Literature DB >> 29112469

Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI.

Alison D Sheridan1,2, Sameer K Nath3,4, Jamil S Syed5, Sanjay Aneja3, Preston C Sprenkle5, Jeffrey C Weinreb1, Michael Spektor1.   

Abstract

OBJECTIVE: The objective of this study is to determine the frequency of clinically significant cancer (CSC) in Prostate Imaging Reporting and Data System (PI-RADS) category 3 (equivocal) lesions prospectively identified on multiparametric prostate MRI and to identify risk factors (RFs) for CSC that may aid in decision making.
MATERIALS AND METHODS: Between January 2015 and July 2016, a total of 977 consecutively seen men underwent multiparametric prostate MRI, and 342 underwent MRI-ultrasound (US) fusion targeted biopsy. A total of 474 lesions were retrospectively reviewed, and 111 were scored as PI-RADS category 3 and were visualized using a 3-T MRI scanner. Multiparametric prostate MR images were prospectively interpreted by body subspecialty radiologists trained to use PI-RADS version 2. CSC was defined as a Gleason score of at least 7 on targeted biopsy. A multivariate logistic regression model was constructed to identify the RFs associated with CSC.
RESULTS: Of the 111 PI-RADS category 3 lesions, 81 (73.0%) were benign, 11 (9.9%) were clinically insignificant (Gleason score, 6), and 19 (17.1%) were clinically significant. On multivariate analysis, three RFs were identified as significant predictors of CSC: older patient age (odds ratio [OR], 1.13; p = 0.002), smaller prostate volume (OR, 0.94; p = 0.008), and abnormal digital rectal examination (DRE) findings (OR, 3.92; p = 0.03). For PI-RADS category 3 lesions associated with zero, one, two, or three RFs, the risk of CSC was 4%, 16%, 62%, and 100%, respectively. PI-RADS category 3 lesions for which two or more RFs were noted (e.g., age ≥ 70 years, gland size ≤ 36 mL, or abnormal DRE findings) had a CSC detection rate of 67% with a sensitivity of 53%, a specificity of 95%, a positive predictive value of 67%, and a negative predictive value of 91%.
CONCLUSION: Incorporating clinical parameters into risk stratification algorithms may improve the ability to detect clinically significant disease among PI-RADS category 3 lesions and may aid in the decision to perform biopsy.

Entities:  

Keywords:  MRI-ultrasound fusion targeted biopsy; PI-RADS category 3 lesions; PI-RADS version 2; prostate cancer; prostate multiparametric MRI

Mesh:

Year:  2017        PMID: 29112469     DOI: 10.2214/AJR.17.18516

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  10 in total

1.  Clinico-radiological characteristic-based machine learning in reducing unnecessary prostate biopsies of PI-RADS 3 lesions with dual validation.

Authors:  Yansheng Kan; Qing Zhang; Jiange Hao; Wei Wang; Junlong Zhuang; Jie Gao; Haifeng Huang; Jing Liang; Giancarlo Marra; Giorgio Calleris; Marco Oderda; Xiaozhi Zhao; Paolo Gontero; Hongqian Guo
Journal:  Eur Radiol       Date:  2020-06-10       Impact factor: 5.315

2.  Comparison of multiparametric and biparametric MRI of the prostate: are gadolinium-based contrast agents needed for routine examinations?

Authors:  Daniel Junker; Fabian Steinkohl; Veronika Fritz; Jasmin Bektic; Theodoros Tokas; Friedrich Aigner; Thomas R W Herrmann; Michael Rieger; Udo Nagele
Journal:  World J Urol       Date:  2018-08-04       Impact factor: 4.226

3.  PI-RADS version 2.1 scoring system is superior in detecting transition zone prostate cancer: a diagnostic study.

Authors:  Zhibing Wang; Wenlu Zhao; Junkang Shen; Zhen Jiang; Shuo Yang; Shuangxiu Tan; Yueyue Zhang
Journal:  Abdom Radiol (NY)       Date:  2020-09-09

4.  Multicenter analysis of clinical and MRI characteristics associated with detecting clinically significant prostate cancer in PI-RADS (v2.0) category 3 lesions.

Authors:  Bashir Al Hussein Al Awamlh; Leonard S Marks; Geoffrey A Sonn; Shyam Natarajan; Richard E Fan; Michael D Gross; Elizabeth Mauer; Samprit Banerjee; Stefanie Hectors; Sigrid Carlsson; Daniel J Margolis; Jim C Hu
Journal:  Urol Oncol       Date:  2020-04-17       Impact factor: 3.498

5.  Evaluating the performance of clinical and radiological data in predicting prostate cancer in prostate imaging reporting and data system version 2.1 category 3 lesions of the peripheral and the transition zones.

Authors:  Caterina Gaudiano; Lorenzo Bianchi; Beniamino Corcioni; Francesca Giunchi; Riccardo Schiavina; Federica Ciccarese; Lorenzo Braccischi; Arianna Rustici; Michelangelo Fiorentino; Eugenio Brunocilla; Rita Golfieri
Journal:  Int Urol Nephrol       Date:  2021-11-25       Impact factor: 2.370

6.  Combining clinical and MRI data to manage PI-RADS 3 lesions and reduce excessive biopsy.

Authors:  Shuo Yang; Wenlu Zhao; Shuangxiu Tan; Yueyue Zhang; Chaogang Wei; Tong Chen; Junkang Shen
Journal:  Transl Androl Urol       Date:  2020-06

7.  When to biopsy Prostate Imaging and Data Reporting System version 2 (PI-RADSv2) assessment category 3 lesions? Use of clinical and imaging variables to predict cancer diagnosis at targeted biopsy.

Authors:  Christopher S Lim; Jorge Abreu-Gomez; Michel-Alexandre Leblond; Ivan Carrion; Danny Vesprini; Nicola Schieda; Laurence Klotz
Journal:  Can Urol Assoc J       Date:  2021-04       Impact factor: 1.862

8.  Comparison of biparametric MRI to full multiparametric MRI for detection of clinically significant prostate cancer.

Authors:  Rachael L Sherrer; Zachary A Glaser; Jennifer B Gordetsky; Jeffrey W Nix; Kristin K Porter; Soroush Rais-Bahrami
Journal:  Prostate Cancer Prostatic Dis       Date:  2018-11-09       Impact factor: 5.554

9.  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.

Authors:  Jing Zeng; Qingqing Cheng; Dong Zhang; Meng Fan; Changzheng Shi; Liangping Luo
Journal:  Front Oncol       Date:  2021-02-19       Impact factor: 6.244

Review 10.  Paradigm Shift in Prostate Cancer Diagnosis: Pre-Biopsy Prostate Magnetic Resonance Imaging and Targeted Biopsy.

Authors:  Jung Jae Park; Chan Kyo Kim
Journal:  Korean J Radiol       Date:  2022-05-09       Impact factor: 7.109

  10 in total

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