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Towards fast and highly localized spectroscopy using miniaturized coils in a 14.1T animal scanner

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Pérez Rodas,  MA
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Engelmann,  J
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Merkle,  H
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Pohmann,  R
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Former Department MRZ, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Scheffler,  K
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Pérez Rodas, M., Engelmann, J., Merkle, H., Pohmann, R., & Scheffler, K. (2016). Towards fast and highly localized spectroscopy using miniaturized coils in a 14.1T animal scanner. Poster presented at 24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2016), Singapore.


Zitierlink: https://hdl.handle.net/21.11116/0000-0000-7BA1-0
Zusammenfassung
The distinction of functional activity between cortical layers in the brain by MRI or MRS requires high spatial and temporal resolution. High spatial resolution can be achieved by increasing the gradient strength or by using the intrinsic volume selectivity of miniature coils, even in conventional animal scanner. In the present work, initial results for highly-localized spectroscopy within seconds are presented, for a phantom metabolite solution and cell cultures in a 14.1T animal scanner using a 2mm-diameter circular coil. The larger signals from the major metabolites in ~1.5µL were detected in 24sec on the phantom solution with an acceptable SNR.