Differential ultrasonic imaging for the characterization of lesions induced by high intensity focused ultrasound.

High intensity focused ultrasound (HIFU) is an effective technique for noninvasive local creating coagulative necrotic lesions in deep target volumes without damage to the overlaying or surrounding tissues. It is very important to detect and evaluate lesions generated by HIFU during treatment procedures. This study describes the development of several differential ultrasonic imaging techniques to characterize lesions based on estimation of relative changes in tissue properties derived from backscattered RF data. A single, spherical HIFU transducer was used to produce lesions in soft tissues. The RF signals were recorded as outputs from a modified diagnostic ultrasound system. After some preprocessing, the integrated backscatter values, which can be used as an indicator of the microstructure and backscattering property of tissues, were calculated before and after HIFU treatment. The differential integrated backscatter values were subsequently used to form images revealing the lesion areas. The differential attenuation imaging with the same RF data was also performed, which has been proposed by a few researchers. The results of the differential integrated backscatter imaging were compared with that of the differential attenuation imaging and the former method offers some advantages over the latter method. The two methods above are both based on spectrum analysis and would spend much computational time. Therefore, some simple digital differential imaging methods, including absolute difference (AD), sum absolute differences (SAD), and sum squared differences (SSD) algorithms, were also proposed to detect HIFU-induced lesions. However, these methods cannot provide the information of the degree of tissue damage. Experiments in vitro bovine muscle and liver validated the method of differential integrated backscatter imaging for the characterization of HIFU-induced lesions. And the AD, SAD, and SSD algorithms can be implemented in real-time during HIFU therapy to visualize the lesions.