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Abstract #3994

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

Mark Schuppert1, Anagha Deshmane1, Kai Herz1, Klaus Scheffler1, and Moritz Zaiss1

1High-field magnetic resonance center, Max Planck Institute for biological cybernetics, Tübingen, Germany

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.

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