BACKGROUND: Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, identified through multiparametric magnetic resonance imaging (mpMRI), present a clinical challenge due to their equivocal nature in predicting clinically significant prostate cancer (csPCa). Aim of the study is to improve risk stratification of patients with PI-RADS 3 lesions and candidates for prostate biopsy. METHODS: A cohort of 4841 consecutive patients who underwent MRI and subsequent MRI-targeted and systematic biopsies between January 2016 and April 2023 were retrospectively identified from independent prospectively maintained database. Only patients who have PI-RADS 3 lesions were included in the final analysis. A multivariable logistic regression analysis was performed to identify covariables associated with csPCa defined as International Society of Urological Pathology (ISUP) grade group ≥2. Performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Significant predictors were then selected for further exploration using a Chi-squared Automatic Interaction Detection (CHAID) analysis. RESULTS: Overall, 790 patients had PI-RADS 3 lesions and 151 (19%) had csPCa. Significant associations were observed for age (OR: 1.1 [1.0-1.1]; p = 0.01) and PSA density (OR: 1643 [2717-41,997]; p < 0.01). The CHAID analysis identified PSAd as the sole significant factor influencing the decision tree. Cut-offs for PSAd were 0.13 ng/ml/cc (csPCa detection rate of 1% vs. 18%) for the two-nodes model and 0.09 ng/ml/cc and 0.16 ng/ml/cc for the three-nodes model (csPCa detection rate of 0.5% vs. 2% vs. 17%). CONCLUSIONS: For individuals with PI-RADS 3 lesions on prostate mpMRI and a PSAd below 0.13, especially below 0.09, prostate biopsy can be omitted, in order to avoid unnecessary biopsy and overdiagnosis of non-csPCa.

Departement of Urology Hôpital Cochin Paris France

Department of Radiology Jules Bordet Institute Erasme Hospital Hôpital Universitaire de Bruxelles Université Libre de Bruxelles Brussels Belgium

Department of Surgical Studies Faculty of Medicine Ostrava University Ostrava Czech Republic

Department of Urology Centre Hospitalier Universitaire de Reims Reims France

Department of Urology Città della Salute e della Scienza di Torino University of Turin Turin Italy

Department of Urology Clinique Saint Augustin Bordeaux France

Department of Urology Cliniques de l'Europe Saint Elisabeth Brussels Belgium

Department of Urology Grenoble Alpes University Hospital Université Grenoble Alpes CNRS Grenoble INP TIMC Grenoble France

Department of Urology Hôpital Cavale Blanche CHRU Brest Brest France

Department of Urology Hôpital Européen Georges Pompidou Université de Paris Paris France

Department of Urology Hôpitaux Universitaires de Genève Geneva Switzerland

Department of Urology IRCCS Regina Elena National Cancer Institute Rome Italy

Department of Urology Jules Bordet Institute Erasme Hospital Hôpital Universitaire de Bruxelles Université Libre de Bruxelles Brussels Belgium

Department of Urology La Croix du Sud Hospital Quint Fonsegrives France

Department of Urology Private Medical Center Klinika Wisniowa Zielona Góra Poland

Department of Urology University Hospital Ostrava Ostrava Czech Republic

Department of Urology Vivantes Klinikum am Urban Berlin Germany

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Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar MK, et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet. 2017;389:815–22. https://doi.org/10.1016/S0140-6736(16)32401-1 PubMed DOI

Zhang Y, Zeng N, Zhang F, Huang Y, Tian Y. How to make clinical decisions to avoid unnecessary prostate screening in biopsy-naïve men with PI-RADs v2 score ≤ 3? Int J Clin Oncol. 2020;25:175–86. https://doi.org/10.1007/s10147-019-01524-9 PubMed DOI

Wysock JS, Mendhiratta N, Zattoni F, Meng X, Bjurlin M, Huang WC, et al. Predictive value of negative 3T multiparametric magnetic resonance imaging of the prostate on 12-core biopsy results. BJU Int. 2016;118:515–20. https://doi.org/10.1111/bju.13427 PubMed DOI

Haffner J, Lemaitre L, Puech P, Haber G-P, Leroy X, Jones JS, et al. Role of magnetic resonance imaging before initial biopsy: comparison of magnetic resonance imaging-targeted and systematic biopsy for significant prostate cancer detection. BJU Int. 2011;108:E171–8. https://doi.org/10.1111/j.1464-410X.2011.10112.x PubMed DOI

Hamoen EHJ, de Rooij M, Witjes JA, Barentsz JO, Rovers MM. Use of the prostate imaging reporting and data system (PI-RADS) for prostate cancer detection with multiparametric magnetic resonance imaging: a diagnostic meta-analysis. Eur Urol. 2015;67:1112–21. https://doi.org/10.1016/j.eururo.2014.10.033 PubMed DOI

EAU Guidelines on Prostate Cancer - Uroweb. Uroweb - Eur Assoc Urol n.d. https://uroweb.org/guidelines/prostate-cancer#4 . Accessed 21 May 2023.

Purysko AS, Rosenkrantz AB, Turkbey IB, Macura KJ. RadioGraphics update: PI-RADS Version 2.1—a pictorial update. RadioGraphics. 2020;40:E33–7. https://doi.org/10.1148/rg.2020190207 PubMed DOI

Oerther B, Engel H, Bamberg F, Sigle A, Gratzke C, Benndorf M. Cancer detection rates of the PI-RADSv2.1 assessment categories: systematic review and meta-analysis on lesion level and patient level. Prostate Cancer Prostatic Dis. 2022;25:256–63. https://doi.org/10.1038/s41391-021-00417-1 PubMed DOI

Schoots IG. MRI in early prostate cancer detection: how to manage indeterminate or equivocal PI-RADS 3 lesions? Transl Androl Urol. 2018;7:70–82. https://doi.org/10.21037/tau.2017.12.31 PubMed DOI PMC

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. https://doi.org/10.1016/j.eururo.2015.08.052 PubMed DOI

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. https://doi.org/10.1016/j.eururo.2019.02.033 PubMed DOI

Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA, et al. The 2014 International Society of Urological Pathology (ISUP) consensus conference on gleason grading of prostatic carcinoma: definition of grading patterns and proposal for a new grading system. Am J Surg Pathol. 2016;40:244–52. https://doi.org/10.1097/PAS.0000000000000530 PubMed DOI

Riley RD, Ensor J, Snell KIE, Harrell FE, Martin GP, Reitsma JB, et al. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020;368:m441. https://doi.org/10.1136/bmj.m441 PubMed DOI

Zeng J, Cheng Q, Zhang D, Fan M, Shi C, Luo L. Diagnostic ability of dynamic contrast-enhanced magnetic resonance imaging for prostate cancer and clinically significant prostate cancer in equivocal lesions: a systematic review and meta-analysis. Front Oncol. 2021;11:620628. PubMed DOI PMC

Hong SK, Song SH, Kim HJ, Lee HS, Nam JH, Lee SB. Temporal changes of PIRADS scoring by radiologists and correlation to radical prostatectomy pathological outcomes. Prostate Int. 2022;10:188–93. https://doi.org/10.1016/j.prnil.2022.07.001 PubMed DOI PMC

Cornford P, van den Bergh RCN, Briers E, Van den Broeck T, Brunckhorst O, Darraugh J, et al. EAU-EANM-ESTRO-ESUR-ISUP-SIOG guidelines on prostate cancer-2024 update. Part I: screening, diagnosis, and local treatment with curative intent. Eur Urol. 2024:S0302-2838(24)02254-1. https://doi.org/10.1016/j.eururo.2024.03.027

Boschheidgen M, Schimmöller L, Doerfler S, Al-Monajjed R, Morawitz J, Ziayee F, et al. Single center analysis of an advisable control interval for follow-up of patients with PI-RADS category 3 in multiparametric MRI of the prostate. Sci Rep. 2022;12:6746 https://doi.org/10.1038/s41598-022-10859-9 PubMed DOI PMC

Venderink W, van Luijtelaar A, Bomers JGR, van der Leest M, Hulsbergen-van de Kaa C, Barentsz JO, et al. Results of targeted biopsy in men with magnetic resonance imaging lesions classified equivocal, likely or highly likely to be clinically significant prostate cancer. Eur Urol. 2018;73:353–60. https://doi.org/10.1016/j.eururo.2017.02.021 PubMed DOI

Szempliński S, Kamecki H, Dębowska M, Zagożdżon B, Mokrzyś M, Zawadzki M, et al. Predictors of clinically significant prostate cancer in patients with PIRADS categories 3–5 undergoing magnetic resonance imaging-ultrasound fusion biopsy of the prostate. J Clin Med. 2023;12:156 https://doi.org/10.3390/jcm12010156 DOI

Felker ER, Raman SS, Margolis DJ, Lu DSK, Shaheen N, Natarajan S, et al. 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. 2017;209:1272–7. https://doi.org/10.2214/AJR.17.18008 DOI

Sheridan AD, Nath SK, Syed JS, Aneja S, Sprenkle PC, Weinreb JC, et al. 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. 2018;210:347–57. https://doi.org/10.2214/AJR.17.18516 DOI

Schoots IG, Padhani AR. Risk-adapted biopsy decision based on prostate magnetic resonance imaging and prostate-specific antigen density for enhanced biopsy avoidance in first prostate cancer diagnostic evaluation. BJU Int. 2021;127:175–8. https://doi.org/10.1111/bju.15277 PubMed DOI

Kim TJ, Lee MS, Hwang SI, Lee HJ, Hong SK. Outcomes of magnetic resonance imaging fusion-targeted biopsy of prostate imaging reporting and data system 3 lesions. World J Urol. 2019;37:1581–6. https://doi.org/10.1007/s00345-018-2565-3 PubMed DOI

Aussavavirojekul P, Hoonlor A, Srinualnad S. Optimization of clinical risk-factor interpretation and radiological findings with machine learning for PIRADS category 3 patients. Prostate. 2022;82:235–44. https://doi.org/10.1002/pros.24266 PubMed DOI

Ferro M, Crocetto F, La Civita E, Fiorenza M, Jannuzzi G, Carbone G, et al. Serum (-2)proPSA/freePSAratio, (-2)proPSA/freePSA density, prostate health index, and prostate health index density as clues to reveal postoperative clinically significant prostate cancer in men with prostate-specific antigen 2-10ng/mL. Prostate. 2024. https://doi.org/10.1002/pros.24752

Ferro M, Crocetto F, Bruzzese D, Imbriaco M, Fusco F, Longo N, et al. Prostate health index and multiparametric MRI: partners in crime fighting overdiagnosis and overtreatment in prostate cancer. Cancers. 2021;13:4723. https://doi.org/10.3390/cancers13184723 PubMed DOI PMC

Wetterauer C, Matthias M, Pueschel H, Deckart A, Bubendorf L, Mortezavi A, et al. Opportunistic prostate cancer screening with biparametric magnetic resonance imaging (VISIONING). Eur Urol Focus. 2024:S2405-4569(24)00023-3. https://doi.org/10.1016/j.euf.2024.02.006