Literature DB >> 32307327

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

Bashir Al Hussein Al Awamlh1, Leonard S Marks2, Geoffrey A Sonn3, Shyam Natarajan4, Richard E Fan3, Michael D Gross1, Elizabeth Mauer5, Samprit Banerjee5, Stefanie Hectors6, Sigrid Carlsson7, Daniel J Margolis6, Jim C Hu8.   

Abstract

OBJECTIVES: We sought to identify clinical and magnetic resonance imaging (MRI) characteristics in men with the Prostate Imaging - Reporting and Data System (PI-RADS) category 3 index lesions that predict clinically significant prostate cancer (CaP) on MRI targeted biopsy.
MATERIALS AND METHODS: Multicenter study of prospectively collected data for biopsy-naive men (n = 247) who underwent MRI-targeted and systematic biopsies for PI-RADS 3 index lesions. The primary endpoint was diagnosis of clinically significant CaP (Grade Group ≥2). Multivariable logistic regression models assessed for factors associated with clinically significant CaP. The probability distributions of clinically significant CaP based on different levels of predictors of multivariable models were plotted in a heatmap.
RESULTS: Men with clinically significant CaP had smaller prostate volume (39.20 vs. 55.10 ml, P < 0.001) and lower apparent diffusion coefficient (ADC) values (973 vs. 1068 μm2/s, P = 0.013), but higher prostate-specific antigen (PSA) density (0.21 vs. 0.13 ng/ml2, P = 0.027). On multivariable analyses, lower prostate volume (odds ratio [OR]: 0.95, 95% confidence interval [CI]: 0.92-0.97), lower ADC value (OR: 0.99, 95% CI: 0.99-1.00), and Prostate-specific antigen density >0.15 ng/ml2 (OR: 3.51, 95% CI 1.61-7.68) were independently associated with significant CaP.
CONCLUSION: Higher PSA density, lower prostate volume and ADC values are associated with clinically significant CaP in biopsy-naïve men with PI-RADS 3 lesions. We present regression-derived probabilities of detecting clinically significant CaP based on various clinical and imaging values that can be used in decision-making. Our findings demonstrate an opportunity for MRI refinement or biomarker discovery to improve risk stratification for PI-RADS 3 lesions.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Magnetic resonance imaging; Prostate cancer

Mesh:

Year:  2020        PMID: 32307327      PMCID: PMC7328785          DOI: 10.1016/j.urolonc.2020.03.019

Source DB:  PubMed          Journal:  Urol Oncol        ISSN: 1078-1439            Impact factor:   3.498


  28 in total

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Authors:  Michele Scialpi; Eugenio Martorana; Maria Cristina Aisa; Valeria Rondoni; Alfredo D'Andrea; Giampaolo Bianchi
Journal:  Turk J Urol       Date:  2017-08-03

2.  Update of the Standard Operating Procedure on the Use of Multiparametric Magnetic Resonance Imaging for the Diagnosis, Staging and Management of Prostate Cancer.

Authors:  Marc A Bjurlin; Peter R Carroll; Scott Eggener; Pat F Fulgham; Daniel J Margolis; Peter A Pinto; Andrew B Rosenkrantz; Jonathan N Rubenstein; Daniel B Rukstalis; Samir S Taneja; Baris Turkbey
Journal:  J Urol       Date:  2019-10-23       Impact factor: 7.450

3.  Prospective comparison of transperineal magnetic resonance imaging/ultrasonography fusion biopsy and transrectal systematic biopsy in biopsy-naïve patients.

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Journal:  BJU Int       Date:  2017-10-15       Impact factor: 5.588

4.  Prostate Imaging Reporting and Data System 3 Category Cases at Multiparametric Magnetic Resonance for Prostate Cancer: A Systematic Review and Meta-analysis.

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Journal:  Eur Urol Focus       Date:  2019-07-04

5.  The Learning Curve for Magnetic Resonance Imaging/Ultrasound Fusion-guided Prostate Biopsy.

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Journal:  Eur Urol Oncol       Date:  2018-08-17

Review 6.  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.

Authors:  Jonathan I Epstein; Lars Egevad; Mahul B Amin; Brett Delahunt; John R Srigley; Peter A Humphrey
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7.  Targeted biopsy in the detection of prostate cancer using an office based magnetic resonance ultrasound fusion device.

Authors:  Geoffrey A Sonn; Shyam Natarajan; Daniel J A Margolis; Malu MacAiran; Patricia Lieu; Jiaoti Huang; Frederick J Dorey; Leonard S Marks
Journal:  J Urol       Date:  2012-11-14       Impact factor: 7.450

Review 8.  Artificial intelligence in radiology.

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Journal:  Nat Rev Cancer       Date:  2018-08       Impact factor: 60.716

9.  MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis.

Authors:  Veeru Kasivisvanathan; Antti S Rannikko; Marcelo Borghi; Valeria Panebianco; Lance A Mynderse; Markku H Vaarala; Alberto Briganti; Lars Budäus; Giles Hellawell; Richard G Hindley; Monique J Roobol; Scott Eggener; Maneesh Ghei; Arnauld Villers; Franck Bladou; Geert M Villeirs; Jaspal Virdi; Silvan Boxler; Grégoire Robert; Paras B Singh; Wulphert Venderink; Boris A Hadaschik; Alain Ruffion; Jim C Hu; Daniel Margolis; Sébastien Crouzet; Laurence Klotz; Samir S Taneja; Peter Pinto; Inderbir Gill; Clare Allen; Francesco Giganti; Alex Freeman; Stephen Morris; Shonit Punwani; Norman R Williams; Chris Brew-Graves; Jonathan Deeks; Yemisi Takwoingi; Mark Emberton; Caroline M Moore
Journal:  N Engl J Med       Date:  2018-03-18       Impact factor: 176.079

Review 10.  Systematic review of complications of prostate biopsy.

Authors:  Stacy Loeb; Annelies Vellekoop; Hashim U Ahmed; James Catto; Mark Emberton; Robert Nam; Derek J Rosario; Vincenzo Scattoni; Yair Lotan
Journal:  Eur Urol       Date:  2013-06-04       Impact factor: 20.096

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1.  Evaluation of a multiparametric MRI radiomic-based approach for stratification of equivocal PI-RADS 3 and upgraded PI-RADS 4 prostatic lesions.

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Journal:  Sci Rep       Date:  2021-01-12       Impact factor: 4.379

2.  Utility of Clinical-Radiomic Model to Identify Clinically Significant Prostate Cancer in Biparametric MRI PI-RADS V2.1 Category 3 Lesions.

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3.  Clinical Utility of Prostate Health Index for Diagnosis of Prostate Cancer in Patients with PI-RADS 3 Lesions.

Authors:  Chung-Un Lee; Sang-Min Lee; Jae-Hoon Chung; Minyong Kang; Hyun-Hwan Sung; Hwang-Gyun Jeon; Byong-Chang Jeong; Seong-Il Seo; Seong-Soo Jeon; Hyun-Moo Lee; Wan Song
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