Literature DB >> 22903580

Three-dimensional susceptibility-weighted imaging at 7 T using fractal-based quantitative analysis to grade gliomas.

Antonio Di Ieva1, Sabine Göd, Günther Grabner, Fabio Grizzi, Camillo Sherif, Christian Matula, Manfred Tschabitscher, Siegfrid Trattnig.   

Abstract

INTRODUCTION: Susceptibility-weighted imaging (SWI) with high- and ultra-high-field magnetic resonance is a very helpful tool for evaluating brain gliomas and intratumoral structures, including microvasculature. Here, we test whether objective quantification of intratumoral SWI patterns by applying fractal analysis can offer reliable indexes capable of differentiating glial tumor grades.
METHODS: Thirty-six patients affected by brain gliomas (grades II-IV, according to the WHO classification system) underwent MRI at 7 T using a SWI protocol. All images were collected and analyzed by applying a computer-aided fractal image analysis, which applies the fractal dimension as a measure of geometrical complexity of intratumoral SWI patterns. The results were subsequently statistically correlated to the histopathological tumor grade.
RESULTS: The mean value of the fractal dimension of the intratumoral SWI patterns was 2.086 ± 0.413. We found a trend of higher fractal dimension values in groups of higher histologic grade. The values ranged from a mean value of 1.682 ± 0.278 for grade II gliomas to 2.247 ± 0.358 for grade IV gliomas (p = 0.013); there was an overall statistically significant difference between histopathological groups.
CONCLUSION: The present study confirms that SWI at 7 T is a useful method for detecting intratumoral vascular architecture of brain gliomas and that SWI pattern quantification by means of fractal dimension offers a potential objective morphometric image biomarker of tumor grade.

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Year:  2012        PMID: 22903580     DOI: 10.1007/s00234-012-1081-1

Source DB:  PubMed          Journal:  Neuroradiology        ISSN: 0028-3940            Impact factor:   2.804


  32 in total

Review 1.  7-T MR--from research to clinical applications?

Authors:  Ewald Moser; Freddy Stahlberg; Mark E Ladd; Siegfried Trattnig
Journal:  NMR Biomed       Date:  2011-11-21       Impact factor: 4.044

2.  The veins of the nucleus dentatus: anatomical and radiological findings.

Authors:  Antonio Di Ieva; Manfred Tschabitscher; Renato Juan Galzio; Günther Grabner; Claudia Kronnerwetter; Georg Widhalm; Christian Matula; Siegfried Trattnig
Journal:  Neuroimage       Date:  2010-07-23       Impact factor: 6.556

Review 3.  Angioarchitectural morphometrics of brain tumors: are there any potential histopathological biomarkers?

Authors:  Antonio Di Ieva
Journal:  Microvasc Res       Date:  2010-09-29       Impact factor: 3.514

4.  Nonnvasive assessment of vascular architecture and function during modulated blood oxygenation using susceptibility weighted magnetic resonance imaging.

Authors:  Alexander Rauscher; Jan Sedlacik; Markus Barth; E Mark Haacke; Jürgen R Reichenbach
Journal:  Magn Reson Med       Date:  2005-07       Impact factor: 4.668

5.  Susceptibility-weighted imaging to visualize blood products and improve tumor contrast in the study of brain masses.

Authors:  Vivek Sehgal; Zachary Delproposto; Djamel Haddar; E Mark Haacke; Andrew E Sloan; Lucia J Zamorano; Geoffery Barger; Jiani Hu; Yingbiao Xu; Karthik Praveen Prabhakaran; Ilaya R Elangovan; Jaladhar Neelavalli; Jürgen R Reichenbach
Journal:  J Magn Reson Imaging       Date:  2006-07       Impact factor: 4.813

6.  Subjective acceptance of 7 Tesla MRI for human imaging.

Authors:  Jens M Theysohn; Stefan Maderwald; Oliver Kraff; Christoph Moenninghoff; Mark E Ladd; Susanne C Ladd
Journal:  MAGMA       Date:  2007-12-07       Impact factor: 2.310

7.  Observation of the lenticulostriate arteries in the human brain in vivo using 7.0T MR angiography.

Authors:  Zang-Hee Cho; Chang-Ki Kang; Jae-Yong Han; Sang-Hoon Kim; Kyoung-Nam Kim; Suk-Min Hong; Cheol-Wan Park; Young-Bo Kim
Journal:  Stroke       Date:  2008-03-13       Impact factor: 7.914

8.  High-resolution contrast-enhanced, susceptibility-weighted MR imaging at 3T in patients with brain tumors: correlation with positron-emission tomography and histopathologic findings.

Authors:  K Pinker; I M Noebauer-Huhmann; I Stavrou; R Hoeftberger; P Szomolanyi; G Karanikas; M Weber; A Stadlbauer; E Knosp; K Friedrich; S Trattnig
Journal:  AJNR Am J Neuroradiol       Date:  2007-08       Impact factor: 3.825

9.  Longitudinal brain imaging of five malignant glioma patients treated with bevacizumab using susceptibility-weighted magnetic resonance imaging at 7 T.

Authors:  Günther Grabner; Iris Nöbauer; Katarzyna Elandt; Claudia Kronnerwetter; Adelheid Woehrer; Christine Marosi; Daniela Prayer; Siegfried Trattnig; Matthias Preusser
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10.  Added value and diagnostic performance of intratumoral susceptibility signals in the differential diagnosis of solitary enhancing brain lesions: preliminary study.

Authors:  H S Kim; G-H Jahng; C W Ryu; S Y Kim
Journal:  AJNR Am J Neuroradiol       Date:  2009-05-20       Impact factor: 3.825

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  17 in total

Review 1.  [Principles and applications of susceptibility weighted imaging].

Authors:  F T Kurz; M Freitag; H-P Schlemmer; M Bendszus; C H Ziener
Journal:  Radiologe       Date:  2016-02       Impact factor: 0.635

Review 2.  State-of-the-art MRI techniques in neuroradiology: principles, pitfalls, and clinical applications.

Authors:  Magalie Viallon; Victor Cuvinciuc; Benedicte Delattre; Laura Merlini; Isabelle Barnaure-Nachbar; Seema Toso-Patel; Minerva Becker; Karl-Olof Lovblad; Sven Haller
Journal:  Neuroradiology       Date:  2015-04-10       Impact factor: 2.804

3.  [Application of ultrahigh-field MRI in neuro-oncology].

Authors:  A Radbruch; H-P Schlemmer
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4.  Cranial fixation plates in cerebral magnetic resonance imaging: a 3 and 7 Tesla in vivo image quality study.

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5.  Contribution of susceptibility- and diffusion-weighted magnetic resonance imaging for grading gliomas.

Authors:  Jianxing Xu; Hai Xu; Wei Zhang; Jiangang Zheng
Journal:  Exp Ther Med       Date:  2018-04-02       Impact factor: 2.447

6.  Foundations of Multiparametric Brain Tumour Imaging Characterisation Using Machine Learning.

Authors:  Anne Jian; Kevin Jang; Carlo Russo; Sidong Liu; Antonio Di Ieva
Journal:  Acta Neurochir Suppl       Date:  2022

7.  Comparison of Routine Brain Imaging at 3 T and 7 T.

Authors:  Elisabeth Springer; Barbara Dymerska; Pedro Lima Cardoso; Simon Daniel Robinson; Christian Weisstanner; Roland Wiest; Benjamin Schmitt; Siegfried Trattnig
Journal:  Invest Radiol       Date:  2016-08       Impact factor: 6.016

Review 8.  High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping.

Authors:  Vivek Yedavalli; Phillip DiGiacomo; Elizabeth Tong; Michael Zeineh
Journal:  Magn Reson Imaging Clin N Am       Date:  2021-02       Impact factor: 2.266

9.  Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI.

Authors:  Carlo Russo; Sidong Liu; Antonio Di Ieva
Journal:  Med Biol Eng Comput       Date:  2021-11-02       Impact factor: 2.602

Review 10.  Clinical applications of susceptibility-weighted imaging in detecting and grading intracranial gliomas: a review.

Authors:  Wasif Mohammed; Hong Xunning; Shi Haibin; Meng Jingzhi
Journal:  Cancer Imaging       Date:  2013-04-24       Impact factor: 3.909

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