English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Poster

Model-free generation of CEST contrast using principal components of Z-spectra at 3 T

MPS-Authors
/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/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;

/persons/resource/persons216082

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/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;

Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Deshmane, A., Zaiss, M., Schuppert, M., Herz, K., & Scheffler, K. (2019). Model-free generation of CEST contrast using principal components of Z-spectra at 3 T. Poster presented at 27th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2019), Montréal, QC, Canada.


Cite as: http://hdl.handle.net/21.11116/0000-0003-96D7-1
Abstract
Fitting of spectrally selective CEST contrasts requires models with limiting assumptions. Snapshot CEST allows us to densely sample the Z-spectrum with rapid volumetric imaging within a clinically feasible scan time. With over 60k spectra available per subject, statistically-driven analysis methods are now possible. Here we demonstrate that principle component analysis can be used for model-free analysis of spectral features. 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.