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Abstract #3619

Bayesian model selection of Time Encoded Arterial Spin Labelling: effect of T1 and dispersion

Marco Castellaro1, Erica Silvestri1, Ilaria Boscolo Galazzo2, Matteo Tonietto1, Alessandro Palombit1, Francesca Benedetta Pizzini2, Stefania Montemezzi2, Enrico Grisan1, Matthias J.P. Van Osch3, and Alessandra Bertoldo1

1Department of Information Engineering, University of Padova, Padova, Italy, 2University of Verona, Verona, Italy, 3Radiology, LUMC, Gorter Center for high field MRI, Leiden, Netherlands

Time-Encoded Arterial Spin Labelling (TE-ASL) has been proposed as a tool to efficiently sample the kinetics of the ASL signal. We propose a model comparison based on Bayesian Model Selection (BMS), to provide insights on which is the optimal model for the quantification of TE-ASL. Our results show how important it is to consider both T1 decay and dispersion in the quantification process. When mainly interested in GM, it is advisable to incorporate the dispersion of the bolus in the model with a Gamma kernel dispersion model and to use a single T1 value of 1.3s.

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