Perturbation method for the second-order nonlinear effect of focused acoustic field around a scatterer in an ideal fluid

Nonlinear Acoustic Modeling and Measurements during the Fatigue Process in Metals

The nonlinear spring model combined with dislocation dipole theory was applied to describe the acoustic nonlinearity during the fatigue process in metals. The spring stiffness changes with fatigue degree. For the early stage, spring stiffness approaches infinity, and the heavier nonlinearity mainly results from the increase of dislocation density. Further fatigue leads to the occurrence of micro-cracks, during which spring stiffness begins to decrease. Abundant micro-crack sprouting accelerates the crack's expansion, and spring stiffness drops quickly, which causes the obvious decline in the transmitted harmonic amplitudes. Solutions obtained from the nonlinear wave equation with dislocation terms were added into the spring model. Varying spring stiffness was chosen for simulating the fatigue process. Then, nonlinear harmonic variation during this process was observed, which was classified into three stages: (I) the early dislocation fatigue stage; (II) the micro-crack sprouting stage; (III) the crack expansion stage. Nonlinear acoustic measurements were carried out on an aluminum alloy specimen during its fatigue process until cracks could be seen clearly. Harmonic variations in experiments can also be classified into the same three stages as the numerical results, which provides a theoretical and experimental reference for fatigue evaluation in metals using the nonlinear acoustic method.

The Influence of Dynamic Tissue Properties on HIFU Hyperthermia: A Numerical Simulation Study

Accurate temperature and thermal dose prediction are crucial to high-intensity focused ultrasound (HIFU) hyperthermia, which has been used successfully for the non-invasive treatment of solid tumors. For the conventional method of prediction, the tissue properties are usually set as constants. However, the temperature rise induced by HIFU irradiation in tissues will cause changes in the tissue properties that in turn affect the acoustic and temperature field. Herein, an acoustic–thermal coupling model is presented to predict the temperature and thermal damage zone in tissue in terms of the Westervelt equation and Pennes bioheat transfer equation, and the individual influence of each dynamic tissue property and the joint effect of all of the dynamic tissue properties are studied. The simulation results show that the dynamic acoustic absorption coefficient has the greatest influence on the temperature and thermal damage zone among all of the individual dynamic tissue properties. In addition, compared with the conventional method, the dynamic acoustic absorption coefficient leads to a higher focal temperature and a larger thermal damage zone; on the contrary, the dynamic blood perfusion leads to a lower focal temperature and a smaller thermal damage zone. Moreover, the conventional method underestimates the focal temperature and the thermal damage zone, compared with the simulation that was performed using all of the dynamic tissue properties. The results of this study will be helpful to guide the doctors to develop more accurate clinical protocols for HIFU treatment planning.

Ultrasound harmonic enhanced imaging using eigenspace-based coherence factor

Tissue harmonic imaging (THI) utilizes harmonic signals generating within the tissue as the result of nonlinear acoustic wave propagation. With inadequate transmitting acoustic energy, THI is incapable to detect the small objects since poor harmonic signals have been generated. In most cases, high transmission energy cannot be guaranteed because of the imaging safety issue or specific imaging modality such as the plane wave imaging (PWI). Discrimination of small point targets such as calcification, however, is particularly important in the ultrasound diagnosis. Few efforts have been made to pursue the THI with high resolution and good small target visibility at the same time. In this paper, we proposed a new eigenspace-based coherence factor (ESBCF) beamformer to solve this problem. A new kind of coherence factor (CF), named as ESBCF, is firstly proposed to detect the point targets. The detected region-of-interest (ROI) is then enhanced adaptively by using a newly developed beamforming method. The ESBCF combines the information from signal eigenspace and coherence factor by expanding the CF to the covariance matrix of signal. Analogous to the image processing but in the radio frequency (RF) data domain, the proposed method fully utilizes the information from the fundamental and harmonic components. The performance of the proposed method is demonstrated by simulation and phantom experiments. The improvement of the point contrast ratio (PCR) is 7.6dB in the simulated data, and 6.0dB in the phantom experiment. Thanks to the improved small point detection ability of the ESBCF, the proposed beamforming algorithm can enhance the PCR considerably and maintain the high resolution of the THI at the same time.