Cancer detection rates of the PI-RADSv2.1 assessment categories: systematic review and meta-analysis on lesion level and patient level.


Journal

Prostate cancer and prostatic diseases
ISSN: 1476-5608
Titre abrégé: Prostate Cancer Prostatic Dis
Pays: England
ID NLM: 9815755

Informations de publication

Date de publication:
02 2022
Historique:
received: 05 03 2021
accepted: 22 06 2021
revised: 05 06 2021
pubmed: 8 7 2021
medline: 14 6 2022
entrez: 7 7 2021
Statut: ppublish

Résumé

The Prostate Imaging Reporting and Data System, version 2.1 (PI-RADSv2.1) standardizes reporting of multiparametric MRI of the prostate. Assigned assessment categories are a risk stratification algorithm, higher categories indicate a higher probability of clinically significant cancer compared to lower categories. PI-RADSv2.1 does not define these probabilities numerically. We conduct a systematic review and meta-analysis to determine the cancer detection rates (CDR) of the PI-RADSv2.1 assessment categories on lesion level and patient level. Two independent reviewers screen a systematic PubMed and Cochrane CENTRAL search for relevant articles (primary outcome: clinically significant cancer, index test: prostate MRI reading according to PI-RADSv2.1, reference standard: histopathology). We perform meta-analyses of proportions with random-effects models for the CDR of the PI-RADSv2.1 assessment categories for clinically significant cancer. We perform subgroup analysis according to lesion localization to test for differences of CDR between peripheral zone lesions and transition zone lesions. A total of 17 articles meet the inclusion criteria and data is independently extracted by two reviewers. Lesion level analysis includes 1946 lesions, patient level analysis includes 1268 patients. On lesion level analysis, CDR are 2% (95% confidence interval: 0-8%) for PI-RADS 1, 4% (1-9%) for PI-RADS 2, 20% (13-27%) for PI-RADS 3, 52% (43-61%) for PI-RADS 4, 89% (76-97%) for PI-RADS 5. On patient level analysis, CDR are 6% (0-20%) for PI-RADS 1, 9% (5-13%) for PI-RADS 2, 16% (7-27%) for PI-RADS 3, 59% (39-78%) for PI-RADS 4, 85% (73-94%) for PI-RADS 5. Higher categories are significantly associated with higher CDR (P < 0.001, univariate meta-regression), no systematic difference of CDR between peripheral zone lesions and transition zone lesions is identified in subgroup analysis. Our estimates of CDR demonstrate that PI-RADSv2.1 stratifies lesions and patients as intended. Our results might serve as an initial evidence base to discuss management strategies linked to assessment categories.

Sections du résumé

BACKGROUND
The Prostate Imaging Reporting and Data System, version 2.1 (PI-RADSv2.1) standardizes reporting of multiparametric MRI of the prostate. Assigned assessment categories are a risk stratification algorithm, higher categories indicate a higher probability of clinically significant cancer compared to lower categories. PI-RADSv2.1 does not define these probabilities numerically. We conduct a systematic review and meta-analysis to determine the cancer detection rates (CDR) of the PI-RADSv2.1 assessment categories on lesion level and patient level.
METHODS
Two independent reviewers screen a systematic PubMed and Cochrane CENTRAL search for relevant articles (primary outcome: clinically significant cancer, index test: prostate MRI reading according to PI-RADSv2.1, reference standard: histopathology). We perform meta-analyses of proportions with random-effects models for the CDR of the PI-RADSv2.1 assessment categories for clinically significant cancer. We perform subgroup analysis according to lesion localization to test for differences of CDR between peripheral zone lesions and transition zone lesions.
RESULTS
A total of 17 articles meet the inclusion criteria and data is independently extracted by two reviewers. Lesion level analysis includes 1946 lesions, patient level analysis includes 1268 patients. On lesion level analysis, CDR are 2% (95% confidence interval: 0-8%) for PI-RADS 1, 4% (1-9%) for PI-RADS 2, 20% (13-27%) for PI-RADS 3, 52% (43-61%) for PI-RADS 4, 89% (76-97%) for PI-RADS 5. On patient level analysis, CDR are 6% (0-20%) for PI-RADS 1, 9% (5-13%) for PI-RADS 2, 16% (7-27%) for PI-RADS 3, 59% (39-78%) for PI-RADS 4, 85% (73-94%) for PI-RADS 5. Higher categories are significantly associated with higher CDR (P < 0.001, univariate meta-regression), no systematic difference of CDR between peripheral zone lesions and transition zone lesions is identified in subgroup analysis.
CONCLUSIONS
Our estimates of CDR demonstrate that PI-RADSv2.1 stratifies lesions and patients as intended. Our results might serve as an initial evidence base to discuss management strategies linked to assessment categories.

Identifiants

pubmed: 34230616
doi: 10.1038/s41391-021-00417-1
pii: 10.1038/s41391-021-00417-1
pmc: PMC9184264
doi:

Types de publication

Journal Article Meta-Analysis Systematic Review Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

256-263

Informations de copyright

© 2021. The Author(s).

Références

Padhani AR, Barentsz J, Villeirs G, Rosenkrantz AB, Margolis DJ, Turkbey B, et al. PI-RADS steering committee: the PI-RADS multiparametric MRI and MRI-directed biopsy pathway. Radiol Soc North Am. 2019;292:464–74.
Sklinda K, Mruk B, Walecki J. Active surveillance of prostate cancer using multiparametric magnetic resonance imaging: a review of the current role and future perspectives. Med Sci Monit. 2020;26:e920252-1–9.
Gaur S, Turkbey B. Prostate MRI for post-treatment evaluation and recurrence. Radio Clin North Am. 2018;56:263–75.
doi: 10.1016/j.rcl.2017.10.008
Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, et al. Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. Eur Urol. 2019;76:340–51.
doi: 10.1016/j.eururo.2019.02.033
PI-RADS. Prostate imaging reporting and data system version 2.1. American College of Radiology; 2019.
Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, et al. PI-RADS prostate imaging - reporting and data system: 2015, Version 2. Eur Urol. 2016;69:16–40.
doi: 10.1016/j.eururo.2015.08.052
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;212:847–54.
doi: 10.2214/AJR.18.20571
Mazzone E, Stabile A, Pellegrino F, Basile G, Cignoli D, Cirulli GO, et al. Positive predictive value of prostate imaging reporting and data system version 2 for the detection of clinically significant prostate cancer: a systematic review and meta-analysis. Eur Urol Oncol. 2020;S2588-9311(20)30212-1.
Sickles E, D’Orsi C, Bassett L. ACR BI-RADS
Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ [Internet]. 2009 [cited 2020 Oct 30];339. Available from: https://www.bmj.com/content/339/bmj.b2700 .
PRISMA [Internet]. [cited 2021 Feb 14]. Available from: http://prisma-statement.org/prismastatement/flowdiagram.aspx .
Whiting PF, Rutjes AWS, Westwood ME, Mallett S, Deeks JJ, Reitsma JB, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529–36.
doi: 10.7326/0003-4819-155-8-201110180-00009
Barendregt JJ, Doi SA, Lee YY, Norman RE, Vos T. Meta-analysis of prevalence. J Epidemiol Community Health. 2013;67:974–8.
doi: 10.1136/jech-2013-203104
Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–60.
doi: 10.1136/bmj.327.7414.557
Sox HC. Probability theory in the use of diagnostic tests. An introduction to critical study of the literature. Ann Intern Med. 1986;104:60–6.
doi: 10.7326/0003-4819-104-1-60
Kim KW, Lee J, Choi SH, Huh J, Park SH. Systematic review and meta-analysis of studies evaluating diagnostic test accuracy: a practical review for clinical researchers-Part I. General guidance and tips. Korean J Radio. 2015;16:1175–87.
doi: 10.3348/kjr.2015.16.6.1175
Hunter JP, Saratzis A, Sutton AJ, Boucher RH, Sayers RD, Bown MJ. In meta-analyses of proportion studies, funnel plots were found to be an inaccurate method of assessing publication bias. J Clin Epidemiol. 2014;67:897–903.
doi: 10.1016/j.jclinepi.2014.03.003
10.4.3.1 Recommendations on testing for funnel plot asymmetry [Internet]. [cited 2021 Feb 9]. Available from: https://handbook-5-1.cochrane.org/chapter_10/10_4_3_1_recommendations_on_testing_for_funnel_plot_asymmetry.htm .
Bao J, Zhi R, Hou Y, Zhang J, Wu C-J, Wang X-M, et al. Optimized MRI assessment for clinically significant prostate cancer: A STARD-Compliant Two-Center Study. J Magn Reson Imaging. 2020;53:1210–9.
Brancato V, Di Costanzo G, Basso L, Tramontano L, Puglia M, Ragozzino A, et al. Assessment of DCE utility for PCa diagnosis using PI-RADS v2.1: effects on diagnostic accuracy and reproducibility. Diagnostics (Basel). 2020;10:164.
doi: 10.3390/diagnostics10030164
Byun J, Park KJ, Kim M-H, Kim JK. Direct comparison of PI-RADS version 2 and 2.1 in transition zone lesions for detection of prostate cancer: preliminary experience. J Magn Reson Imaging. 2020;52:577–86.
doi: 10.1002/jmri.27080
Costa DN, Jia L, Subramanian N, Xi Y, Rofsky NM, Recchimuzzi DZ, et al. Prospectively-reported PI-RADS version 2.1 atypical benign prostatic hyperplasia nodules with marked restricted diffusion (“2+1” Transition Zone Lesions): clinically significant prostate cancer detection rates on multiparametric MRI. AJR Am J Roentgenol. 2020.
Falagario UG, Jambor I, Lantz A, Ettala O, Stabile A, Taimen P, et al. Combined use of prostate-specific antigen density and magnetic resonance imaging for prostate biopsy decision planning: a retrospective multi-institutional study using the prostate magnetic resonance imaging outcome database (PROMOD). Eur Urol Oncol. 2020;S2588-9311:30142–5.
Gorin MA, Meyer AR, Zimmerman M, Harb R, Joice GA, Schwen ZR, et al. Transperineal prostate biopsy with cognitive magnetic resonance imaging/biplanar ultrasound fusion: description of technique and early results. World J Urol. 2020;38:1943–9.
doi: 10.1007/s00345-019-02992-4
Han C, Liu S, Qin XB, Ma S, Zhu LN, Wang XY. MRI combined with PSA density in detecting clinically significant prostate cancer in patients with PSA serum levels of 4∼10ng/mL: biparametric versus multiparametric MRI. Diagn Inter Imaging. 2020;101:235–44.
doi: 10.1016/j.diii.2020.01.014
Hosseiny M, Shakeri S, Felker ER, Lu D, Sayre J, Ahuja P, et al. 3-T multiparametric MRI followed by In-Bore MR-guided biopsy for detecting clinically significant prostate cancer after prior negative transrectal ultrasound-guided biopsy. AJR Am J Roentgenol. 2020;215:660–6.
doi: 10.2214/AJR.19.22455
Hosseiny M, Felker ER, Azadikhah A, Suvannarerg V, Sayre J, Ponzini D, et al. Efficacy of 3T multiparametric MR imaging followed by 3T in-bore MR-guided biopsy for detection of clinically significant prostate cancer based on PIRADSv2.1 score. J Vasc Inter Radio. 2020;31:1619–26.
doi: 10.1016/j.jvir.2020.03.002
Hötker AM, Blüthgen C, Rupp NJ, Schneider AF, Eberli D, Donati OF. Comparison of the PI-RADS 2.1 scoring system to PI-RADS 2.0: impact on diagnostic accuracy and inter-reader agreement. PLoS ONE. 2020;15:e0239975.
doi: 10.1371/journal.pone.0239975
Lim CS, Abreu-Gomez J, Carrion I, Schieda N. Prevalence of prostate cancer in PI-RADS version 2.1 transition zone atypical nodules upgraded by abnormal DWI: correlation with MRI-directed TRUS-guided targeted biopsy. AJR Am J Roentgenol. 2021;216:683–90.
Rudolph MM, Baur ADJ, Cash H, Haas M, Mahjoub S, Hartenstein A, et al. Diagnostic performance of PI-RADS version 2.1 compared to version 2.0 for detection of peripheral and transition zone prostate cancer. Sci Rep. 2020;10:15982.
doi: 10.1038/s41598-020-72544-z
Tamada T, Kido A, Yamamoto A, Takeuchi M, Miyaji Y, Moriya T, et al. Comparison of biparametric and multiparametric MRI for clinically significant prostate cancer detection with PI-RADS version 2.1. J Magn Reson Imaging. 2021;53:283–91.
doi: 10.1002/jmri.27283
Vilanova JC, Pérez de Tudela A, Puig J, Hoogenboom M, Barceló J, Planas M, et al. Robotic-assisted transrectal MRI-guided biopsy. Technical feasibility and role in the current diagnosis of prostate cancer: an initial single-center experience. Abdom Radio (NY). 2020;45:4150–9.
doi: 10.1007/s00261-020-02665-6
Walker SM, Mehralivand S, Harmon SA, Sanford T, Merino MJ, Wood BJ, et al. Prospective evaluation of PI-RADS version 2.1 for prostate cancer detection. AJR Am J Roentgenol. 2020;215:1098–103.
Wang Z, Zhao W, Shen J, Jiang Z, Yang S, Tan S, et al. PI-RADS version 2.1 scoring system is superior in detecting transition zone prostate cancer: a diagnostic study. Abdom Radio (NY). 2020;45:4142–9.
doi: 10.1007/s00261-020-02724-y
Xu L, Zhang G, Zhang D, Zhang X, Bai X, Yan W, et al. Comparison of PI-RADS version 2.1 and PI-RADS version 2 regarding interreader variability and diagnostic accuracy for transition zone prostate cancer. Abdom Radio (NY). 2020;45:4133–41.
doi: 10.1007/s00261-020-02738-6
Osses DF, Arsov C, Schimmöller L, Schoots IG, van Leenders GJLH, Esposito I, et al. Equivocal PI-RADS three lesions on prostate magnetic resonance imaging: risk stratification strategies to avoid MRI-Targeted Biopsies. J Pers Med. 2020;10.
Woo S, Suh CH, Kim SY, Cho JY, Kim SH. 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. 2017;72:177–88.
doi: 10.1016/j.eururo.2017.01.042
Park KJ, Choi SH, Kim M-H, Kim JK, Jeong IG. Performance of prostate imaging reporting and data system version 2.1 for diagnosis of prostate cancer: a systematic review and meta-analysis. J Magn Reson Imaging. 2021;54:103–12.
Sica GT. Bias in Research Studies. Radiol Soc North Am. 2006;238:780–9.
QUADAS-2 template [Internet]. [cited 2021 Feb 25]. Available from: https://www.bristol.ac.uk/population-health-sciences/projects/quadas/resources/ .

Auteurs

Benedict Oerther (B)

Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany, Freiburg, Germany.

Hannes Engel (H)

Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany, Freiburg, Germany.

Fabian Bamberg (F)

Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany, Freiburg, Germany.

August Sigle (A)

Department of Urology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany, Freiburg, Germany.

Christian Gratzke (C)

Department of Urology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany, Freiburg, Germany.

Matthias Benndorf (M)

Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany, Freiburg, Germany. matthias.benndorf@uniklinik-freiburg.de.

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