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  In vivo online magnetic resonance quantification of absolute metabolite concentrations in microdialysate.

Glöggler, S., Rizzitelli, S., Pinaud, N., Raffard, G., Zhendre, V., Bouchaud, V., et al. (2016). In vivo online magnetic resonance quantification of absolute metabolite concentrations in microdialysate. Scientific Reports, 6: 36080. doi:10.1038/srep36080.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-2EAD-B Version Permalink: http://hdl.handle.net/21.11116/0000-0000-2EB1-5
Genre: Journal Article

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Glöggler, S.1, Author              
Rizzitelli, S., Author
Pinaud, N., Author
Raffard, G., Author
Zhendre, V., Author
Bouchaud, V., Author
Sanchez, S., Author
Radecki, G., Author
Ciobanu, L., Author
Wong, A., Author
Crémillieux, Y., Author
Affiliations:
1Research Group of NMR Signal Enhancement, MPI for Biophysical Chemistry, Max Planck Society, ou_2396691              

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 Abstract: In order to study metabolic processes in animal models of diseases and in patients, microdialysis probes have evolved as powerful tools that are minimally invasive. However, analyses of microdialysate, performed remotely, do not provide real-time monitoring of microdialysate composition. Microdialysate solutions can theoretically be analyzed online inside a preclicinal or clinical MRI scanner using MRS techniques. Due to low NMR sensitivity, acquisitions of real-time NMR spectra on very small solution volumes (μL) with low metabolite concentrations (mM range) represent a major issue. To address this challenge we introduce the approach of combining a microdialysis probe with a custom-built magnetic resonance microprobe that allows for online metabolic analysis (1H and 13C) with high sensitivity under continuous flow conditions. This system is mounted inside an MRI scanner and allows performing simultaneously MRI experiments and rapid MRS metabolic analysis of the microdialysate. The feasibility of this approach is demonstrated by analyzing extracellular brain cancer cells (glioma) in vitro and brain metabolites in an animal model in vivo. We expect that our approach is readily translatable into clinical settings and can be used for a better and precise understanding of diseases linked to metabolic dysfunction.

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Language(s): eng - English
 Dates: 2016-11-042016
 Publication Status: Published in print
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 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1038/srep36080
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Title: Scientific Reports
Source Genre: Journal
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Pages: 8 Volume / Issue: 6 Sequence Number: 36080 Start / End Page: - Identifier: -