Literature DB >> 20947645

Diffusion tensor MR imaging of cerebral gliomas: evaluating fractional anisotropy characteristics.

M L White1, Y Zhang, F Yu, S A Jaffar Kazmi.   

Abstract

BACKGROUND AND
PURPOSE: FA correlation to glioma tumor grade has been mixed if not disappointing. There are several potential underlying fundamental issues that have contributed to these results. In an attempt to overcome these past shortfalls, we evaluated characteristics of FA of the solid tissue components of gliomas, including whether high-grade gliomas have a greater variation of FA than low-grade gliomas.
MATERIALS AND METHODS: Thirty-four patients with gliomas (9 grade II, 8 grade III, and 17 grade IV) underwent diffusion tensor imaging at 3T. Mean FA, maximum FA, and minimum FA values were measured within the solid tissue components of the tumors. The variations of FA were evaluated by determining the range of FA values and the maximum SDs of FA. The variations of FA values among different tumor grades were compared statistically. We also correlated FA variations with minimum FA and maximum FA.
RESULTS: The maximum FA, FA range, and maximum SD for grade II tumors were significantly lower than those for grade III and IV tumors (P < .0001 ∼ P = .0164). A very good correlation of maximum FA to FA range (r = 0.931) and maximum SD (r = 0.889) was observed.
CONCLUSIONS: The FA range and maximum SD appear useful for differentiating low- and high-grade gliomas. This analysis added value to the findings on conventional MR imaging. In addition, focal maximum FA is a key factor contributing to the larger FA variation within high-grade gliomas.

Entities:  

Mesh:

Year:  2010        PMID: 20947645      PMCID: PMC7965729          DOI: 10.3174/ajnr.A2267

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  25 in total

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Authors:  P E Sijens; M A A M Heesters; R H Enting; W T A van der Graaf; J H Potze; R Irwan; L C Meiners; M Oudkerk
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2.  How often are nonenhancing supratentorial gliomas malignant? A population study.

Authors:  J N Scott; P M A Brasher; R J Sevick; N B Rewcastle; P A Forsyth
Journal:  Neurology       Date:  2002-09-24       Impact factor: 9.910

3.  Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm.

Authors:  Brian P Witwer; Roham Moftakhar; Khader M Hasan; Praveen Deshmukh; Victor Haughton; Aaron Field; Konstantinos Arfanakis; Jane Noyes; Chad H Moritz; M Elizabeth Meyerand; Howard A Rowley; Andrew L Alexander; Behnam Badie
Journal:  J Neurosurg       Date:  2002-09       Impact factor: 5.115

4.  Diffusion tensor imaging for preoperative evaluation of tumor grade in gliomas.

Authors:  Takashi Inoue; Kuniaki Ogasawara; Takaaki Beppu; Akira Ogawa; Hiroyuki Kabasawa
Journal:  Clin Neurol Neurosurg       Date:  2005-04       Impact factor: 1.876

5.  Gliomas: histopathologic evaluation of changes in directionality and magnitude of water diffusion at diffusion-tensor MR imaging.

Authors:  Andreas Stadlbauer; Oliver Ganslandt; Rolf Buslei; Thilo Hammen; Stephan Gruber; Ewald Moser; Michael Buchfelder; Erich Salomonowitz; Christopher Nimsky
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6.  Disarrangement of fiber tracts and decline of neuronal density correlate in glioma patients--a combined diffusion tensor imaging and 1H-MR spectroscopy study.

Authors:  E Goebell; J Fiehler; X-Q Ding; S Paustenbach; S Nietz; O Heese; T Kucinski; C Hagel; M Westphal; H Zeumer
Journal:  AJNR Am J Neuroradiol       Date:  2006-08       Impact factor: 3.825

7.  Fractional anisotropy value by diffusion tensor magnetic resonance imaging as a predictor of cell density and proliferation activity of glioblastomas.

Authors:  Takaaki Beppu; Takashi Inoue; Yuji Shibata; Noriyuki Yamada; Akira Kurose; Kuniaki Ogasawara; Akira Ogawa; Hiroyuki Kabasawa
Journal:  Surg Neurol       Date:  2005-01

8.  Contribution of diffusion tensor imaging to delineation of gliomas and glioblastomas.

Authors:  A Tropine; G Vucurevic; P Delani; S Boor; N Hopf; J Bohl; P Stoeter
Journal:  J Magn Reson Imaging       Date:  2004-12       Impact factor: 4.813

9.  Diffusion-tensor imaging for glioma grading at 3-T magnetic resonance imaging: analysis of fractional anisotropy and mean diffusivity.

Authors:  Ho Yun Lee; Dong Gyu Na; In-Chan Song; Dong Hoon Lee; Hyung Suk Seo; Ji-hoon Kim; Kee-Hyun Chang
Journal:  J Comput Assist Tomogr       Date:  2008 Mar-Apr       Impact factor: 1.826

10.  Diffusion tensor imaging demonstrates deviation of fibres in normal appearing white matter adjacent to a brain tumour.

Authors:  U C Wieshmann; M R Symms; G J Parker; C A Clark; L Lemieux; G J Barker; S D Shorvon
Journal:  J Neurol Neurosurg Psychiatry       Date:  2000-04       Impact factor: 10.154

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  18 in total

1.  Differentiation of tumefactive demyelinating lesions from high-grade gliomas with the use of diffusion tensor imaging.

Authors:  C H Toh; K-C Wei; S-H Ng; Y-L Wan; M Castillo; C-P Lin
Journal:  AJNR Am J Neuroradiol       Date:  2011-12-15       Impact factor: 3.825

2.  Combination of diffusion tensor imaging and conventional MRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in oligodendroglial tumours.

Authors:  Ji Xiong; Wenli Tan; Jianbo Wen; Jiawei Pan; Yin Wang; Jun Zhang; Daoying Geng
Journal:  Eur Radiol       Date:  2015-09-22       Impact factor: 5.315

Review 3.  Multimodality Brain Tumor Imaging: MR Imaging, PET, and PET/MR Imaging.

Authors:  James R Fink; Mark Muzi; Melinda Peck; Kenneth A Krohn
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4.  Potential role of fractional anisotropy derived from diffusion tensor imaging in differentiating high-grade gliomas from low-grade gliomas: a meta-analysis.

Authors:  Ruofei Liang; Xiang Wang; Mao Li; Yuan Yang; Jiewen Luo; Qing Mao; Yanhui Liu
Journal:  Int J Clin Exp Med       Date:  2014-10-15

5.  Assessment of tissue heterogeneity using diffusion tensor and diffusion kurtosis imaging for grading gliomas.

Authors:  Rajikha Raja; Neelam Sinha; Jitender Saini; Anita Mahadevan; Kvl Narasinga Rao; Aarthi Swaminathan
Journal:  Neuroradiology       Date:  2016-10-29       Impact factor: 2.804

Review 6.  Neurologic Applications of PET/MR Imaging.

Authors:  Michelle M Miller-Thomas; Tammie L S Benzinger
Journal:  Magn Reson Imaging Clin N Am       Date:  2017-01-26       Impact factor: 2.266

7.  Deep Convolutional Radiomic Features on Diffusion Tensor Images for Classification of Glioma Grades.

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8.  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

9.  Imaging signatures of meningioma and low-grade glioma: a diffusion tensor, magnetization transfer and quantitative longitudinal relaxation time MRI study.

Authors:  Rory J Piper; Shadia Mikhael; Joanna M Wardlaw; David H Laidlaw; Ian R Whittle; Mark E Bastin
Journal:  Magn Reson Imaging       Date:  2015-12-17       Impact factor: 2.546

Review 10.  The role of imaging in the management of adults with diffuse low grade glioma: A systematic review and evidence-based clinical practice guideline.

Authors:  Sarah Jost Fouke; Tammie Benzinger; Daniel Gibson; Timothy C Ryken; Steven N Kalkanis; Jeffrey J Olson
Journal:  J Neurooncol       Date:  2015-11-03       Impact factor: 4.130

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