Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel

Published Online:https://doi.org/10.1148/radiol.2020190646

Wide variation in prostate cancer detection is seen across all Prostate Imaging Reporting and Data System scores for men with suspected or biopsy-proven untreated prostate cancer who undergo MRI.

Background

Prostate MRI is used widely in clinical care for guiding tissue sampling, active surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) helps provide a standardized probabilistic approach for identifying clinically significant prostate cancer. Despite widespread use, the variability in performance of prostate MRI across practices remains unknown.

Purpose

To estimate the positive predictive value (PPV) of PI-RADS for the detection of high-grade prostate cancer across imaging centers.

Materials and Methods

This retrospective cross-sectional study was compliant with the HIPAA. Twenty-six centers with members in the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel submitted data from men with suspected or biopsy-proven untreated prostate cancer. MRI scans were obtained between January 2015 and April 2018. This was followed with targeted biopsy. Only men with at least one MRI lesion assigned a PI-RADS score of 2–5 were included. Outcome was prostate cancer with Gleason score (GS) greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2). A mixed-model logistic regression with institution and individuals as random effects was used to estimate overall PPVs. The variability of observed PPV of PI-RADS across imaging centers was described by using the median and interquartile range.

Results

The authors evaluated 3449 men (mean age, 65 years ± 8 [standard deviation]) with 5082 lesions. Biopsy results showed 1698 cancers with GS greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2) in 2082 men. Across all centers, the estimated PPV was 35% (95% confidence interval [CI]: 27%, 43%) for a PI-RADS score greater than or equal to 3 and 49% (95% CI: 40%, 58%) for a PI-RADS score greater than or equal to 4. The interquartile ranges of PPV at these same PI-RADS score thresholds were 27%–44% and 27%–48%, respectively.

Conclusion

The positive predictive value of the Prostate Imaging and Reporting Data System was low and varied widely across centers.

© RSNA, 2020

Online supplemental material is available for this article.

See also the editorial by Milot in this issue.

References

  • 1. Kasivisvanathan V, Rannikko AS, Borghi M, et al. MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis. N Engl J Med 2018;378(19):1767–1777.
  • 2. Rosenkrantz AB, Verma S, Choyke P, et al. 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 2016;196(6):1613–1618.
  • 3. Mottet N, Bellmunt J, Briers E, et al. EAU–ESTRO–ESUR–SIOG Guidelines on Prostate Cancer. https://uroweb.org/guideline/prostate-cancer. Published 2019. Accessed June 24, 2019.
  • 4. Rosenkrantz AB, Hemingway J, Hughes DR, Duszak R Jr, Allen B Jr, Weinreb JC. Evolving Use of Prebiopsy Prostate Magnetic Resonance Imaging in the Medicare Population. J Urol 2018;200(1):89–94.
  • 5. Weinreb JC, Barentsz JO, Choyke PL, et al. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol 2016;69(1):16–40.
  • 6. Patel NU, Lind KE, Garg K, Crawford D, Werahera PN, Pokharel SS. Assessment of PI-RADS v2 categories ≥ 3 for diagnosis of clinically significant prostate cancer. Abdom Radiol (NY) 2019;44(2):705–712.
  • 7. Lin WC, Westphalen AC, Silva GE, Chodraui Filho S, Reis RB, Muglia VF. Comparison of PI-RADS 2, ADC histogram-derived parameters, and their combination for the diagnosis of peripheral zone prostate cancer. Abdom Radiol (NY) 2016;41(11):2209–2217 [Published correction appears in Abdom Radiol (NY) 2017;42(5):1619.] https://doi.org/10.1007/s00261-016-0826-4.
  • 8. Mertan FV, Greer MD, Shih JH, et al. Prospective Evaluation of the Prostate Imaging Reporting and Data System Version 2 for Prostate Cancer Detection. J Urol 2016;196(3):690–696.
  • 9. Esses SJ, Taneja SS, Rosenkrantz AB. Imaging Facilities’ Adherence to PI-RADS v2 Minimum Technical Standards for the Performance of Prostate MRI. Acad Radiol 2018;25(2):188–195.
  • 10. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42(2):377–381.
  • 11. Barkovich EJ, Shankar PR, Westphalen AC. A Systematic Review of the Existing Prostate Imaging Reporting and Data System Version 2 (PI-RADSv2) Literature and Subset Meta-Analysis of PI-RADSv2 Categories Stratified by Gleason Scores. AJR Am J Roentgenol 2019;212(4):847–854.
  • 12. Rosenkrantz AB, Ginocchio LA, Cornfeld D, et al. Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists. Radiology 2016;280(3):793–804.
  • 13. Porpiglia F, DE Luca S, Checcucci E, et al. Comparing Image-guided targeted Biopsies to Radical Prostatectomy Specimens for Accurate Characterization of the Index Tumor in Prostate Cancer. Anticancer Res 2018;38(5):3043–3047.
  • 14. Oto A, Kayhan A, Jiang Y, et al. Prostate cancer: Differentiation of central gland cancer from benign prostatic hyperplasia by using diffusion-weighted and dynamic contrast-enhanced MR imaging. Radiology 2010;257(3):715–723.
  • 15. Schiebler ML, Tomaszewski JE, Bezzi M, et al. Prostatic carcinoma and benign prostatic hyperplasia: correlation of high-resolution MR and histopathologic findings. Radiology 1989;172(1):131–137.
  • 16. Kitzing YX, Prando A, Varol C, Karczmar GS, Maclean F, Oto A. Benign Conditions That Mimic Prostate Carcinoma: MR Imaging Features with Histopathologic Correlation. RadioGraphics 2016;36(1):162–175.
  • 17. Fulgham PF, Rukstalis DB, Turkbey IB, et al. AUA Policy Statement on the Use of Multiparametric Magnetic Resonance Imaging in the Diagnosis, Staging and Management of Prostate Cancer. J Urol 2017;198(4):832–838.
  • 18. Muthigi A, George AK, Sidana A, et al. Missing the Mark: Prostate Cancer Upgrading by Systematic Biopsy over Magnetic Resonance Imaging/Transrectal Ultrasound Fusion Biopsy. J Urol 2017;197(2):327–334.
  • 19. Vargas HA, Hötker AM, Goldman DA, et al. Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: Critical evaluation using whole-mount pathology as standard of reference. Eur Radiol 2016;26(6):1606–1612.

Article History

Received: Mar 26 2019
Revision requested: Apr 29 2019
Revision received: Jan 7 2020
Accepted: Feb 13 2020
Published online: Apr 21 2020
Published in print: July 2020