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Data-Driven Spectral Feature Extraction in 9.4T CEST MRI data of the human brain

MPS-Authors
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Schuppert,  M
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons215996

Deshmane,  A
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons216025

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

/persons/resource/persons84187

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

/persons/resource/persons214560

Zaiss,  M
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

http://indexsmart.mirasmart.com/ISMRM2019/PDFfiles/3994.html
(Abstract)

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Citation

Schuppert, M., Deshmane, A., Herz, K., Scheffler, K., & Zaiss, M. (2019). Data-Driven Spectral Feature Extraction in 9.4T CEST MRI data of the human brain. Poster presented at 27th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2019), Montréal, QC, Canada.


Cite as: https://hdl.handle.net/21.11116/0000-0003-9703-F
Abstract
Model-based extraction of features, e.g. Lorentzian fitting of Z-spectra, in CEST MRI can be limited by the underlying model assumptions. Here we analyzed high spectral resolution Z-spectra acquired at 9.4T in five healthy subjects and one tumor patient using principal component analysis, a purely data-driven statistical procedure. Projection of Z-spectra onto principle components from a group of healthy subjects provides several relevant contrasts which reveal anatomical detail and correlate with Gadolinium uptake signatures in a brain tumor patient.