Literature DB >> 27982759

MR Imaging-derived Oxygen Metabolism and Neovascularization Characterization for Grading and IDH Gene Mutation Detection of Gliomas.

Andreas Stadlbauer1, Max Zimmermann1, Melitta Kitzwögerer1, Stefan Oberndorfer1, Karl Rössler1, Arnd Dörfler1, Michael Buchfelder1, Gertraud Heinz1.   

Abstract

Purpose To explore the diagnostic performance of physiological magnetic resonance (MR) imaging of oxygen metabolism and neovascularization activity for grading and characterization of isocitrate dehydrogenase (IDH) gene mutation status of gliomas. Materials and Methods This retrospective study had institutional review board approval; written informed consent was obtained from all patients. Eighty-three patients with histopathologically proven glioma (World Health Organization [WHO] grade II-IV) were examined with quantitative blood oxygen level-dependent imaging and vascular architecture mapping. Biomarker maps of neovascularization activity (microvessel radius, microvessel density, and microvessel type indicator [MTI]) and oxygen metabolism (oxygen extraction fraction [OEF] and cerebral metabolic rate of oxygen [CMRO2]) were calculated. Receiver operating characteristic analysis was used to determine diagnostic performance for grading and detection of IDH gene mutation status. Results Low-grade (WHO grade II) glioma showed areas with increased OEF (+18%, P < .001, n = 20), whereas anaplastic glioma (WHO grade III) and glioblastoma (WHO grade IV) showed decreased OEF when compared with normal brain tissue (-54% [P < .001, n = 21] and -49% [P < .001, n = 41], respectively). This allowed clear differentiation between low- and high-grade glioma (area under the receiver operating characteristic curve [AUC], 1) for the patient cohort. MTI had the highest diagnostic performance (AUC, 0.782) for differentiation between gliomas of grades III and IV among all biomarkers. CMRO2 was decreased (P = .037) in low-grade glioma with a mutated IDH gene, and MTI was significantly increased in glioma grade III with IDH mutation (P = .013) when compared with the IDH wild-type counterparts. CMRO2 showed the highest diagnostic performance for IDH gene mutation detection in low-grade glioma (AUC, 0.818) and MTI in high-grade glioma (AUC, 0.854) and for all WHO grades (AUC, 0.899) among all biomarkers. Conclusion MR imaging-derived oxygen metabolism and neovascularization characterization may be useful for grading and IDH mutation detection of gliomas and requires only 7 minutes of extra imaging time. © RSNA, 2016 Online supplemental material is available for this article.

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Year:  2016        PMID: 27982759     DOI: 10.1148/radiol.2016161422

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  25 in total

1.  Simultaneous pH-sensitive and oxygen-sensitive MRI of human gliomas at 3 T using multi-echo amine proton chemical exchange saturation transfer spin-and-gradient echo echo-planar imaging (CEST-SAGE-EPI).

Authors:  Robert J Harris; Jingwen Yao; Ararat Chakhoyan; Catalina Raymond; Kevin Leu; Linda M Liau; Phioanh L Nghiemphu; Albert Lai; Noriko Salamon; Whitney B Pope; Timothy F Cloughesy; Benjamin M Ellingson
Journal:  Magn Reson Med       Date:  2018-04-06       Impact factor: 4.668

2.  Characterizing white matter fiber orientation effects on multi-parametric quantitative BOLD assessment of oxygen extraction fraction.

Authors:  Stephan Kaczmarz; Jens Göttler; Claus Zimmer; Fahmeed Hyder; Christine Preibisch
Journal:  J Cereb Blood Flow Metab       Date:  2019-04-05       Impact factor: 6.200

3.  Physiologic MR imaging of the tumor microenvironment revealed switching of metabolic phenotype upon recurrence of glioblastoma in humans.

Authors:  Andreas Stadlbauer; Stefan Oberndorfer; Max Zimmermann; Bertold Renner; Michael Buchfelder; Gertraud Heinz; Arnd Doerfler; Andrea Kleindienst; Karl Roessler
Journal:  J Cereb Blood Flow Metab       Date:  2019-02-07       Impact factor: 6.200

4.  Development of a Non-invasive Assessment of Hypoxia and Neovascularization with Magnetic Resonance Imaging in Benign and Malignant Breast Tumors: Initial Results.

Authors:  Andreas Stadlbauer; Max Zimmermann; Barbara Bennani-Baiti; Thomas H Helbich; Pascal Baltzer; Paola Clauser; Panagiotis Kapetas; Zsuzsanna Bago-Horvath; Katja Pinker
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

5.  Association between tissue hypoxia, perfusion restrictions, and microvascular architecture alterations with lesion-induced impairment of neurovascular coupling.

Authors:  Andreas Stadlbauer; Thomas M Kinfe; Max Zimmermann; Ilker Eyüpoglu; Nadja Brandner; Michael Buchfelder; Moritz Zaiss; Arnd Dörfler; Sebastian Brandner
Journal:  J Cereb Blood Flow Metab       Date:  2020-08-12       Impact factor: 6.200

6.  Imaging prediction of isocitrate dehydrogenase (IDH) mutation in patients with glioma: a systemic review and meta-analysis.

Authors:  Chong Hyun Suh; Ho Sung Kim; Seung Chai Jung; Choong Gon Choi; Sang Joon Kim
Journal:  Eur Radiol       Date:  2018-07-12       Impact factor: 5.315

7.  Cluster analysis of time evolution (CAT) for quantitative susceptibility mapping (QSM) and quantitative blood oxygen level-dependent magnitude (qBOLD)-based oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2 ) mapping.

Authors:  Junghun Cho; Shun Zhang; Youngwook Kee; Pascal Spincemaille; Thanh D Nguyen; Simon Hubertus; Ajay Gupta; Yi Wang
Journal:  Magn Reson Med       Date:  2019-09-10       Impact factor: 4.668

8.  Predicting Glioblastoma Response to Bevacizumab Through MRI Biomarkers of the Tumor Microenvironment.

Authors:  Andreas Stadlbauer; Karl Roessler; Max Zimmermann; Michael Buchfelder; Andrea Kleindienst; Arnd Doerfler; Gertraud Heinz; Stefan Oberndorfer
Journal:  Mol Imaging Biol       Date:  2019-08       Impact factor: 3.488

9.  Intratumoral heterogeneity of oxygen metabolism and neovascularization uncovers 2 survival-relevant subgroups of IDH1 wild-type glioblastoma.

Authors:  Andreas Stadlbauer; Max Zimmermann; Arnd Doerfler; Stefan Oberndorfer; Michael Buchfelder; Roland Coras; Melitta Kitzwögerer; Karl Roessler
Journal:  Neuro Oncol       Date:  2018-10-09       Impact factor: 12.300

10.  Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas.

Authors:  Hao Zhou; Ken Chang; Harrison X Bai; Bo Xiao; Chang Su; Wenya Linda Bi; Paul J Zhang; Joeky T Senders; Martin Vallières; Vasileios K Kavouridis; Alessandro Boaro; Omar Arnaout; Li Yang; Raymond Y Huang
Journal:  J Neurooncol       Date:  2019-01-19       Impact factor: 4.506

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