Literature DB >> 19785020

Pattern recognition of MRSI data shows regions of glioma growth that agree with DTI markers of brain tumor infiltration.

Alan J Wright1, G Fellows, T J Byrnes, K S Opstad, D J O McIntyre, J R Griffiths, B A Bell, C A Clark, T R Barrick, F A Howe.   

Abstract

Gliomas are the most common primary brain tumors and the majority are highly malignant, with one of the worst prognoses for patients. Gliomas are characterized by invasive growth into normal brain tissue that makes complete surgical resection and accurate radiotherapy planning extremely difficult. We have performed independent component analysis of magnetic resonance spectroscopy imaging data from human gliomas to segment brain tissue into tumor core, tumor infiltration, and normal brain, with confirmation by diffusion tensor imaging analysis. Our data are consistent with previous studies that compared anomalies in isotropic and anisotropic diffusion images to determine regions of potential glioma infiltration. We show that coefficients of independent components can be used to create colored images for easy visual identification of regions of infiltrative tumor growth. (c) 2009 Wiley-Liss, Inc.

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Year:  2009        PMID: 19785020     DOI: 10.1002/mrm.22163

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  13 in total

1.  Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen.

Authors:  Sarah J Nelson; Achuta K Kadambi; Ilwoo Park; Yan Li; Jason Crane; Marram Olson; Annette Molinaro; Ritu Roy; Nicholas Butowski; Soonmee Cha; Susan Chang
Journal:  Neuro Oncol       Date:  2017-03-01       Impact factor: 12.300

2.  A combined diffusion tensor imaging and Ki-67 labeling index study for evaluating the extent of tumor infiltration using the F98 rat glioma model.

Authors:  Kai Wang; Tingting Ha; Xuzhu Chen; Shaowu Li; Lin Ai; Jun Ma; Jianping Dai
Journal:  J Neurooncol       Date:  2018-01-02       Impact factor: 4.130

3.  Proton MRS imaging in pediatric brain tumors.

Authors:  Maria Zarifi; A Aria Tzika
Journal:  Pediatr Radiol       Date:  2016-05-27

4.  Quantitative MR imaging and spectroscopy of brain tumours: a step forward?

Authors:  Dita Wagnerova; Vit Herynek; Alberto Malucelli; Monika Dezortova; Josef Vymazal; Dusan Urgosik; Martin Syrucek; Filip Jiru; Antonin Skoch; Robert Bartos; Martin Sames; Milan Hajek
Journal:  Eur Radiol       Date:  2012-06-12       Impact factor: 5.315

Review 5.  Imaging of brain tumors: MR spectroscopy and metabolic imaging.

Authors:  Alena Horská; Peter B Barker
Journal:  Neuroimaging Clin N Am       Date:  2010-08       Impact factor: 2.264

Review 6.  Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI.

Authors:  Sarah J Nelson
Journal:  NMR Biomed       Date:  2011-04-27       Impact factor: 4.044

Review 7.  MR-visible lipids and the tumor microenvironment.

Authors:  E James Delikatny; Sanjeev Chawla; Daniel-Joseph Leung; Harish Poptani
Journal:  NMR Biomed       Date:  2011-04-27       Impact factor: 4.044

8.  Main genetic differences in high-grade gliomas may present different MR imaging and MR spectroscopy correlates.

Authors:  Ángela Bernabéu-Sanz; María Fuentes-Baile; Cristina Alenda
Journal:  Eur Radiol       Date:  2020-09-01       Impact factor: 5.315

Review 9.  Functional imaging in adult and paediatric brain tumours.

Authors:  Andrew C Peet; Theodoros N Arvanitis; Martin O Leach; Adam D Waldman
Journal:  Nat Rev Clin Oncol       Date:  2012-11-13       Impact factor: 66.675

10.  Differential Effects of a Left Frontal Glioma on the Cortical Thickness and Complexity of Both Hemispheres.

Authors:  Ryuta Kinno; Yoshihiro Muragaki; Takashi Maruyama; Manabu Tamura; Kyohei Tanaka; Kenjiro Ono; Kuniyoshi L Sakai
Journal:  Cereb Cortex Commun       Date:  2020-06-27
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