In vivo 1H magnetic resonance spectroscopy, T2-weighted and diffusion-weighted MRI during lithium–pilocarpine-induced status epilepticus in the rat

2004 ◽  
Vol 1030 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Pieter van Eijsden ◽  
Robbert G.E. Notenboom ◽  
Ona Wu ◽  
Pierre N.E. de Graan ◽  
Onno van Nieuwenhuizen ◽  
...  
Keyword(s):  
Status Epilepticus ◽  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Resonance Spectroscopy ◽  
Diffusion Weighted Mri ◽  
1H Magnetic Resonance Spectroscopy ◽  
Diffusion Weighted ◽  
And Diffusion

Characterisation of in vivo ovarian cancer models by quantitative 1 H magnetic resonance spectroscopy and diffusion-weighted imaging

2011 ◽  
Vol 25 (4) ◽  
pp. 632-642 ◽  
Author(s):  
Rossella Canese ◽  
Maria Elena Pisanu ◽  
Delia Mezzanzanica ◽  
Alessandro Ricci ◽  
Luisa Paris ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Diffusion Weighted Imaging ◽  
Resonance Spectroscopy ◽  
Diffusion Weighted ◽  
Cancer Models ◽  
And Diffusion

scholarly journals 1H magnetic resonance spectroscopy of 2H-to-1H exchange quantifies the dynamics of cellular metabolism in vivo

2020 ◽  
Vol 4 (3) ◽  
pp. 335-342 ◽  
Author(s):  
Laurie J. Rich ◽  
Puneet Bagga ◽  
Neil E. Wilson ◽  
Mitchell D. Schnall ◽  
John A. Detre ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Cellular Metabolism ◽  
Resonance Spectroscopy ◽  
1H Magnetic Resonance Spectroscopy

scholarly journals Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3406
Author(s):  
Elisabeth Bumes ◽  
Fro-Philip Wirtz ◽  
Claudia Fellner ◽  
Jirka Grosse ◽  
Dirk Hellwig ◽  
...  
Keyword(s):  
Machine Learning ◽  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Support Vector ◽  
Resonance Spectroscopy ◽  
Idh Mutation ◽  
1H Mrs ◽  
1H Magnetic Resonance Spectroscopy ◽  
Non Invasive

Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard 1H-magnetic resonance spectroscopy (1H-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) for optimized voxel placement in 1H-MRS. Routine 1H-magnetic resonance (1H-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the 1H-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%) and a specificity of 75.0% (95% CI, 42.9–94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo 1H-nuclear magnetic resonance (1H-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting.

scholarly journals Diffusion-weighted magnetic resonance spectroscopy enables cell-specific monitoring of astrocyte reactivity in vivo

NeuroImage ◽  
2019 ◽  
Vol 191 ◽  
pp. 457-469 ◽  
Author(s):  
Clémence Ligneul ◽  
Marco Palombo ◽  
Edwin Hernández-Garzón ◽  
María-Angeles Carrillo-de Sauvage ◽  
Julien Flament ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Resonance Spectroscopy ◽  
Diffusion Weighted
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