Regularized referenceless temperature estimation in PRF-shift MR thermometry

In PRF-shift MR thermometry, temperature rises induced by thermal therapy can be estimated from the phase differences between tissue in a heated state and in a pretreatment state. To overcome errors caused by motion, referenceless methods have been proposed that estimate temperature from a single image. Compared to baseline subtraction, these methods are not susceptible to inter-frame motion, and produce accurate temperature estimates in moving tissues. However, referenceless methods could be improved if they did not require knowledge of the hot spot´s location, or if they took into account underlying noise statistics. Here we introduce a regularized approach to referenceless PRF-shift thermometry that is statistically motivated, generalizes readily to multiple receive coils, and does not require knowledge of the hot spot´s location.