Proton resonance frequency-based thermometry for aqueous and adipose tissues

Purpose The proton resonance frequency (PRF)-based thermometry uses heating-induced phase variations to reconstruct magnetic resonance (MR) temperature maps. However, the measurements of the phase differences may be corrupted by the presence of fat due to its phase being insensitive to heat. The work aims to reconstruct the PRF-based temperature maps for tissues containing fat. Methods This work proposes a PRF-based method that eliminates the fat's phase contribution by estimating the temperature-insensitive fat vector. A vector in a complex domain represents a given voxel's magnetization from an acquired, complex MR image. In this method, a circle was fit to a time series of vectors acquired from a heated region during a heating experiment. The circle center served as the fat vector, which was then subtracted from the acquired vectors, leaving only the temperature-sensitive vectors for thermal mapping. This work was verified with the gel phantoms of 10%, 15%, and 20% fat content and the ex vivo phantom of porcine abdomen tissue during water-bath heating. It was also tested with an ex vivo porcine tissue during focused ultrasound (FUS) heating. Results A good agreement was found between the temperature measurements obtained from the proposed method and the optical fiber temperature probe in the verification experiments. In the gel phantoms, the linear regression provided a slope of 0.992 and an R-2 of 0.994. The Bland-Altman analysis gave a bias of 0.49 degrees C and a 95% confidence interval of +/- 1.60 degrees C. In the ex vivo tissue, the results of the linear regression and Bland-Altman methods provided a slope of 0.979, an intercept of 0.353, an R-2 of 0.947, and a 95% confidence interval of +/- 3.26 degrees C with a bias of -0.14 degrees C. In FUS tests, a temperature discrepancy of up to 28% was observed between the proposed and conventional PRF methods in ex vivo tissues containing fat. Conclusions The proposed PRF-based method can improve the accuracy of the temperature measurements in tissues with fat, such as breast, abdomen, prostate, and bone marrow.