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Abdominal Radiology

, Volume 44, Issue 1, pp 252–258 | Cite as

Correlation of 3T multiparametric prostate MRI using prostate imaging reporting and data system (PIRADS) version 2 with biopsy as reference standard

  • Shobhit MathurEmail author
  • Martin E. O’Malley
  • Sangeet Ghai
  • Kartik Jhaveri
  • Boraiah Sreeharsha
  • Myles Margolis
  • Lehang Zhong
  • Hassan Maan
  • Ants Toi
Article

Abstract

Objective

To correlate the findings on 3T multiparametric prostate MRI using PIRADS version 2 with prostate biopsy results as the standard of reference.

Materials and methods

134 consecutive treatment naive patients (mean age 64 years, range 41–82 years) underwent MRI-directed prostate biopsy. MRI–TRUS fusion biopsy was used for 77 (77/134 = 57.5%) patients, cognitive fusion for 51 (51/134 = 38.0%) patients, and 6 patients (6/134 = 4.5%) without a target nodule had systematic biopsy only. Out of the 1676 biopsy sites, 237 (237/1676 = 14.1%) were positive on MRI for a PIRADS 3, 4, or 5 nodule. Fifty-eight (58/134, 43.3%) patients had clinically significant prostate cancer (csPCa). The findings on MRI using PIRADS version 2 were correlated with the biopsy results.

Results

The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of PIRADS ≥ 3 for csPCa were 89%, 76.5%, 89.7%, 31.7%, and 98.4%, respectively. The detection rates of csPCa for PIRADS 3, 4, and 5 nodules were 6.1% (4/66), 33.3% (42/126), and 64.4% (29/45), respectively. MRI did not identify a nodule in 23/1676 (1.4%) biopsy sites that contained csPCa. The MRI reader, biopsy operator, method of fusion biopsy, and zonal location of prostate nodule did not significantly affect the odds of having a biopsy result positive for csPCa.

Conclusion

PIRADS ≥ 3 had high specificity and high negative predictive value for csPCa using biopsy results as the standard of reference. The presence of csPCa from a biopsy site was highly unlikely in the absence of a corresponding PIRADS ≥ 3 nodule.

Keywords

Prostate MRI PI-RADS Prostate biopsy Prostate cancer 

Notes

Author contributions

SM: Conceptualization, methodology, data acquisition/analysis, literature review, investigation, validation, writing. MEO and AT: Conceptualization, methodology, data acquisition, clinical studies, literature review, investigation, validation, writing, administration, supervision. SG, KJ, MM, and BS: Conceptualization, methodology, clinical studies, literature review, investigation, validation, writing. LZ: Methodology, literature review, literature review, investigation, data analysis, writing. HM: Conceptualization, methodology, data acquisition/analysis, literature review, investigation, writing.

Compliance with ethical standards

Funding

None.

Conflict of interest

None.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Informed consent

Waived by institutional Research Ethics Board for this retrospective study.

References

  1. 1.
    Ahmed HU, El-Shater Bosaily A, Brown LC, et al. (2017) Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 389:815–822.  https://doi.org/10.1016/S0140-6736(16)32401-1 CrossRefGoogle Scholar
  2. 2.
    De Rooij M, Hamoen EHJ, Fütterer JJ, Barentsz JO, Rovers MM (2014) Accuracy of multiparametric MRI for prostate cancer detection: a meta-analysis. Am J Roentgenol 202:343–351.  https://doi.org/10.2214/AJR.13.11046 CrossRefGoogle Scholar
  3. 3.
    Barentsz JO, Richenberg J, Clements R, et al. (2012) ESUR prostate MR guidelines 2012. Eur Radiol 22:746–757.  https://doi.org/10.1007/s00330-011-2377-y CrossRefGoogle Scholar
  4. 4.
    American College of Radiology (2015) MR prostate imaging reporting and data system version 2.0. ACR WebpageGoogle Scholar
  5. 5.
    Rosenkrantz AB, Verma S, Choyke P, et al. (2016) Prostate magnetic resonance imaging and magnetic resonance imaging targeted biopsy in patients with a prior negative biopsy: a consensus statement by AUA and SAR. J Urol 196:1613–1618.  https://doi.org/10.1016/j.juro.2016.06.079 CrossRefGoogle Scholar
  6. 6.
    Salerno J, Finelli A, Morash C, et al. (2016) Multiparametric magnetic resonance imaging for pre-treatment local staging of prostate cancer: a Cancer Care Ontario clinical practice guideline. Can Urol Assoc J 10:332.  https://doi.org/10.5489/cuaj.3823 CrossRefGoogle Scholar
  7. 7.
    Felker ER, Raman SS, Margolis DJ, et al. (2017) Risk stratification among men with prostate imaging reporting and data system version 2 category 3 transition zone lesions: is biopsy always necessary? Am J Roentgenol 209:1272–1277.  https://doi.org/10.2214/AJR.17.18008 CrossRefGoogle Scholar
  8. 8.
    Sheridan AD, Nath SK, Syed JS, et al. (2017) Risk of clinically significant prostate cancer associated with prostate imaging reporting and data system category 3 (equivocal) lesions identified on multiparametric prostate MRI. Am J Roentgenol .  https://doi.org/10.2214/AJR.17.18516 Google Scholar
  9. 9.
    Verma S, Choyke PL, Eberhardt SC, et al. (2017) The current state of MR imaging-targeted biopsy techniques for detection of prostate cancer. Radiology 285:343–356.  https://doi.org/10.1148/radiol.2017161684 CrossRefGoogle Scholar
  10. 10.
    Weinreb JC, Barentsz JO, Choyke PL, et al. (2016) PI-RADS Prostate imaging—reporting and data system: 2015, version 2. Eur Urol 69:16–40.  https://doi.org/10.1016/j.eururo.2015.08.052 CrossRefGoogle Scholar
  11. 11.
    Fedorov A, Khallaghi S, Sánchez CA, et al. (2015) Open-source image registration for MRI–TRUS fusion-guided prostate interventions. Int J Comput Assist Radiol Surg 10:925–934.  https://doi.org/10.1007/s11548-015-1180-7 CrossRefGoogle Scholar
  12. 12.
    Sparks R, Bloch BN, Feleppa E, et al. (2015) Multiattribute probabilistic prostate elastic registration (MAPPER): application to fusion of ultrasound and magnetic resonance imaging. Med Phys 42:1153–1163.  https://doi.org/10.1118/1.4905104 CrossRefGoogle Scholar
  13. 13.
    Martin PR, Cool DW, Romagnoli C, Fenster A, Ward AD (2014) Magnetic resonance imaging-targeted, 3D transrectal ultrasound-guided fusion biopsy for prostate cancer: quantifying the impact of needle delivery error on diagnosis. Med Phys 41:73504.  https://doi.org/10.1118/1.4883838 CrossRefGoogle Scholar
  14. 14.
    Purysko AS, Bittencourt LK, Bullen JA, et al. (2017) Accuracy and interobserver agreement for prostate imaging reporting and data system, version 2, for the characterization of lesions identified on multiparametric MRI of the prostate. Am J Roentgenol 2:1–7.  https://doi.org/10.2214/AJR.16.17289 Google Scholar
  15. 15.
    Zhao C, Gao G, Fang D, et al. (2016) The efficiency of multiparametric magnetic resonance imaging (mpMRI) using PI-RADS version 2 in the diagnosis of clinically significant prostate cancer. Clin Imaging 40:885–888.  https://doi.org/10.1016/j.clinimag.2016.04.010 CrossRefGoogle Scholar
  16. 16.
    Mertan FV, Greer MD, Shih JH, et al. (2016) Prospective evaluation of the prostate imaging reporting and data system version 2 for prostate cancer detection. J Urol 196:690–696.  https://doi.org/10.1016/j.juro.2016.04.057 CrossRefGoogle Scholar
  17. 17.
    Kim SH, Choi MS, Kim MJ, Kim YH, Cho SH (2017) Validation of prostate imaging reporting and data system version 2 using an MRI–ultrasound fusion biopsy in prostate cancer diagnosis. Am J Roentgenol 209:800–805.  https://doi.org/10.2214/AJR.16.17629 CrossRefGoogle Scholar
  18. 18.
    Liddell H, Jyoti R, Haxhimolla HZ (2014) Mp-MRI prostate characterised pirads 3 lesions are associated with a low risk of clinically significant prostate cancer-a retrospective review of 92 biopsied pirads 3 lesions. Curr Urol 8:96–100.  https://doi.org/10.1159/000365697 CrossRefGoogle Scholar
  19. 19.
    Baldisserotto M, Neto EJD, Carvalhal G, et al. (2016) Validation of PI-RADS v. 2 for prostate cancer diagnosis with MRI at 3T using an external phased-array coil. J Magn Reson Imaging 44:1354–1359.  https://doi.org/10.1002/jmri.25284 CrossRefGoogle Scholar
  20. 20.
    Rosenkrantz AB, Ginocchio LA, Cornfeld D, et al. (2016) Interobserver reproducibility of the PI-RADS version 2 Lexicon: a multicenter study of six experienced prostate radiologists. Radiology 280:793–804.  https://doi.org/10.1148/radiol.2016152542 CrossRefGoogle Scholar
  21. 21.
    Woo S, Suh CH, Kim SY, Cho JY, Kim SH (2017) Diagnostic performance of prostate imaging reporting and data system version 2 for detection of prostate cancer: a systematic review and diagnostic meta-analysis. Eur Urol 72:177–188.  https://doi.org/10.1016/j.eururo.2017.01.042 CrossRefGoogle Scholar
  22. 22.
    Park SY, Jung DC, Oh YT, et al. (2016) Prostate cancer: pI-RADS version 2 helps preoperatively predict clinically significant cancers. Radiology 280:108–116.  https://doi.org/10.1148/radiol.16151133 CrossRefGoogle Scholar
  23. 23.
    Muller BG, Shih JH, Sankineni S, et al. (2015) Prostate cancer: interobserver agreement and accuracy with the revised prostate imaging reporting and data system at multiparametric MR imaging. Radiology 277:741–750.  https://doi.org/10.1148/radiol.2015142818 CrossRefGoogle Scholar
  24. 24.
    Fütterer JJ, Briganti A, De Visschere P, et al. (2015) Can clinically significant prostate cancer be detected with multiparametric magnetic resonance imaging? A systematic review of the literature. Eur Urol 68:1045–1053.  https://doi.org/10.1016/j.eururo.2015.01.013 CrossRefGoogle Scholar
  25. 25.
    Wysock JS, Rosenkrantz AB, Huang WC, et al. (2014) A prospective, blinded comparison of magnetic resonance (MR) imaging-ultrasound fusion and visual estimation in the performance of MR-targeted prostate biopsy: the profus trial. Eur Urol 66:343–351.  https://doi.org/10.1016/j.eururo.2013.10.048 CrossRefGoogle Scholar
  26. 26.
    Puech P, Rouvière O, Renard-Penna R (2013) Prostate cancer diagnosis: multiparametric MR-targeted biopsy with cognitive and transrectal US–MR fusion guidance versus systematic biopsy. Radiology 268:461–469.  https://doi.org/10.1148/radiol.13121501/-/DC1 CrossRefGoogle Scholar
  27. 27.
    Cool DW, Zhang X, Romagnoli C, et al. (2015) Evaluation of MRI–TRUS fusion versus cognitive registration accuracy for MRI-targeted, TRUS-guided prostate biopsy. Am J Roentgenol 204:83–91.  https://doi.org/10.2214/AJR.14.12681 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Joint Department of Medical Imaging, Toronto General HospitalUniversity of TorontoTorontoCanada
  2. 2.Joint Department of Medical Imaging, Princess Margaret HospitalUniversity of TorontoTorontoCanada
  3. 3.Joint Department of Medical Imaging, Mount Sinai HospitalUniversity of TorontoTorontoCanada
  4. 4.Division of Biostatistics, Dalla Lana School of Public HealthUniversity of TorontoTorontoCanada

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