1932
0

Annual Review of Medicine

Volume 70, 2019

Prostate Magnetic Resonance Imaging: Lesion Detection and Local Staging

Abstract

Dramatic changes in the use of prostate magnetic resonance imaging (MRI) have occurred in the last decade. The recognition that MRI detects and localizes cancers with reasonable accuracy led to the development of directed biopsies. These image-guided biopsies have a higher sensitivity for clinically significant cancers and a lower sensitivity for indolent disease. Prospective trials provide level 1 evidence supporting the use of prostate MRI. For local staging, while the specificity of prostate MRI is high, its sensitivity is lacking for microscopic extraprostatic extension. Computer-aided diagnosis of prostate MRI promises to bring the diagnostic power of MRI to nonexpert readers and thus further integrate MRI into the diagnostic workup.

Keyword(s): computer-aided diagnosis, diagnosis, magnetic resonance imaging, prostate cancer, staging
Loading

Article metrics loading...

/content/journals/10.1146/annurev-med-053117-123215
2019-01-27
2025-06-16
Loading full text...

Full text loading...

/deliver/fulltext/med/70/1/annurev-med-053117-123215.html?itemId=/content/journals/10.1146/annurev-med-053117-123215&mimeType=html&fmt=ahah

Literature Cited

  1. 1.  Siegel RL, Miller KD, Jemal A 2018. Cancer statistics, 2018. CA: Cancer J. Clin. 68:17–30
     [Google Scholar]
  2. 2.  de Koning HJ, Gulati R, Moss SM et al. 2018. The efficacy of prostate-specific antigen screening: impact of key components in the ERSPC and PLCO trials. Cancer 124:61197–206
     [Google Scholar]
  3. 3.  Schroder FH, Hugosson J, Roobol MJ et al. 2009. Screening and prostate-cancer mortality in a randomized European study. N. Engl. J. Med. 360:131320–28
     [Google Scholar]
  4. 4.  Hricak H, Choyke PL, Eberhardt SC et al. 2007. Imaging prostate cancer: a multidisciplinary perspective. Radiology 243:128–53
     [Google Scholar]
  5. 5.  Turkbey B, Mani H, Shah V et al. 2011. Multiparametric 3T prostate magnetic resonance imaging to detect cancer: histopathological correlation using prostatectomy specimens processed in customized magnetic resonance imaging based molds. J. Urol. 186:51818–24
     [Google Scholar]
  6. 6.  Turkbey B, Pinto PA, Mani H et al. 2010. Prostate cancer: value of multiparametric MR imaging at 3 T for detection—histopathologic correlation. Radiology 255:189–99
     [Google Scholar]
  7. 7.  Siddiqui MM, Rais-Bahrami S, Turkbey B et al. 2015. Comparison of MR/ultrasound fusion-guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer. JAMA 313:4390–97
     [Google Scholar]
  8. 8.  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. 66:2343–51
     [Google Scholar]
  9. 9.  Sonn GA, Natarajan S, Margolis DJ et al. 2013. Targeted biopsy in the detection of prostate cancer using an office based magnetic resonance ultrasound fusion device. J. Urol. 189:186–91
     [Google Scholar]
  10. 10.  Rosenkrantz AB, Deng FM, Kim S et al. 2012. Prostate cancer: multiparametric MRI for index lesion localization—a multiple-reader study. Am. J. Roentgenol. 199:4830–37
     [Google Scholar]
  11. 11.  Hambrock T, Somford DM, Hoeks C et al. 2010. Magnetic resonance imaging guided prostate biopsy in men with repeat negative biopsies and increased prostate specific antigen. J. Urol. 183:2520–27
     [Google Scholar]
  12. 12.  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. 196:61613–18
     [Google Scholar]
  13. 13.  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 389:10071815–22
     [Google Scholar]
  14. 14.  Kasivisvanathan V, Rannikko AS, Borghi M et al. 2018. MRI-targeted or standard biopsy for prostate-cancer diagnosis. N. Engl. J. Med. 378:1767–77
     [Google Scholar]
  15. 15.  Weinreb JC, Barentsz JO, Choyke PL et al. 2016. PI-RADS prostate imaging–reporting and data system: 2015, version 2. Eur. Urol. 69:116–40
     [Google Scholar]
  16. 16.  Spilseth B, Ghai S, Patel NU et al. 2018. A comparison of radiologists’ and urologists’ opinions regarding prostate MRI reporting: results from a survey of specialty societies. Am. J. Roentgenol. 210:101–7
     [Google Scholar]
  17. 17.  Mehralivand S, Shih JH, Rais-Bahrami S et al. 2018. A magnetic resonance imaging-based prediction model for prostate biopsy risk stratification. JAMA Oncology 4:678–85
     [Google Scholar]
  18. 18.  Zhang L, Tang M, Chen S et al. 2017. A meta-analysis of use of Prostate Imaging Reporting and Data System Version 2 (PI-RADS V2) with multiparametric MR imaging for the detection of prostate cancer. Eur. Radiol. 27:125204–14
     [Google Scholar]
  19. 19.  Greer MD, Brown AM, Shih JH et al. 2017. Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: a multireader study. J. Magn. Reson. Imag. 45:2579–85
     [Google Scholar]
  20. 20.  Greer MD, Shih JH, Barrett T et al. 2018. All over the map: an interobserver agreement study of tumor location based on the PI-RADSv2 sector map. J. Magn. Reson. Imag 48:2482–90
     [Google Scholar]
  21. 21.  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 280:3793–804
     [Google Scholar]
  22. 22.  Rosenkrantz AB, Babb JS, Taneja SS et al. 2017. Proposed adjustments to PI-RADS version 2 decision rules: impact on prostate cancer detection. Radiology 283:1119–29
     [Google Scholar]
  23. 23.  Rosenkrantz AB, Oto A, Turkbey B et al. 2016. Prostate Imaging Reporting and Data System (PI-RADS), Version 2: a critical look. Am. J. Roentgenol. 206:61179–83
     [Google Scholar]
  24. 24.  Borofsky S, George AK, Gaur S et al. 2017. What are we missing? False-negative cancers at multiparametric MR imaging of the prostate. Radiology 286:186–95
     [Google Scholar]
  25. 25.  Truong M, Hollenberg G, Weinberg E et al. 2017. Impact of Gleason subtype on prostate cancer detection using multiparametric magnetic resonance imaging: correlation with final histopathology. J. Urol. 198:2316–21
     [Google Scholar]
  26. 26.  Wang S, Burtt K, Turkbey B et al. 2014. Computer-aided diagnosis of prostate cancer on multiparametric MRI: a technical review of current research. BioMed. Res. Int. 2014:789561
     [Google Scholar]
  27. 27.  Greer MD, Lay N, Shih JH et al. 2018. Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study. Eur. Radiol. 28:104407–17
     [Google Scholar]
  28. 28.  Ravery V, Boccon-Gibod L 1997. T3 prostate cancer: How reliable is clinical staging?. Semin. Urol. Oncol. 15:4202–6
     [Google Scholar]
  29. 29.  Eifler JB, Feng Z, Lin BM et al. 2013. An updated prostate cancer staging nomogram (Partin tables) based on cases from 2006 to 2011. BJU Int 111:122–29
     [Google Scholar]
  30. 30.  Yu KK, Hricak H, Alagappan R et al. 1997. Detection of extracapsular extension of prostate carcinoma with endorectal and phased-array coil MR imaging: multivariate feature analysis. Radiology 202:3697–702
     [Google Scholar]
  31. 31.  Hricak H, Dooms GC, Jeffrey RB et al. 1987. Prostatic carcinoma: staging by clinical assessment, CT, and MR imaging. Radiology 162:2331–36
     [Google Scholar]
  32. 32.  Costa DN, Passoni NM, Leyendecker JR et al. 2018. Diagnostic utility of a Likert scale versus qualitative descriptors and length of capsular contact for determining extraprostatic tumor extension at multiparametric prostate MRI. Am. J. Roentgenol. 210:51066–72
     [Google Scholar]
  33. 33.  Baco E, Rud E, Vlatkovic L et al. 2015. Predictive value of magnetic resonance imaging determined tumor contact length for extracapsular extension of prostate cancer. J. Urol. 193:2466–72
     [Google Scholar]
  34. 34.  Kongnyuy M, Sidana A, George AK et al. 2017. Tumor contact with prostate capsule on magnetic resonance imaging: a potential biomarker for staging and prognosis. Urol. Oncol. 35:130.e1–8
     [Google Scholar]
  35. 35.  Rosenkrantz AB, Shanbhogue AK, Wang A et al. 2016. Length of capsular contact for diagnosing extraprostatic extension on prostate MRI: assessment at an optimal threshold. J. Magn. Reson. Imag. 43:4990–97
     [Google Scholar]
  36. 36.  Raskolnikov D, George AK, Rais-Bahrami S et al. 2014. Multiparametric magnetic resonance imaging and image-guided biopsy to detect seminal vesicle invasion by prostate cancer. J. Endourol. 28:111283–89
     [Google Scholar]
  37. 37.  de Rooij M, Hamoen EH, Witjes JA et al. 2016. Accuracy of magnetic resonance imaging for local staging of prostate cancer: a diagnostic meta-analysis. Eur. Urol. 70:2233–45
     [Google Scholar]
/content/journals/10.1146/annurev-med-053117-123215
Loading
Prostate Magnetic Resonance Imaging: Lesion Detection and Local Staging
Annual Review of Medicine 70, 451 (2019); https://doi.org/10.1146/annurev-med-053117-123215
/content/journals/10.1146/annurev-med-053117-123215
/content/journals/10.1146/annurev-med-053117-123215
Loading

Data & Media loading...

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error