Skip to main content

Advertisement

SpringerLink
Log in

Assessment of prostate imaging reporting and data system version 2.1 false-positive category 4 and 5 lesions in clinically significant prostate cancer

  • Pelvis
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

To determine the incidence and false-positive rates of clinically significant prostate cancer (CSPC) in prostate imaging reporting and data system (PI-RADS) category 4 and 5 lesions using PI-RADS v2.1.

Methods

One hundred and eighty-two lesions in 169 subjects with a PI-RADS score of 4 or 5 were included in our study. Lesions with clinically insignificant prostate cancer (CIPC) or benign pathologic findings were reviewed and categorized by a radiologist. The initial comparison of demographic and clinical data was performed by t-test and χ2 test, and then the logistic regression model was used to determine factors associated with CIPC or benign pathological findings.

Results

Of the 182 PI-RADS category 4 and 5 lesions, 84.6% (154/182) were prostate cancer (PCa), 73.1% (133/182) were CSPC, and 26.9% (49/182) were CIPC or benign pathologic findings. The false-positive cases included 44.9% (22/49) with inflammation, 42.9% (21/49) with CIPC, 8.2% (4/49) with BPH nodules and 4.1% (2/49) with normal anatomy cases. In multivariate analysis, factors associated with CIPC or benign features included those in both the peripheral zone (PZ) and central gland (CG) (odds ratio [OR] 0.062; p = 0.003) and a low prostate-specific antigen density (PSAD) (OR 0.34; p = 0.012).

Conclusion

The integration of clinical information (PSAD and lesion location) into mpMRI to identify lesions helps with obtaining a clinically significant diagnosis and decision-making.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Abbreviations

mpMRI:

Multiparametric magnetic resonance imaging

PI-RADS:

Prostate imaging reporting and data system

PCa:

Prostate cancer

CSPC:

Clinically significant prostate cancer

CIPC:

Clinically insignificant prostate cancer

T2WI:

T2-weighted imaging

DWI:

Diffusion-weighted imaging

ADC:

Apparent diffusion coefficient

DCE:

Dynamic contrast material-enhanced

BPH:

Benign prostatic hyperplasia

PSA:

Prostate-specific antigen

PSAD:

Prostate-specific antigen density

ROC:

Receiver operating characteristic

AUC:

Area under the ROC curve

ROI:

Region of interest

PZ:

Peripheral zone

TZ:

Transition zone

CZ:

Central zone

AFMS:

Anterior fibromuscular stroma

CG:

Central gland

References

  1. Barentsz J, Richenberg J, Clements R, Choyke P, Verma S, Villeirs G, Rouviere O, Logager V, Fütterer J. ESUR prostate MR guidelines 2012. European radiology 2012;22(4):746-757. https://doi.org/10.1007/s00330-011-2377-y

    Article  PubMed  PubMed Central  Google Scholar 

  2. Weinreb J, Barentsz J, Choyke P, Cornud F, Haider M, Macura K, Margolis D, Schnall M, Shtern F, Tempany C, Thoeny H, Verma S. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. European urology 2016;69(1):16-40. https://doi.org/10.1016/j.eururo.2015.08.052

    Article  PubMed  Google Scholar 

  3. Turkbey B, Rosenkrantz A, Haider M, Padhani A, Villeirs G, Macura K, Tempany C, Choyke P, Cornud F, Margolis D, Thoeny H, Verma S, Barentsz J, Weinreb J. Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2. European urology 2019;76(3):340–351. https://doi.org/10.1016/j.eururo.2019.02.033

  4. Dugan J, Bostwick D, Myers R, Qian J, Bergstralh E, Oesterling J. The definition and preoperative prediction of clinically insignificant prostate cancer. JAMA 1996;275(4):288-294. https://doi.org/10.1001/jama.275.4.288

    Article  CAS  PubMed  Google Scholar 

  5. Chamie K, Sonn G, Finley D, Tan N, Margolis D, Raman S, Natarajan S, Huang J, Reiter R. The role of magnetic resonance imaging in delineating clinically significant prostate cancer. Urology 2014;83(2):369-375. https://doi.org/10.1016/j.urology.2013.09.045

    Article  PubMed  Google Scholar 

  6. Loffroy R, Chevallier O, Moulin M, Favelier S, Genson P, Pottecher P, Crehange G, Cochet A, Cormier L. Current role of multiparametric magnetic resonance imaging for prostate cancer. Quantitative imaging in medicine and surgery 2015;5(5):754-764. https://doi.org/10.3978/j.issn.2223-4292.2015.10.08

    Article  PubMed  PubMed Central  Google Scholar 

  7. Greer M, Brown A, Shih J, Summers R, Marko J, Law Y, Sankineni S, George A, Merino M, Pinto P, Choyke P, Turkbey B. Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: A multireader study. Journal of magnetic resonance imaging : JMRI 2017;45(2):579-585. https://doi.org/10.1002/jmri.25372

    Article  PubMed  Google Scholar 

  8. Ahmed H, El-Shater Bosaily A, Brown L, Gabe R, Kaplan R, Parmar M, Collaco-Moraes Y, Ward K, Hindley R, Freeman A, Kirkham A, Oldroyd R, Parker C, Emberton M. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet (London, England) 2017;389(10071):815-822. https://doi.org/10.1016/s0140-6736(16)32401-1

    Article  Google Scholar 

  9. Mehralivand S, Bednarova S, Shih J, Mertan F, Gaur S, Merino M, Wood B, Pinto P, Choyke P, Turkbey B. Prospective Evaluation of PI-RADS™ Version 2 Using the International Society of Urological Pathology Prostate Cancer Grade Group System. The Journal of urology 2017;198(3):583-590. https://doi.org/10.1016/j.juro.2017.03.131

    Article  PubMed  PubMed Central  Google Scholar 

  10. Tan N, Lin W, Khoshnoodi P, Asvadi N, Yoshida J, Margolis D, Lu D, Wu H, Sung K, Lu D, Huang J, Raman S. In-Bore 3-T MR-guided Transrectal Targeted Prostate Biopsy: Prostate Imaging Reporting and Data System Version 2-based Diagnostic Performance for Detection of Prostate Cancer. Radiology 2017;283(1):130-139. https://doi.org/10.1148/radiol.2016152827

    Article  PubMed  Google Scholar 

  11. Rosenkrantz A, Taneja S. Radiologist, be aware: ten pitfalls that confound the interpretation of multiparametric prostate MRI. AJR American journal of roentgenology 2014;202(1):109-120. https://doi.org/10.2214/ajr.13.10699

    Article  PubMed  Google Scholar 

  12. Noworolski S, Vigneron D, Chen A, Kurhanewicz J. Dynamic contrast-enhanced MRI and MR diffusion imaging to distinguish between glandular and stromal prostatic tissues. Magnetic resonance imaging 2008;26(8):1071-1080. https://doi.org/10.1016/j.mri.2008.01.033

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bour L, Schull A, Delongchamps N, Beuvon F, Muradyan N, Legmann P, Cornud F. Multiparametric MRI features of granulomatous prostatitis and tubercular prostate abscess. Diagnostic and interventional imaging 2013;94(1):84-90. https://doi.org/10.1016/j.diii.2012.09.001

    Article  CAS  PubMed  Google Scholar 

  14. Distler F, Radtke J, Bonekamp D, Kesch C, Schlemmer H, Wieczorek K, Kirchner M, Pahernik S, Hohenfellner M, Hadaschik B. The Value of PSA Density in Combination with PI-RADS™ for the Accuracy of Prostate Cancer Prediction. The Journal of urology 2017;198(3):575-582. https://doi.org/10.1016/j.juro.2017.03.130

    Article  PubMed  Google Scholar 

  15. Radtke J, Wiesenfarth M, Kesch C, Freitag M, Alt C, Celik K, Distler F, Roth W, Wieczorek K, Stock C, Duensing S, Roethke M, Teber D, Schlemmer H, Hohenfellner M, Bonekamp D, Hadaschik B. Combined Clinical Parameters and Multiparametric Magnetic Resonance Imaging for Advanced Risk Modeling of Prostate Cancer-Patient-tailored Risk Stratification Can Reduce Unnecessary Biopsies. European urology 2017;72(6):888-896. https://doi.org/10.1016/j.eururo.2017.03.039

    Article  PubMed  Google Scholar 

  16. Washino S, Okochi T, Saito K, Konishi T, Hirai M, Kobayashi Y, Miyagawa T. Combination of prostate imaging reporting and data system (PI-RADS) score and prostate-specific antigen (PSA) density predicts biopsy outcome in prostate biopsy naïve patients. BJU international 2017;119(2):225-233. https://doi.org/10.1111/bju.13465

    Article  CAS  PubMed  Google Scholar 

  17. StataCorp. Stata Statistical Software: Release 15. College Station, TX: StataCorp LLC. 2017

  18. Akin OThai J, Narayanan H, George A, Siddiqui M, Shah P, Mertan F, Merino M, Pinto P, Choyke P, Wood B, Turkbey B. Validation of PI-RADS Version 2 in Transition Zone Lesions for the Detection of Prostate Cancer. Radiology 2018;288(2):485-491. https://doi.org/10.1148/radiol.2018170425

    Article  Google Scholar 

  19. Truong M, Wang B, Gordetsky J, Nix J, Frye T, Messing E, Thomas J, Feng C, Rais-Bahrami S. Multi-institutional nomogram predicting benign prostate pathology on magnetic resonance/ultrasound fusion biopsy in men with a prior negative 12-core systematic biopsy. Cancer 2018;124(2):278-285. https://doi.org/10.1002/cncr.31051

    Article  PubMed  Google Scholar 

  20. Sheridan A, Nath S, Aneja S, Syed J, Pahade J, Mathur M, Sprenkle P, Weinreb J, Spektor M. MRI-Ultrasound Fusion Targeted Biopsy of Prostate Imaging Reporting and Data System Version 2 Category 5 Lesions Found False-Positive at Multiparametric Prostate MRI. AJR American journal of roentgenology 2018;210(5):W218-W225. https://doi.org/10.2214/ajr.17.18680

    Article  PubMed  Google Scholar 

  21. Rais-Bahrami S, Nix J, Turkbey B, Pietryga J, Sanyal R, Thomas J, Gordetsky J. Clinical and multiparametric MRI signatures of granulomatous prostatitis. Abdominal radiology (New York) 2017;42(7):1956-1962. https://doi.org/10.1007/s00261-017-1080-0

    Article  Google Scholar 

  22. Nagel K, Schouten M, Hambrock T, Litjens G, Hoeks C, ten Haken B, Barentsz J, Fütterer J. Differentiation of prostatitis and prostate cancer by using diffusion-weighted MR imaging and MR-guided biopsy at 3 T. Radiology 2013;267(1):164-172. https://doi.org/10.1148/radiol.12111683

    Article  PubMed  Google Scholar 

  23. Esen M, Onur M, Akpolat N, Orhan I, Kocakoc E. Utility of ADC measurement on diffusion-weighted MRI in differentiation of prostate cancer, normal prostate and prostatitis. Quantitative imaging in medicine and surgery 2013;3(4):210-216. https://doi.org/10.3978/j.issn.2223-4292.2013.08.06

    Article  PubMed  PubMed Central  Google Scholar 

  24. Akin O, Sala E, Moskowitz C, Kuroiwa K, Ishill N, Pucar D, Scardino P, Hricak H. Transition zone prostate cancers: features, detection, localization, and staging at endorectal MR imaging. Radiology 2006;239(3):784-792. https://doi.org/10.1148/radiol.2392050949

    Article  PubMed  Google Scholar 

  25. Gordetsky J, Ullman D, Schultz L, Porter K, Del Carmen Rodriguez Pena M, Calderone C, Nix J, Ullman M, Bae S, Rais-Bahrami S. Histologic findings associated with false-positive multiparametric magnetic resonance imaging performed for prostate cancer detection. Human pathology 2019;83:159–165. https://doi.org/10.1016/j.humpath.2018.08.021

Download references

Funding

Clinical Research Project of Shenzhen Second Peoples’ Hospital (20193357008).

Author information

Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, 3002 SunGangXi Road, Shenzhen, 518035, China

    Xiangyu Wang, Yi Lei & Fan Lin

  2. Department of Ultrasonography, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, 3002 SunGangXi Road, Shenzhen, 518035, China

    Weizong Liu

  3. Department of Radiology, Shenzhen University General Hospital, 1098 XueYuan Road, Shenzhen, 518055, China

    Guangyao Wu

Authors
  1. Xiangyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Weizong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yi Lei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guangyao Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fan Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Guangyao Wu or Fan Lin.

Ethics declarations

Conflict of interest

The authors declare there are no conflicts of interest regarding the publication of this paper.

Ethical approval

This retrospective study was approved by our institutional review board, and the requirement for written informed consent for all patients was waived.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, X., Liu, W., Lei, Y. et al. Assessment of prostate imaging reporting and data system version 2.1 false-positive category 4 and 5 lesions in clinically significant prostate cancer. Abdom Radiol 46, 3410–3417 (2021). https://doi.org/10.1007/s00261-021-03023-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-021-03023-w

Keywords

Search

Navigation