Literature DB >> 30460594

Outcomes of magnetic resonance imaging fusion-targeted biopsy of prostate imaging reporting and data system 3 lesions.

Tae Jin Kim1, Min Seung Lee1, Sung Il Hwang2, Hak Jong Lee2, Sung Kyu Hong3,4.   

Abstract

PURPOSE: To evaluate the characteristics and histological outcomes in patients with Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions undergoing magnetic resonance imaging-guided fusion-targeted biopsy (MRIFTB).
METHODS: We retrospectively reviewed 138 patients with PI-RADS category 3 lesions classified using multiparametric MRI who underwent MRIFTB between May 2016 and March 2018. The study population included biopsy-naïve and patients with prior negative biopsy. Univariate and multivariate analyzes were performed to determine significant predictors of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The definition of csPCa was set at Gleason score ≥ 3 + 4.
RESULTS: Overall, 114 (82.6%) biopsied lesions were benign and 24 (17.4%) were identified as prostate cancer. Of these 24 lesions, 14 (58.3%) harbored csPCa. Peripheral zone (PZ) lesions were more likely to be associated with malignant disease than transition zone lesions (13.7 vs. 6.2%). Multivariate logistic analysis revealed that age, PZ location, and prostate-specific antigen (PSA) density (P < 0.05) were independent predictors of both PCa and csPCa.
CONCLUSIONS: A non-negligible number of PI-RADS 3 patients harbor csPCa. Moreover, age, lesion location, and PSA density could be potential clinical predictors of PCa and csPCa. Physicians should be aware of the cancer prevalence of PI-RADS 3 lesions, as the use of the aforementioned factors can help in the decision-making process for these patients.

Entities:  

Keywords:  MRI; PI-RADS score; PSA density; Prostate biopsy; Prostate cancer

Mesh:

Year:  2018        PMID: 30460594     DOI: 10.1007/s00345-018-2565-3

Source DB:  PubMed          Journal:  World J Urol        ISSN: 0724-4983            Impact factor:   4.226


  3 in total

1.  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

2.  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

3.  Development and Validation of a Radiomics Nomogram for Predicting Clinically Significant Prostate Cancer in PI-RADS 3 Lesions.

Authors:  Tianping Li; Linna Sun; Qinghe Li; Xunrong Luo; Mingfang Luo; Haizhu Xie; Peiyuan Wang
Journal:  Front Oncol       Date:  2022-01-26       Impact factor: 6.244

  3 in total

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