 

  16. Itou Y, Nakanishi K, Narumi Y, Nishizawa Y, Tsukuma H (2011) Clinical utility of apparent diffusion coefficient (ADC) values in patients with prostate cancer: can ADC values contribute to assess the aggressiveness of prostate cancer? J Magn Reson Imaging 33(1):167–172. doi:10.1002/jmri.22317

    Article  PubMed  Google Scholar 

  17. Verma SK, McClure K, Parker L, et al. (2010) Simple linear measurements of the normal liver: interobserver agreement and correlation with hepatic volume on MRI. Clin Radiol 65(4):315–318. doi:10.1016/j.crad.2009.09.016

    Article  PubMed  CAS  Google Scholar 

  18. Vargas HA, Akin O, Franiel T, et al. (2011) Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness. Radiology 259(3):775–784. doi:10.1148/radiol.11102066

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chenevert TL, Galban CJ, Ivancevic MK, et al. (2011) Diffusion coefficient measurement using a temperature-controlled fluid for quality control in multicenter studies. J Magn Reson Imaging 34(4):983–987. doi:10.1002/jmri.22363

    Article  PubMed  PubMed Central  Google Scholar 

  20. Males RG, Vigneron DB, Star-Lack J, et al. (2000) Clinical application of BASING and spectral/spatial water and lipid suppression pulses for prostate cancer staging and localization by in vivo 3D 1H magnetic resonance spectroscopic imaging. Magn Reson Med 43(1):17–22

    Article  PubMed  CAS  Google Scholar 

  21. Lee DH, Koo KC, Lee SH, et al. (2013) Tumor lesion diameter on diffusion weighted magnetic resonance imaging could help predict insignificant prostate cancer in patients eligible for active surveillance: preliminary analysis. J Urol 190(4):1213–1217. doi:10.1016/j.juro.2013.03.127

    Article  PubMed  Google Scholar 

  22. Puech P, Potiron E, Lemaitre L, et al. (2009) Dynamic contrast-enhanced-magnetic resonance imaging evaluation of intraprostatic prostate cancer: correlation with radical prostatectomy specimens. Urology 74(5):1094–1099. doi:10.1016/j.urology.2009.04.102

    Article  PubMed  Google Scholar 

  23. Borofsky MS, Rosenkrantz AB, Abraham N, Jain R, Taneja SS (2013) Does suspicion of prostate cancer on integrated T2 and diffusion-weighted MRI predict more adverse pathology on radical prostatectomy? Urology 81(6):1279–1283. doi:10.1016/j.urology.2012.12.026

    Article  PubMed  Google Scholar 

  24. Nagarajan R, Margolis D, Raman S, et al. (2012) MR spectroscopic imaging and diffusion-weighted imaging of prostate cancer with Gleason scores. J Magn Reson Imaging 36(3):697–703. doi:10.1002/jmri.23676

    Article  PubMed  Google Scholar 

  25. Shukla-Dave A, Hricak H, Akin O, et al. (2012) Preoperative nomograms incorporating magnetic resonance imaging and spectroscopy for prediction of insignificant prostate cancer. BJU Int 109(9):1315–1322. doi:10.1111/j.1464-410X.2011.10612.x

    Article  PubMed  PubMed Central  Google Scholar 

  26. Park BH, Jeon HG, Choo SH, et al. (2013) Role of multiparametric 3.0 tesla magnetic resonance imaging in prostate cancer patients eligible for active surveillance. BJU Int. doi:10.1111/bju.12423.

  27. Turkbey B, Mani H, Aras O, et al. (2013) Prostate cancer: can multiparametric MR imaging help identify patients who are candidates for active surveillance? Radiology 268(1):144–152. doi:10.1148/radiol.13121325

    Article  PubMed  PubMed Central  Google Scholar 

  28. Guzzo TJ, Resnick MJ, Canter DJ, et al. (2012) Endorectal T2-weighted MRI does not differentiate between favorable and adverse pathologic features in men with prostate cancer who would qualify for active surveillance. Urol Oncol 30(3):301–305. doi:10.1016/j.urolonc.2010.08.023

    Article  PubMed  Google Scholar 

  29. Ploussard G, Xylinas E, Durand X, et al. (2011) Magnetic resonance imaging does not improve the prediction of misclassification of prostate cancer patients eligible for active surveillance when the most stringent selection criteria are based on the saturation biopsy scheme. BJU Int 108(4):513–517. doi:10.1111/j.1464-410X.2010.09974.x

    Article  PubMed  Google Scholar 

  30. Cabrera AR, Coakley FV, Westphalen AC, et al. (2008) Prostate cancer: is inapparent tumor at endorectal MR and MR spectroscopic imaging a favorable prognostic finding in patients who select active surveillance? Radiology 247(2):444–450. doi:10.1148/radiol.2472070770

    Article  PubMed  PubMed Central  Google Scholar 

  31. Fradet V, Kurhanewicz J, Cowan JE, et al. (2010) Prostate cancer managed with active surveillance: role of anatomic MR imaging and MR spectroscopic imaging. Radiology 256(1):176–183. doi:10.1148/radiol.10091147

    Article  PubMed  PubMed Central  Google Scholar 

  32. Morgan VA, Riches SF, Thomas K, et al. (2011) Diffusion-weighted magnetic resonance imaging for monitoring prostate cancer progression in patients managed by active surveillance. Br J Radiol 84(997):31–37. doi:10.1259/bjr/14556365

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  33. Giles SL, Morgan VA, Riches SF, et al. (2011) Apparent diffusion coefficient as a predictive biomarker of prostate cancer progression: value of fast and slow diffusion components. AJR Am J Roentgenol 196(3):586–591. doi:10.2214/AJR.10.5016

    Article  PubMed  Google Scholar 

  34. van As NJ, de Souza NM, Riches SF, et al. (2009) A study of diffusion-weighted magnetic resonance imaging in men with untreated localised prostate cancer on active surveillance. Eur Urol 56(6):981–987. doi:10.1016/j.eururo.2008.11.051

    Article  PubMed  Google Scholar 

  35. Margel D, Yap SA, Lawrentschuk N, et al. (2012) Impact of multiparametric endorectal coil prostate magnetic resonance imaging on disease reclassification among active surveillance candidates: a prospective cohort study. J Urol 187(4):1247–1252. doi:10.1016/j.juro.2011.11.112

    Article  PubMed  Google Scholar 

  36. Vargas HA, Akin O, Afaq A, et al. (2012) Magnetic resonance imaging for predicting prostate biopsy findings in patients considered for active surveillance of clinically low risk prostate cancer. J Urol 188(5):1732–1738. doi:10.1016/j.juro.2012.07.024

    Article  PubMed  Google Scholar 

  37. Hoeks CM, Somford DM, van Oort IM, et al. (2013) Value of 3-T multiparametric magnetic resonance imaging and magnetic resonance-guided biopsy for early risk restratification in active surveillance of low-risk prostate cancer: a prospective multicenter cohort study. Invest Radiol . doi:10.1097/RLI.0000000000000008

    Google Scholar 

  38. Stamatakis L, Siddiqui MM, Nix JW, et al. (2013) Accuracy of multiparametric magnetic resonance imaging in confirming eligibility for active surveillance for men with prostate cancer. Cancer 119(18):3359–3366. doi:10.1002/cncr.28216

    Article  PubMed  Google Scholar 

  39. Bonekamp D, Bonekamp S, Mullins JK, et al. (2013) Multiparametric magnetic resonance imaging characterization of prostate lesions in the active surveillance population: incremental value of magnetic resonance imaging for prediction of disease reclassification. J Comput Assist Tomogr 37(6):948–956. doi:10.1097/RCT.0b013e31829ae20a

    Article  PubMed  Google Scholar 

  40. Mullins JK, Bonekamp D, Landis P, et al. (2013) Multiparametric magnetic resonance imaging findings in men with low-risk prostate cancer followed using active surveillance. BJU Int 111(7):1037–1045. doi:10.1111/j.1464-410X.2012.11641.x

    Article  PubMed  PubMed Central  Google Scholar 

  41. Lawrentschuk N, Haider MA, Daljeet N, et al. (2010) ‘Prostatic evasive anterior tumours’: the role of magnetic resonance imaging. BJU Int 105(9):1231–1236. doi:10.1111/j.1464-410X.2009.08938.x

    Article  PubMed  Google Scholar 

  42. International Scientific Cooperation to Advance Image-Guided Prostate Cancer Care (2012) American College of Radiology News Releases. Reston: International Scientific Cooperation to Advance Image-Guided Prostate Cancer Care

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Authors and Affiliations

  1. Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Avenue, M-372, Box 0628, San Francisco, CA, USA

    Robert R. Flavell, Antonio C. Westphalen, Carmin Liang, Christopher C. Sotto, Susan M. Noworolski, Daniel B. Vigneron, Zhen J. Wang & John Kurhanewicz

Authors
  1. Robert R. Flavell
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  2. Antonio C. Westphalen
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  3. Carmin Liang
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  8. John Kurhanewicz
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Correspondence to Antonio C. Westphalen.

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Flavell, R.R., Westphalen, A.C., Liang, C. et al. Abnormal findings on multiparametric prostate magnetic resonance imaging predict subsequent biopsy upgrade in patients with low risk prostate cancer managed with active surveillance. Abdom Imaging 39, 1027–1035 (2014). https://doi.org/10.1007/s00261-014-0136-7

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  • DOI: https://doi.org/10.1007/s00261-014-0136-7

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