Literature DB >> 23723087

Diffusion-weighted signal models in healthy and cancerous peripheral prostate tissues: comparison of outcomes obtained at different b-values.

Lorenzo N Mazzoni1, Silvia Lucarini, Stefano Chiti, Simone Busoni, Cesare Gori, Ilario Menchi.   

Abstract

PURPOSE: To evaluate the dependence on the b-values adopted of apparent diffusion coefficient (ADC), perfusion fraction (PF), slow and fast diffusion coefficient (Dslow, Dfast), corrected diffusion coefficient (D) and kurtosis (K), in healthy peripheral (HP) and peripheral cancerous (PCa) prostate tissues.
MATERIALS AND METHODS: Patients who underwent multiparametric prostate MR examination were retrospectively evaluated for possible inclusion. ADC, PF, Dslow, Dfast, D, and K were estimated both in HP and PCa tissues, using three different ranges of b-values: 0-2300, 0-1800, 0-800 s/mm2 (group A, B and C, respectively). Analysis of variance (ANOVA) and receiver operating characteristic (ROC) analysis were performed, to establish differences among groups and to evaluate sensitivity and specificity of every parameter in distinguishing HP and PCa tissues when calculated with different b-values.
RESULTS: In all, 57 patients were included. ANOVA showed significant differences of all parameters between group A-B vs. C, both in HP and PCa tissues. In ROC analysis K showed the best area under the curve (AUC) when calculated in groups A and B (0.87 and 0.86), while it was comparable with the ADC one in group C (both 0.82).
CONCLUSION: A significant dependence on the adopted b-values of DWI parameters is shown. The best performance in distinguishing HP from PCa tissues was obtained by K, calculated using a high b-value sequence.
Copyright © 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  ADC; biexponential DWI model; kurtosis; prostate DWI

Mesh:

Year:  2013        PMID: 23723087     DOI: 10.1002/jmri.24184

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  8 in total

1.  Effect of combination and number of b values in IVIM analysis with post-processing methodology: simulation and clinical study.

Authors:  Archana Vadiraj Malagi; Chandan J Das; Kedar Khare; Fernando Calamante; Amit Mehndiratta
Journal:  MAGMA       Date:  2019-06-18       Impact factor: 2.310

2.  Feasibility study of computed vs measured high b-value (1400 s/mm²) diffusion-weighted MR images of the prostate.

Authors:  Leonardo K Bittencourt; Ulrike I Attenberger; Daniel Lima; Ralph Strecker; Andre de Oliveira; Stefan O Schoenberg; Emerson L Gasparetto; Daniel Hausmann
Journal:  World J Radiol       Date:  2014-06-28

3.  Prostate cancer discrimination in the peripheral zone with a reduced field-of-view T(2)-mapping MRI sequence.

Authors:  Fernando I Yamauchi; Tobias Penzkofer; Andriy Fedorov; Fiona M Fennessy; Renxin Chu; Stephan E Maier; Clare M C Tempany; Robert V Mulkern; Lawrence P Panych
Journal:  Magn Reson Imaging       Date:  2015-02-14       Impact factor: 2.546

4.  Quantitative diffusion MRI using reduced field-of-view and multi-shot acquisition techniques: Validation in phantoms and prostate imaging.

Authors:  Yuxin Zhang; James Holmes; Iñaki Rabanillo; Arnaud Guidon; Shane Wells; Diego Hernando
Journal:  Magn Reson Imaging       Date:  2018-04-17       Impact factor: 2.546

5.  Evaluation of different mathematical models and different b-value ranges of diffusion-weighted imaging in peripheral zone prostate cancer detection using b-value up to 4500 s/mm2.

Authors:  Zhaoyan Feng; Xiangde Min; Daniel J A Margolis; Caohui Duan; Yuping Chen; Vivek Kumar Sah; Nabin Chaudhary; Basen Li; Zan Ke; Peipei Zhang; Liang Wang
Journal:  PLoS One       Date:  2017-02-15       Impact factor: 3.240

6.  Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis.

Authors:  V Brancato; C Cavaliere; M Salvatore; S Monti
Journal:  Sci Rep       Date:  2019-11-14       Impact factor: 4.379

Review 7.  Basic concepts and applications of functional magnetic resonance imaging for radiotherapy of prostate cancer.

Authors:  Lars E Olsson; Mikael Johansson; Björn Zackrisson; Lennart K Blomqvist
Journal:  Phys Imaging Radiat Oncol       Date:  2019-02-25

8.  Evaluating Prostate Cancer Using Fractional Tissue Composition of Radical Prostatectomy Specimens and Pre-Operative Diffusional Kurtosis Magnetic Resonance Imaging.

Authors:  Edward M Lawrence; Anne Y Warren; Andrew N Priest; Tristan Barrett; Debra A Goldman; Andrew B Gill; Vincent J Gnanapragasam; Evis Sala; Ferdia A Gallagher
Journal:  PLoS One       Date:  2016-07-28       Impact factor: 3.240

  8 in total

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