Abstract #5122

Assessment of a clinically feasible Bayesian fitting algorithm using a simplified description of Chemical Exchange Saturation Transfer (CEST) Imaging

Aaron Kujawa¹, Mina Kim¹, Eleni Demetriou¹, Annasofia Anemone², Dario Longo³, Moritz Zaiss⁴, and Xavier Golay¹

¹Brain Repair and Rehabilitation, University College London, London, United Kingdom, ²Molecular Biotechnology and Health Sciences, University of Torino, Turin, Italy, ³Institute of Biostructure and Bioimaging, University of Torino, Turin, Italy, ⁴Magnetic Resonance Center, Max-Planck institute for biological cybernetics, Tübingen, Germany

A Bayesian fitting algorithm was combined with analytical approximations of the Bloch-McConnell (BM) equations with the aim to considerably reduce processing time. The accuracy of the algorithm was assessed with simulated data and data from phantom experiments and compared to fit results obtained with the numerical solution of the BM equations. Continuous-wave and pulsed saturation was considered. The results showed agreement between estimates and ground truth as well as between the approximate analytical and numerical model implementations of the Bayesian algorithm. A considerable reduction of processing time was achieved.

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