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Abstract #0143

Denoising of Z-spectra for stable CEST MRI using principal component analysis

Johannes Breitling1,2,3, Anagha Deshmane4, Steffen Goerke1, Kai Herz4, Mark E. Ladd1,2,5, Klaus Scheffler4,6, Peter Bachert1,2, and Moritz Zaiss4

1Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany, 3Max Max Planck Institute for Nuclear Physics, Heidelberg, Germany, 4High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 5Faculty of Medicine, University of Heidelberg, Heidelberg, Germany, 6Department of Biomedical Magnetic Resonance, Eberhard-Karls University Tübingen, Tübingen, Germany

Chemical exchange saturation transfer (CEST) MRI allows for the indirect detection of low-concentration biomolecules by their saturation transfer to the abundant water pool. However, reliable quantification of CEST effects remains challenging and requires a high image signal-to-noise ratio. In this study, we show that principle component analysis can provide a denoising capability which is comparable or better than 6-fold averaging. Principle component analysis allows identifying similarities across all noisy Z-spectra, and thus, extracting the relevant information. The resulting denoised Z-spectra provide a more stable basis for quantification of selective CEST effects, without requiring additional measurements.

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