Flip angle optimisation using an in-vivo T1 distribution-weighted approach based on the Cramer-Rao lower bound theory for accurate T1 quantification

including the proton density, machine-dependent gain factor and the echo term. Optimisation of flip angles when imaging samples with a large R1 range of values has been far from trivial and little work has been published on this subject [1, 2]. During the optimisation, it is important that the actual distribution of R1 values in the image sample is taken into account. We propose a novel flip angle optimisation approach, based on the Cramer-Rao lower bound (CRLB) theory, which is weighted by the probability distribution of the R1 range of interest.