Barentsz JO, Richenberg J, Clements R, Choyke P, Verma S, Villeirs G, Rouviere O, Logager V, Logager JJ (2012) European Society of Urogenital Radiology. ESUR prostate MR guidelines 2012. Eur Radiol. 22(4):746–57. https://doi.org/10.1007/s00330-011-2377-y

Article  PubMed  PubMed Central  Google Scholar 

Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, Margolis D, Schnall MD, Shtern F, Tempany CM, Thoeny HC, Verma S (2016) PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol. 69(1):16-40. https://doi.org/10.1016/j.eururo.2015.08.052

Article  PubMed  Google Scholar 

Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, Tempany CM, Choyke PL, Cornud F, Margolis DJ, Thoeny HC, Verma S, Barentsz J, Weinreb JC (2019) Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2. Eur Urol. 76(3):340-351. https://doi.org/10.1016/j.eururo.2019.02.033

Article  PubMed  Google Scholar 

Walker SM, Mehralivand S, Harmon SA, Sanford T, Merino MJ, Wood BJ, Shih JH, Pinto PA, Choyke PL, Turkbey B (2020) Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection. AJR Am J Roentgenol. 215(5):1098–1103. https://doi.org/10.2214/AJR.19.22679

Article  PubMed  PubMed Central  Google Scholar 

Bogner K, Engelhard K, Wuest W, Hamel S (2022) Prostate cancer in PI-RADS scores 1 and 2 version 2.1: a comparison to previous PI-RADS versions. Abdom Radiol (NY). 47(6):2187–2196. https://doi.org/10.1007/s00261-022-03444-1

Girometti R, Giannarini G, De Martino M, Caregnato E, Cereser L, Soligo M, Rozze D, Pizzolitto S, Isola M, Zuiani C (2023) Multivariable stratification of PI-RADS version 2.1 categories for the risk of false-positive target biopsy: Impact on prostate biopsy decisions. Eur J Radiol. 165:110897. https://doi.org/10.1016/j.ejrad.2023.110897

Park KJ, Choi SH, Kim MH, Kim JK, Jeong IG (2021) 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. 54(1):103–112. https://doi.org/10.1002/jmri.27546

Article  PubMed  Google Scholar 

Lee CH, Vellayappan B, Tan CH (2022) Comparison of diagnostic performance and inter-reader agreement between PI-RADS v2.1 and PI-RADS v2: systematic review and meta-analysis. Br J Radiol. 95(1131):20210509. https://doi.org/10.1259/bjr.20210509

Oerther B, Engel H, Bamberg F, Sigle A, Gratzke C, Benndorf M (2022) 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. 25(2):256–263. https://doi.org/10.1038/s41391-021-00417-1

Article  CAS  PubMed  Google Scholar 

Girometti R, Giannarini G, Greco F, Isola M, Cereser L, Como G, Sioletic S, Pizzolitto S, Crestani A, Ficarra V, Zuiani C (2019) Interreader agreement of PI-RADS v. 2 in assessing prostate cancer with multiparametric MRI: A study using whole-mount histology as the standard of reference. J Magn Reson Imaging. 49(2):546–555. https://doi.org/10.1002/jmri.26220

Article  PubMed  Google Scholar 

Annamalai A, Fustok JN, Beltran-Perez J, Rashad AT, Krane LS, Triche BL (2022) Interobserver Agreement and Accuracy in Interpreting mpMRI of the Prostate: a Systematic Review. Curr Urol Rep. 23(1):1-10. https://doi.org/10.1007/s11934-022-01084-y

Article  PubMed  Google Scholar 

Purysko AS, Baroni RH, Giganti F, Costa D, Renard-Penna R, Kim CK, Raman SS (2021) PI-RADS Version 2.1: A Critical Review, From the AJR Special Series on Radiology Reporting and Data Systems. AJR Am J Roentgenol. 216(1):20–32. https://doi.org/10.2214/AJR.20.24495

Cornford P, Tilki D, van den Bergh RCN, et al. EAU-EANM-ESTRO-ESUR-ISUP-SIOG Guidelines on Prostate Cancer 2024. https://uroweb.org/guidelines/prostate-cancer. Last access July 3, 2024

National Institute for Health and Care Excellence (2019) Prostate cancer: diagnosis and management [NG131]. https://www.nice.org.uk/guidance/ng131. Accessed 17 April 2024

Brizmohun Appayya M, Adshead J, Ahmed HU, Allen C, Bainbridge A, Barrett T, Giganti F, Graham J, Haslam P, Johnston EW, Kastner C, Kirkham APS, Lipton A, McNeill A, Moniz L, Moore CM, Nabi G, Padhani AR, Parker C, Patel A, Pursey J, Richenberg J, Staffurth J, van der Meulen J, Walls D, Punwani S (2018) National implementation of multiparametric magnetic resonance imaging for prostate cancer detection - recommendations from a UK consensus meeting. BJU Int. 122(1):13-25. https://doi.org/10.1111/bju.14361

Article  PubMed  PubMed Central  Google Scholar 

Desai S, Costa DN (2022) PI-RADS and Likert scales for structured reporting in multiparametric MR imaging of the prostate. Br J Radiol. 95(1131):20210758. https://doi.org/10.1259/bjr.20210758

Article  PubMed  Google Scholar 

Latifoltojar A, Appayya MB, Barrett T, Punwani S (2019) Similarities and differences between Likert and PIRADS v2.1 scores of prostate multiparametric MRI: a pictorial review of histology-validated cases. Clin Radiol. 74(11):895.e1–895.e15. https://doi.org/10.1016/j.crad.2019.08.020

Khoo CC, Eldred-Evans D, Peters M, Bertoncelli Tanaka M, Noureldin M, Miah S, Shah T, Connor MJ, Reddy D, Clark M, Lakhani A, Rockall A, Hosking-Jervis F, Cullen E, Arya M, Hrouda D, Qazi H, Winkler M, Tam H, Ahmed HU (2020) Likert vs PI-RADS v2: a comparison of two radiological scoring systems for detection of clinically significant prostate cancer. BJU Int. 125(1):49-55. https://doi.org/10.1111/bju.14916

Article  CAS  PubMed  Google Scholar 

Zawaideh JP, Sala E, Pantelidou M, Shaida N, Koo B, Caglic I, Warren AY, Carmisciano L, Saeb-Parsy K, Gnanapragasam VJ, Kastner C, Barrett T (2020) Comparison of Likert and PI-RADS version 2 MRI scoring systems for the detection of clinically significant prostate cancer. Br J Radiol. 93(1112):20200298. https://doi.org/10.1259/bjr.20200298

Article  PubMed  PubMed Central  Google Scholar 

Mazzone E, Stabile A, Pellegrino F, Basile G, Cignoli D, Cirulli GO, Sorce G, Barletta F, Scuderi S, Bravi CA, Cucchiara V, Fossati N, Gandaglia G, Montorsi F, Briganti A (2021) 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. 4(5):697-713. https://doi.org/10.1016/j.euo.2020.12.004

Article  PubMed  Google Scholar 

Sokhi HK, Wilson A, Pindoria N, McNamara C, Padhani AR, Meer Z, Pope A (2022) Audit of cancer yields after prostate MRI using both the PI-RADS version 2 and Likert scoring systems. Clin Radiol. 77(7):541-547. https://doi.org/10.1016/j.crad.2022.03.004

Article  CAS  PubMed  Google Scholar 

Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA; Grading Committee (2016) 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. 40(2):244–52. https://doi.org/10.1097/PAS.0000000000000530

Vickers AJ, Woo S (2022) Decision curve analysis in the evaluation of radiology research. Eur Radiol. 32(9):5787-5789. https://doi.org/10.1007/s00330-022-08685-8

Article  PubMed  Google Scholar 

Shin T, Smyth TB, Ukimura O, Ahmadi N, de Castro Abreu AL, Ohe C, Oishi M, Mimata H, Gill IS (2018) Diagnostic accuracy of a five-point Likert scoring system for magnetic resonance imaging (MRI) evaluated according to results of MRI/ultrasonography image-fusion targeted biopsy of the prostate. BJU Int. 121(1):77-83. https://doi.org/10.1111/bju.13972

Article  PubMed  Google Scholar 

Gaziev G, Wadhwa K, Barrett T, Koo BC, Gallagher FA, Serrao E, Frey J, Seidenader J, Carmona L, Warren A, Gnanapragasam V, Doble A, Kastner C (2016) Defining the learning curve for multiparametric magnetic resonance imaging (MRI) of the prostate using MRI-transrectal ultrasonography (TRUS) fusion-guided transperineal prostate biopsies as a validation tool. BJU Int. 117(1):80-6. https://doi.org/10.1111/bju.12892

Article  PubMed  Google Scholar 

Stevens W, Parchment-Smith C, Adiotomre E, Hulson O, Khan A, Melling P, Pierre S, Smith J (2023) Is Likert better than PI-RADS at predicting prostate cancer on MRI and can a mathematical algorithm achieve similar results? Acta Radiol. 64(9):2659-2666. https://doi.org/10.1177/02841851231187135

Article  PubMed  Google Scholar 

Rosenkrantz AB, Kim S, Lim RP, Hindman N, Deng FM, Babb JS, Taneja SS (2013) Prostate cancer localization using multiparametric MR imaging: comparison of Prostate Imaging Reporting and Data System (PI-RADS) and Likert scales. Radiology. 269(2):482-92. https://doi.org/10.1148/radiol.13122233

Article  PubMed  Google Scholar 

Inan I, Aktan A, Seyma Ozkanli S, Yildirim A, Aslan A, Senturk Gucel S, Mehmet Erturk S (2021) Comparison of Likert and PI-RADS v2 scoring in the diagnosis of prostate cancer. Ann. Med. Res. 25(4):0651–0655. https://doi.org/10.5455/annalsmedres.2018.08.157

Article  Google Scholar 

Renard-Penna R, Mozer P, Cornud F, Barry-Delongchamps N, Bruguière E, Portalez D, Malavaud B (2015) Prostate Imaging Reporting and Data System and Likert Scoring System: Multiparametric MR Imaging Validation Study to Screen Patients for Initial Biopsy. Radiology. 275(2):458-68. https://doi.org/10.1148/radiol.14140184

Article  PubMed  Google Scholar 

Stevens WM, Parchment-Smith C, Melling PP, Smith JT (2023) Making an art into a science: a mathematical "Likert tool" can change PI-RADS (v2) scores into Likert scores when reporting multiparametric MRI for prostate cancer. Acta Radiol. 64(3):1245-1254. https://doi.org/10.1177/02841851221112194

Article  PubMed  Google Scholar 

Rouvière O, Puech P, Renard-Penna R, Claudon M, Roy C, Mège-Lechevallier F, Decaussin-Petrucci M, Dubreuil-Chambardel M, Magaud L, Remontet L, Ruffion A, Colombel M, Crouzet S, Schott AM, Lemaitre L, Rabilloud M, Grenier N, MRI-FIRST Investigators (2019) Use of prostate systematic and targeted biopsy on the basis of multiparametric MRI in biopsy-naive patients (MRI-FIRST): a prospective, multicentre, paired diagnostic study. Lancet Oncol 20(1):100-109. https://doi.org/10.1016/S1470-2045(18)30569-2

Article  PubMed  Google Scholar 

Parekh S, Ratnani P, Falagario U, Lundon D, Kewlani D, Nasri J, Dovey Z, Stroumbakis D, Ranti D, Grauer R, Sobotka S, Pedraza A, Wagaskar V, Mistry L, Jambor I, Lantz A, Ettala O, Stabile A, Taimen P, Aronen HJ, Knaapila J, Perez IM, Gandaglia G, Martini A, Picker W, Haug E, Cormio L, Nordström T, Briganti A, Boström PJ, Carrieri G, Haines K, Gorin MA, Wiklund P, Menon M, Tewari A (2022) The Mount Sinai Prebiopsy Risk Calculator for Predicting any Prostate Cancer and Clinically Significant Prostate Cancer: Development of a Risk Predictive Tool and Validation with Advanced Neural Networking, Prostate Magnetic Resonance Imaging Outcome Database, and European Randomized Study of Screening for Prostate Cancer Risk Calculator. Eur Urol Open Sci. 41:45-54. https://doi.org/10.1016/j.euros.2022.04.017

Article  PubMed  PubMed Central