Dynamical model parameter adjustments in model predictive filtering MR thermometry

Background/introduction In magnetic resonance guided focused ultrasound (MRgFUS) brain applications the fully insonified field-ofview (FOV) is ideally monitored. This can be achieved by k-space subsampling and using a dedicated reconstruction method, such as the previously described model predictive filtering (MPF) method.[1] MPF utilizes the Pennes Bioheat transfer equation (PBTE) and tissue thermal and acoustic properties determined from a low-power pretreatment heating (which ideally does not deliver any thermal dose, i.e. ΔT<2°C). The accuracy of the determined tissue parameters, and hence of the MPF reconstruction, depends on the low power heating. In this work we investigate dynamical adjustment of model parameters during heating for improved MPF temperature measurement accuracy.