Motion compensation for ultrasound thermal imaging using motion-mapped reference model: an in vivo mouse study

Ultrasound (US)-based thermal imaging is very sensitive to tissue motion, which is a major obstacle to apply US temperature monitoring to noninvasive thermal therapies of in vivo subjects. In this study, we aim to develop a motion compensation method for stable US thermal imaging in in vivo subjects. Based on the assumption that the major tissue motion is approximately periodic caused by respiration, we propose a motion compensation method for change in backscattered energy (CBE) with multiple reference frames. Among the reference frames, the most similar reference to the current frame is selected to subtract the respiratory-induced motions. Since exhaustive reference searching in all stored reference frames can impede real-time thermal imaging, we improve the reference searching by using a motion-mapped reference model. We tested our method in six tumor-bearing mice with high intensity focused ultrasound (HIFU) sonication in the tumor volume until the temperature had increased by 7°C. The proposed motion compensation was evaluated by root-mean-square-error (RMSE) analysis between the estimated temperature by CBE and the measured temperature by thermocouple. As a result, the mean ±SD RMSE in the heating range was 1.1±0.1°C with the proposed method, while the corresponding result without motion compensation was 4.3±2.6°C. In addition, with the idea of motion-mapped reference frame, total processing time to produce a frame of thermal image was reduced in comparison with the exhaustive reference searching, which enabled the motion-compensated thermal imaging in 15 frames per second with 150 reference frames under 50% HIFU duty ratio.