Literature DB >> 32901562

Prostatitis, the Great Mimicker of Prostate Cancer: Can We Differentiate Them Quantitatively With Multiparametric MRI?

Aycan Uysal1, Ali D Karaosmanoğlu2, Musturay Karcaaltıncaba2, Deniz Akata3, Bulent Akdogan4, Dilek E Baydar5, Mustafa N Ozmen3.   

Abstract

OBJECTIVE. The purpose of this study was to investigate the diagnostic performance of semiquantitative and quantitative pharmacokinetic parameters and quantitative apparent diffusion coefficient (ADC) values obtained from prostate multiparametric MRI (mpMRI) to differentiate prostate cancer (PCa) and prostatitis objectively. MATERIALS AND METHODS. We conducted a retrospective review of patients with biopsy-proven PCa or prostatitis who underwent mpMRI study between January 2015 and February 2018. Mean ADC, forward volume transfer constant (Ktrans), reverse volume transfer constant (kep), plasma volume fraction (Vp), extravascular extracellular space volume fraction (Ve), and time to peak (TTP) values were calculated for both lesions and contralateral normal prostate tissue. Signal intensity-time curves were analyzed. Lesion-to-normal prostate tissue ratios of pharmacokinetic parameters were also calculated. The diagnostic accuracy and cutoff points of all parameters were analyzed to differentiate PCa from prostatitis. RESULTS. A total of 138 patients (94 with PCa and 44 with prostatitis) were included in the study. Statistically, ADC, quantitative pharmacokinetic parameters (Ktrans, kep, Ve, and Vp), their lesion-to-normal prostate tissue ratios, and TTP values successfully differentiated PCa and prostatitis. Surprisingly, we found that Ve values were significantly higher in prostatitis lesions. The combination of these parameters had 92.7% overall diagnostic accuracy. ADC, kep, and TTP made up the most successful combination for differential diagnosis. Analysis of the signal intensity-time curves showed mostly type 2 and type 3 enhancement curve patterns for patients with PCa. Type 3 curves were not seen in any prostatitis cases. CONCLUSION. Quantitative analysis of mpMRI differentiates PCa from prostatitis with high sensitivity and specificity, appears to have significant potential, and may improve diagnostic accuracy. In addition, evaluating these parameters does not cause any extra burden to the patients.

Entities:  

Keywords:  multiparametric MRI; prostate cancer; prostatitis; quantitative analysis

Mesh:

Year:  2020        PMID: 32901562     DOI: 10.2214/AJR.20.22843

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


  4 in total

1.  Prostate cancer in PI-RADS scores 1 and 2 version 2.1: a comparison to previous PI-RADS versions.

Authors:  Katja Bogner; Karl Engelhard; Wolfgang Wuest; Sajad Hamel
Journal:  Abdom Radiol (NY)       Date:  2022-03-21

2.  Imaging Patterns of Bacillus Calmette-Guérin-Related Granulomatous Prostatitis Based on Multiparametric MRI.

Authors:  Seungsoo Lee; Young Taik Oh; Hye Min Kim; Dae Chul Jung; Hyesuk Hong
Journal:  Korean J Radiol       Date:  2022-01       Impact factor: 3.500

3.  A preliminary study on the diagnostic value of PSADR, DPC and TSRP in the distinction of prostatitis and prostate cancer.

Authors:  Minxin He; Li Wang; Hong Wang; Fang Liu; Mingrui Li; Tie Chong; Li Xue
Journal:  BMC Cancer       Date:  2022-03-31       Impact factor: 4.430

4.  Impact of Chronic Prostatitis on the PI-RADS Score 3: Proposal for the Addition of a Novel Binary Suffix.

Authors:  Sascha Merat; Theresa Blümlein; Markus Klarhöfer; Dominik Nickel; Gad Singer; Frank G Zöllner; Stefan O Schoenberg; Rahel A Kubik-Huch; Daniel Hausmann; Lukas Hefermehl
Journal:  Diagnostics (Basel)       Date:  2021-03-30
  4 in total

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