Cargando…

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

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. Microdialys...

Descripción completa

Detalles Bibliográficos
Autores principales: Glöggler, Stefan, Rizzitelli, Silvia, Pinaud, Noël, Raffard, Gérard, Zhendre, Vanessa, Bouchaud, Véronique, Sanchez, Stéphane, Radecki, Guillaume, Ciobanu, Luisa, Wong, Alan, Crémillieux, Yannick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5095764/
https://www.ncbi.nlm.nih.gov/pubmed/27811972
http://dx.doi.org/10.1038/srep36080
Descripción
Sumario: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 ((1)H and (13)C) 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.