Literature DB >> 32315265

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.

Antonio C Westphalen1, Charles E McCulloch1, Jordan M Anaokar1, Sandeep Arora1, Nimrod S Barashi1, Jelle O Barentsz1, Tharakeswara K Bathala1, Leonardo K Bittencourt1, Michael T Booker1, Vaughn G Braxton1, Peter R Carroll1, David D Casalino1, Silvia D Chang1, Fergus V Coakley1, Ravjot Dhatt1, Steven C Eberhardt1, Bryan R Foster1, Adam T Froemming1, Jurgen J Fütterer1, Dhakshina M Ganeshan1, Mark R Gertner1, Lori Mankowski Gettle1, Sangeet Ghai1, Rajan T Gupta1, Michael E Hahn1, Roozbeh Houshyar1, Candice Kim1, Chan Kyo Kim1, Chandana Lall1, Daniel J A Margolis1, Stephen E McRae1, Aytekin Oto1, Rosaleen B Parsons1, Nayana U Patel1, Peter A Pinto1, Thomas J Polascik1, Benjamin Spilseth1, Juliana B Starcevich1, Varaha S Tammisetti1, Samir S Taneja1, Baris Turkbey1, Sadhna Verma1, John F Ward1, Christopher A Warlick1, Andrew R Weinberger1, Jinxing Yu1, Ronald J Zagoria1, Andrew B Rosenkrantz1.   

Abstract

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.

Entities:  

Mesh:

Year:  2020        PMID: 32315265      PMCID: PMC7373346          DOI: 10.1148/radiol.2020190646

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  19 in total

1.  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.

Authors:  Emil Jernstedt Barkovich; Prasad R Shankar; Antonio C Westphalen
Journal:  AJR Am J Roentgenol       Date:  2019-02-26       Impact factor: 3.959

2.  Missing the Mark: Prostate Cancer Upgrading by Systematic Biopsy over Magnetic Resonance Imaging/Transrectal Ultrasound Fusion Biopsy.

Authors:  Akhil Muthigi; Arvin K George; Abhinav Sidana; Michael Kongnyuy; Richard Simon; Vanessa Moreno; Maria J Merino; Peter L Choyke; Baris Turkbey; Bradford J Wood; Peter A Pinto
Journal:  J Urol       Date:  2016-08-28       Impact factor: 7.450

Review 3.  Prostate Magnetic Resonance Imaging and Magnetic Resonance Imaging Targeted Biopsy in Patients with a Prior Negative Biopsy: A Consensus Statement by AUA and SAR.

Authors:  Andrew B Rosenkrantz; Sadhna Verma; Peter Choyke; Steven C Eberhardt; Scott E Eggener; Krishnanath Gaitonde; Masoom A Haider; Daniel J Margolis; Leonard S Marks; Peter Pinto; Geoffrey A Sonn; Samir S Taneja
Journal:  J Urol       Date:  2016-06-16       Impact factor: 7.450

4.  Imaging Facilities' Adherence to PI-RADS v2 Minimum Technical Standards for the Performance of Prostate MRI.

Authors:  Steven J Esses; Samir S Taneja; Andrew B Rosenkrantz
Journal:  Acad Radiol       Date:  2017-11-06       Impact factor: 3.173

5.  Assessment of PI-RADS v2 categories ≥ 3 for diagnosis of clinically significant prostate cancer.

Authors:  Nayana U Patel; Kimberly E Lind; Kavita Garg; David Crawford; Priya N Werahera; Sajal S Pokharel
Journal:  Abdom Radiol (NY)       Date:  2019-02

6.  Comparison of PI-RADS 2, ADC histogram-derived parameters, and their combination for the diagnosis of peripheral zone prostate cancer.

Authors:  W C Lin; A C Westphalen; G E Silva; S Chodraui Filho; R B Reis; V F Muglia
Journal:  Abdom Radiol (NY)       Date:  2016-11

7.  Re: Nicolas Mottet, Joaquim Bellmunt, Erik Briers, et al. EAU-ESTRO-ESUR-SIOG Guidelines on Prostate Cancer. European Association of Urology; 2017. http://uroweb.org/guideline/prostate-cancer: How to Assess the Efficacy of Medical Castration.

Authors:  Juan Morote; Imma Comas; Jacques Planas
Journal:  Eur Urol       Date:  2018-02-13       Impact factor: 20.096

8.  Evolving Use of Prebiopsy Prostate Magnetic Resonance Imaging in the Medicare Population.

Authors:  Andrew B Rosenkrantz; Jennifer Hemingway; Danny R Hughes; Richard Duszak; Bibb Allen; Jeffrey C Weinreb
Journal:  J Urol       Date:  2018-02-02       Impact factor: 7.450

Review 9.  Benign Conditions That Mimic Prostate Carcinoma: MR Imaging Features with Histopathologic Correlation.

Authors:  Yu Xuan Kitzing; Adilson Prando; Celi Varol; Gregory S Karczmar; Fiona Maclean; Aytekin Oto
Journal:  Radiographics       Date:  2015-11-20       Impact factor: 5.333

10.  Comparing Image-guided targeted Biopsies to Radical Prostatectomy Specimens for Accurate Characterization of the Index Tumor in Prostate Cancer.

Authors:  Francesco Porpiglia; Stefano DE Luca; Enrico Checcucci; Diletta Garrou; Matteo Manfredi; Fabrizio Mele; Angela Pecoraro; Roberto Passera; Enrico Bollito; Cristian Fiori
Journal:  Anticancer Res       Date:  2018-05       Impact factor: 2.480

View more
  28 in total

Review 1.  Role of pre-biopsy multiparametric MRI in prostate cancer diagnosis: Evidence from the literature.

Authors:  David Ka-Wai Leung; Peter Ka-Fung Chiu; Chi-Fai Ng; Jeremy Yuen-Chun Teoh
Journal:  Turk J Urol       Date:  2020-10-01

Review 2.  Deep learning-based artificial intelligence applications in prostate MRI: brief summary.

Authors:  Baris Turkbey; Masoom A Haider
Journal:  Br J Radiol       Date:  2021-12-03       Impact factor: 3.039

Review 3.  Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway.

Authors:  Tristan Barrett; Maarten de Rooij; Francesco Giganti; Clare Allen; Jelle O Barentsz; Anwar R Padhani
Journal:  Nat Rev Urol       Date:  2022-09-27       Impact factor: 16.430

4.  Structured approach to resolving discordance between PI-RADS v2.1 score and targeted prostate biopsy results: an opportunity for quality improvement.

Authors:  Rohith Arcot; Sitharthan Sekar; Srinath Kotamarti; Madison Krischak; Zoe D Michael; Wen-Chi Foo; Jiaoti Huang; Thomas J Polascik; Rajan T Gupta
Journal:  Abdom Radiol (NY)       Date:  2022-06-08

5.  Prostate cancer: diagnostic yield of modified transrectal ultrasound-guided twelve-core combined biopsy (targeted plus systematic biopsies) using prebiopsy magnetic resonance imaging.

Authors:  Chorog Song; Sung Yoon Park
Journal:  Abdom Radiol (NY)       Date:  2021-06-28

6.  Impact of PI-RADS Category 3 lesions on the diagnostic accuracy of MRI for detecting prostate cancer and the prevalence of prostate cancer within each PI-RADS category: A systematic review and meta-analysis.

Authors:  Akshay Wadera; Mostafa Alabousi; Alex Pozdnyakov; Mohammed Kashif Al-Ghita; Ali Jafri; Matthew Df McInnes; Nicola Schieda; Christian B van der Pol; Jean-Paul Salameh; Lucy Samoilov; Kaela Gusenbauer; Abdullah Alabousi
Journal:  Br J Radiol       Date:  2020-10-22       Impact factor: 3.039

7.  Prostate Imaging-Reporting and Data System: Comparison of the Diagnostic Performance between Version 2.0 and 2.1 for Prostatic Peripheral Zone.

Authors:  Hyun Soo Kim; Ghee Young Kwon; Min Je Kim; Sung Yoon Park
Journal:  Korean J Radiol       Date:  2021-04-09       Impact factor: 3.500

Review 8.  Imaging of Prostate Cancer.

Authors:  Heinz-Peter Schlemmer; Bernd Joachim Krause; Viktoria Schütz; David Bonekamp; Sarah Marie Schwarzenböck; Markus Hohenfellner
Journal:  Dtsch Arztebl Int       Date:  2021-10-22       Impact factor: 8.251

9.  Practice Patterns and Challenges of Performing and Interpreting Prostate MRI: A Survey by the Society of Abdominal Radiology Prostate Disease-Focused Panel.

Authors:  Silvia D Chang; Daniel J A Margolis; Baris Turkbey; Abigail A Arnold; Sadhna Verma
Journal:  AJR Am J Roentgenol       Date:  2021-02-10       Impact factor: 6.582

10.  MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance.

Authors:  Nikita Sushentsev; Leonardo Rundo; Oleg Blyuss; Vincent J Gnanapragasam; Evis Sala; Tristan Barrett
Journal:  Sci Rep       Date:  2021-06-21       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.