Noninvasive Monitoring of Tissue Temperature Changes Induced by Focused Ultrasound Exposure using Sparse Expression of Ultrasonic Radio Frequency Echo Signals

Background: Noninvasive therapies such as focused ultrasound were developed to be used for cancer therapies, vessel bleeding, and drug delivery. The main purpose of focused ultrasound therapy is to affect regions of interest (ROI) of tissues without any injuries to surrounding tissues. In this regard, an appropriate monitoring method is required to control the treatment. Methods: This study is aimed to develop a noninvasive monitoring technique of focused ultrasound (US) treatment using sparse representation of US radio frequency (RF) echo signals. To this end, reasonable results in temperature change estimation in the tissue under focused US radiation were obtained by utilizing algorithms related to sparse optimization as orthogonal matching pursuit (OMP) and accompanying Shannon’s entropy. Consequently, ex vivo tissue experimental tests yielded two datasets, including low-intensity focused US (LIFU) and high-intensity focused US (HIFU) data. The proposed processing method analyzed the ultrasonic RF echo signal and expressed it as a sparse signal and calculated the entropy of each frame. Results: The results indicated that the suggested approach could noninvasively estimate temperature changes between 37°C and 47°C during LIFU therapy. In addition, it represented temperature changes during HIFU ablation at various powers, ranging from 10 to 130 W. The normalized mean square error of the proposed method is 0.28, approximately 2.15 on previous related methods. Conclusion: These results demonstrated that this novel proposed approach, including the combination of sparsity and Shanoon’s entropy, is more feasible and effective in temperature change estimation than its predecessors.