Literature DB >> 19009566

Diffusion-weighted imaging of the prostate and rectal wall: comparison of biexponential and monoexponential modelled diffusion and associated perfusion coefficients.

S F Riches1, K Hawtin, E M Charles-Edwards, N M de Souza.   

Abstract

This study compares parameters from monoexponential and biexponential modelling of diffusion-weighted imaging of normal and malignant prostate tissue and normal rectal wall tissues. Fifty men with Stage Ic prostate cancer were studied using endorectal T(2)-weighted imaging and diffusion-weighted imaging with 11 diffusion-sensitive values (b-values = 0, 1, 2, 4, 10, 20, 50, 100, 200, 400, 800 s/mm(2)). Regions of interest were drawn within non-malignant central gland and peripheral zone, malignant prostate tissue and normal rectal wall tissue. Both a monoexponential and biexponential model was fitted over various b-value ranges, giving an apparent diffusion coefficient (ADC) from the monoexponential model and a diffusion coefficient, perfusion coefficient and perfusion fraction from the biexponential model. In all tissues, over the full range of b-values, the ADC from the monoexponential model was significantly higher than the corresponding diffusion coefficient from the biexponential model. As the minimum b-value increased, the ADC decreased and was equal to the diffusion coefficient for some b-value ranges. The biexponential model best described the data when low b-values were included, suggesting that there is a fast perfusion component. Neither model could distinguish between benign prostate tissues on the basis of diffusion coefficients, but the rectal wall tissue and malignant prostate tissue had significantly lower diffusion coefficients than normal prostate tissues. Perfusion coefficients and fractions were highly variable within the population, so their clinical utility may be limited, but removal of this variable perfusion component from reported diffusion coefficients is important when attributing clinical differences to diffusion within tissues.

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Year:  2009        PMID: 19009566     DOI: 10.1002/nbm.1328

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  51 in total

Review 1.  Diffusion weighted imaging in prostate cancer.

Authors:  Cher Heng Tan; Jihong Wang; Vikas Kundra
Journal:  Eur Radiol       Date:  2010-10-09       Impact factor: 5.315

2.  Reducing the influence of b-value selection on diffusion-weighted imaging of the prostate: evaluation of a revised monoexponential model within a clinical setting.

Authors:  Yousef Mazaheri; Hebert Alberto Vargas; Oguz Akin; Debra A Goldman; Hedvig Hricak
Journal:  J Magn Reson Imaging       Date:  2011-11-08       Impact factor: 4.813

3.  Practical estimate of gradient nonlinearity for implementation of apparent diffusion coefficient bias correction.

Authors:  Dariya I Malkyarenko; Thomas L Chenevert
Journal:  J Magn Reson Imaging       Date:  2014-12       Impact factor: 4.813

4.  Evaluation of fitting models for prostate tissue characterization using extended-range b-factor diffusion-weighted imaging.

Authors:  Fredrik Langkilde; Thiele Kobus; Andriy Fedorov; Ruth Dunne; Clare Tempany; Robert V Mulkern; Stephan E Maier
Journal:  Magn Reson Med       Date:  2017-07-17       Impact factor: 4.668

5.  Intravoxel Incoherent Motion (IVIM) Diffusion Weighted Imaging (DWI) in the Periferic Prostate Cancer Detection and Stratification.

Authors:  Filippo Pesapane; Francesca Patella; Enrico Maria Fumarola; Silvia Panella; Anna Maria Ierardi; Giovanni Guido Pompili; Giuseppe Franceschelli; Salvatore Alessio Angileri; Alberto Magenta Biasina; Gianpaolo Carrafiello
Journal:  Med Oncol       Date:  2017-01-31       Impact factor: 3.064

6.  Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements.

Authors:  Dariya I Malyarenko; Brian D Ross; Thomas L Chenevert
Journal:  Magn Reson Med       Date:  2014-03       Impact factor: 4.668

7.  Computed diffusion-weighted imaging using 3-T magnetic resonance imaging for prostate cancer diagnosis.

Authors:  Yoshiko Ueno; Satoru Takahashi; Kazuhiro Kitajima; Tokunori Kimura; Ikuo Aoki; Fumi Kawakami; Hideaki Miyake; Yoshiharu Ohno; Kazuro Sugimura
Journal:  Eur Radiol       Date:  2013-07-25       Impact factor: 5.315

8.  Prediction of biochemical recurrence following radical prostatectomy in men with prostate cancer by diffusion-weighted magnetic resonance imaging: initial results.

Authors:  Sung Yoon Park; Chan Kyo Kim; Byung Kwan Park; Hyun Moo Lee; Kyung Soo Lee
Journal:  Eur Radiol       Date:  2010-11-03       Impact factor: 5.315

Review 9.  Diffusion-weighted imaging with apparent diffusion coefficient mapping and spectroscopy in prostate cancer.

Authors:  Michael A Jacobs; Ronald Ouwerkerk; Kyle Petrowski; Katarzyna J Macura
Journal:  Top Magn Reson Imaging       Date:  2008-12

10.  Current and future trends in magnetic resonance imaging assessments of the response of breast tumors to neoadjuvant chemotherapy.

Authors:  Lori R Arlinghaus; Xia Li; Mia Levy; David Smith; E Brian Welch; John C Gore; Thomas E Yankeelov
Journal:  J Oncol       Date:  2010-09-29       Impact factor: 4.375

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