Literature DB >> 19646836

Imaging parameter effects in apparent diffusion coefficient determination of magnetic resonance imaging.

Akio Ogura1, Katsumi Hayakawa, Tosiaki Miyati, Fumie Maeda.   

Abstract

PURPOSE: Although an apparent diffusion coefficient (ADC) value is often used for differential diagnosis of tumours, it varies with scanning parameters. The present study was performed to investigate the influence of imaging parameters, i.e., b value, repetition time (TR) and echo time (TE), on ADC value.
METHODS: The phantoms were scanned using diffusion weighted imaging (DWI) with changing b values (b=0-3000 s/mm(2)), TR and TE to determine the influence on ADC. Moreover, ADC of the brain in normal volunteers was determined with varying b values (b=0-1000 s/mm(2)).
RESULTS: Diffusion decay curves were obtained by biexponential fitting in all phantoms. The points where fast and slow components of the biexponential decay crossed were called turning points. The b values of turning points that crossed from the biexponential curve were different in each phantom. The b values of turning points depended on ADC of fast diffusion component. When ADC is calculated using two b values of front and back for the turning point, the ADC value may be different. Therefore, it was necessary to perform calculations by b value until the turning point to obtain the ADC value of the fast component. In addition, b≥100 was recommended to avoid the influence of perfusion by blood. Furthermore, the choice of long TR and short TE was effective for accurate measurement of ADC.
CONCLUSION: It is important to determine the turning point for measuring ADC.
Copyright © 2009 Elsevier Ireland Ltd. All rights reserved.

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Year:  2009        PMID: 19646836     DOI: 10.1016/j.ejrad.2009.06.031

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  24 in total

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2.  Differentiation of recurrent tumor and posttreatment changes in head and neck squamous cell carcinoma: application of high b-value diffusion-weighted imaging.

Authors:  I Hwang; S H Choi; Y-J Kim; K G Kim; A L Lee; T J Yun; J-h Kim; C-H Sohn
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6.  Multi-system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice-water phantom.

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Authors:  Dariya I Malyarenko; David Newitt; Lisa J Wilmes; Alina Tudorica; Karl G Helmer; Lori R Arlinghaus; Michael A Jacobs; Guido Jajamovich; Bachir Taouli; Thomas E Yankeelov; Wei Huang; Thomas L Chenevert
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8.  Roles of the apparent diffusion coefficient and tumor volume in predicting tumor grade in patients with choroid plexus tumors.

Authors:  Tomoaki Sasaki; John Kim; Toshio Moritani; Aristides A Capizzano; Shawn P Sato; Yutaka Sato; Patricia Kirby; Shunta Ishitoya; Akiko Oya; Masahiro Toda; Sayaka Yuzawa; Koji Takahashi
Journal:  Neuroradiology       Date:  2018-03-15       Impact factor: 2.804

9.  Effects of diffusional kurtosis imaging parameters on diffusion quantification.

Authors:  Issei Fukunaga; Masaaki Hori; Yoshitaka Masutani; Nozomi Hamasaki; Shuji Sato; Yuriko Suzuki; Fumitaka Kumagai; Masatsugu Kosuge; Haruyoshi Hoshito; Koji Kamagata; Keigo Shimoji; Atsushi Nakanishi; Shigeki Aoki; Atsushi Senoo
Journal:  Radiol Phys Technol       Date:  2013-03-28

10.  Improving apparent diffusion coefficient accuracy on a compact 3T MRI scanner using gradient nonlinearity correction.

Authors:  Ashley T Tao; Yunhong Shu; Ek T Tan; Joshua D Trzasko; Shengzhen Tao; Robert D Reid; Paul T Weavers; John Huston; Matt A Bernstein
Journal:  J Magn Reson Imaging       Date:  2018-09-26       Impact factor: 4.813

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