Multi-echo MR thermometry using iterative separation of baseline water and fat images.

ABSTRACT

PURPOSE: To perform multi-echo water/fat separated proton resonance frequency (PRF)-shift temperature mapping. METHODS: State-of-the-art, iterative multi-echo water/fat separation algorithms produce high-quality water and fat images in the absence of heating but are not suitable for real-time imaging due to their long compute times and potential errors in heated regions. Existing fat-referenced PRF-shift temperature reconstruction methods partially address these limitations but do not address motion or large time-varying and spatially inhomogeneous B0 shifts. We describe a model-based temperature reconstruction method that overcomes these limitations by fitting a library of separated water and fat images measured before heating directly to multi-echo data measured during heating, while accounting for the PRF shift with temperature. RESULTS: Simulations in a mixed water/fat phantom with focal heating showed that the proposed algorithm reconstructed more accurate temperature maps in mixed tissues compared to a fat-referenced thermometry method. In a porcine phantom experiment with focused ultrasound heating at 1.5 Tesla, temperature maps were accurate to within 1∘ C of fiber optic probe temperature measurements and were calculated in 0.47 s per time point. Free-breathing breast and liver imaging experiments demonstrated motion and off-resonance compensation. The algorithm can also accurately reconstruct water/fat separated temperature maps from a single echo during heating. CONCLUSIONS: The proposed model-based water/fat separated algorithm produces accurate PRF-shift temperature maps in mixed water and fat tissues in the presence of spatiotemporally varying off-resonance and motion.