Literature DB >> 19394780

Diffusion tensor magnetic resonance imaging of glial brain tumors.

Jirí Ferda1, Jan Kastner, Petr Mukensnabl, Milan Choc, Jana Horemuzová, Eva Ferdová, Boris Kreuzberg.   

Abstract

AIM: To evaluate the author's experience with the use of diffusion tensor magnetic resonance imaging (DTI) on patients with glial tumors.
METHODS: A retrospective evaluation of a group of 24 patients with glial tumors was performed. There were eight patients with Grade II, eight patients with Grade III and eight patients with Grade IV tumors with a histologically proven diagnosis. All the patients underwent routine imaging including T2 weighted images, multidirectional diffusion weighted imaging (measured in 60 non-collinear directions) and T1 weighted non-enhanced and contrast enhanced images. The imaging sequence and evaluation software were produced by Massachusetts General Hospital Corporation (Boston, MA, USA). Fractional anisotropy (FA) maps were calculated in all patients. The white matter FA changes were assessed within the tumorous tissue, on the tumorous borderline and in the normally appearing white matter adjacent to the tumor. A three-dimensional model of the white matter tract was created to demonstrate the space relationship of the tumor and the capsula interna or corpus callosum in each case using the following fiber tracing parameters: FA step 0.25 and a tensor declination angle of 45 gr. An additional assessment of the tumorous tissue enhancement was performed.
RESULTS: A uniform homogenous structure with sharp demargination of the Grade II tumors and the wide rim of the intermedial FA in all Grade III tumors respectively, were found during the evaluation of the FA maps. In Grade IV tumors a variable demargination was noted on the FA maps. The sensitivity and specificity for the discrimination of low- and high-grade glial tumors using FA maps was revealed to be 81% and 87% respectively. If the evaluation of the contrast enhancement was combined with the evaluation of the FA maps, both sensitivity and specificity were 100%.
CONCLUSION: Although the evaluation of the fractional anisotropy maps is not sufficient for glioma grading, the combination of the contrast enhancement pattern and fractional anisotropy maps evaluation improves the possibility of distinguishing low- and high-grade glial tumors. Three-dimensional models of the white matter fibers in the corpus callosum and the internal capsule may be used in the presurgical planning. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

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Year:  2009        PMID: 19394780     DOI: 10.1016/j.ejrad.2009.03.030

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


  15 in total

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2.  Potential role of fractional anisotropy derived from diffusion tensor imaging in differentiating high-grade gliomas from low-grade gliomas: a meta-analysis.

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3.  Potential role for magnetoencephalography in distinguishing low- and high-grade gliomas: a preliminary study with histopathological confirmation.

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4.  Glioma grade assessment by using histogram analysis of diffusion tensor imaging-derived maps.

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Journal:  Neuroradiology       Date:  2010-09-21       Impact factor: 2.804

Review 5.  Neurosurgery for brain tumors: update on recent technical advances.

Authors:  Jonathan H Sherman; Kathryn Hoes; Joshua Marcus; Ricardo J Komotar; Cameron W Brennan; Philip H Gutin
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6.  Diffusion tensor MR imaging of cerebral gliomas: evaluating fractional anisotropy characteristics.

Authors:  M L White; Y Zhang; F Yu; S A Jaffar Kazmi
Journal:  AJNR Am J Neuroradiol       Date:  2010-10-14       Impact factor: 3.825

7.  Assessment of diffusion tensor imaging metrics in differentiating low-grade from high-grade gliomas.

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8.  Diffusion tensor tractography in the presurgical assessment of cerebral gliomas.

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Review 9.  Diffusion-weighted MRI as a biomarker for treatment response in glioma.

Authors:  Kathleen M Schmainda
Journal:  CNS Oncol       Date:  2012-11

10.  Meta-analysis of diffusion metrics for the prediction of tumor grade in gliomas.

Authors:  V Z Miloushev; D S Chow; C G Filippi
Journal:  AJNR Am J Neuroradiol       Date:  2014-09-04       Impact factor: 3.825

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