Assessment of a clinically feasible Bayesian fitting algorithm using a simplified description of Chemical Exchange Saturation Transfer (CEST) imaging(120 views) Kujawa A, Kim M, Demetriou E, Anemone A, Livio Longo D, Zaiss M, Golay X
Paper type: Journal Article
, Research Support, Non-U. S. Gov'T,
Impact factor: 2.586, 5-year impact factor: 2.731
Url: Not available.
Keywords: Algorithms
, Bayes Theorem
, Computer Simulation
, Feasibility Studies
, Magnetic Fields
, Magnetic Resonance Imaging Methods
, Normal Distribution
, Phantoms, Protons
, Amide Proton Transfer
, Chemical Exchange Saturation Transfer
, Pulsed Saturation,
Affiliations: *** IBB - CNR ***
Brain Repair and Rehabilitation, University College London, 8-11 Queen Square, London WC1N 3AR, United Kingdom. Electronic address: aaron.kujawa.10@ucl.ac.uk.
Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Turin, Italy.
Institute of Biostructures and Bioimaging (IBB), National Research Council of Italy (CNR), Via Nizza 52, 10126 Torino, Italy.
Magnetic Resonance Center, Max-Planck Institute for Biological Cybernetics, Max-Planck-Ring 8-14, 72076 Tübingen, Germany.
References: Not available.
Assessment of a clinically feasible Bayesian fitting algorithm using a simplified description of Chemical Exchange Saturation Transfer (CEST) imaging
Fitting a model based on the Bloch-McConnell (BM) equations to Chemical Exchange Saturation Transfer (CEST) spectra allows for the quantification of metabolite concentration and exchange rate as well as simultaneous correction of field inhomogeneity, direct water saturation and magnetization transfer. Employing a Bayesian fitting approach permits the integration of prior information into the analysis to incorporate expected parameter distributions and to prevent over-fitting. However, the analysis can be time consuming if a general numerical solution of the BM equations is applied. In this study, we combined a Bayesian fitting algorithm with approximate analytical solutions of the BM equations to achieve feasible computational times. To evaluate the accuracy and speed of the suggested approach, phantoms including Iodipamide, Taurine and Creatine were tested in addition to simulated data with continuous-wave (CW) and pulsed saturation with Gaussian pulses. A significant reduction of computational time was achieved when fitting CW data (about 50-fold) and pulsed saturation data (more than 100-fold) with the analytical model while the estimated parameters were largely consistent with the parameters from the general numerical solution. The increased speed of the algorithm facilitates the Bayesian analysis of CEST data within clinically feasible processing times. Other analytical models valid for different parameter regimes may be employed to extend the applicability to a wider range of CEST agents.
Assessment of a clinically feasible Bayesian fitting algorithm using a simplified description of Chemical Exchange Saturation Transfer (CEST) imaging
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Assessment of a clinically feasible Bayesian fitting algorithm using a simplified description of Chemical Exchange Saturation Transfer (CEST) imaging