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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