Treatable focal region modulated by double excitation signal superimposition to realize platform temperature distribution during transcranial brain tumor therapy with high-intensity focused ultrasound

Recently, the phase compensation technique has allowed the ultrasound to propagate through the skull and focus into the brain. However, the temperature evolution during treatment is hard to control to achieve effective treatment and avoid over-high temperature. Proposed in this paper is a method to modulate the temperature distribution in the focal region. It superimposes two signals which focus on two preset different targets with a certain distance. Then the temperature distribution is modulated by changing triggering time delay and amplitudes of the two signals. The simulation model is established based on an 82-element transducer and computed tomography （CT） data of a volunteer＇s head. A finite- difference time-domain （FDTD） method is used to calculate the temperature distributions. The results show that when the distances between the two targets respectively are 7.5-12.5 mm on the acoustic axis and 2.0-3.0 mm in the direction perpendicular to the acoustic axis, a focal region with a uniform temperature distribution （64-65 ℃） can be created. Moreover, the volume of the focal region formed by one irradiation can be adjusted （26.8-266.7 mm3） along with the uniform temperature distribution. This method may ensure the safety and efficacy of HIFU brain tumor therapy.

Gaussian shaper for nuclear pulses based on multilevel cascade convolution

For nuclear measurements,it is necessary to obtain accurate information from nuclear pulses,which should be obtained by first shaping the pulses outputted by the detectors.However,commonly used pulse-shaping algorithms have certain problems.For example,certain pulse-shaping algorithms have long dead-times in high-counting-rate environments or are difficult to achieve in digital systems.Gaussian signals are widely used in analog nuclear instruments owing to their symmetry and completeness.A Gaussian signal is usually implemented by using a multilevel S–K filter in series or in parallel.It is difficult to construct a real-time digital Gaussian filter for the complex Gaussian filtering algorithm.Based on the multilevel cascade convolution,a pulse-shaping algorithm for double exponential signals is proposed in this study,which,in addition to double exponential signals,allows more complex output signal models to be used in the new algorithm.The proposed algorithm can be used in high-counting-rate environments and has been implemented in an FPGA with fewer multipliers than those required in other traditional Gaussian pulse-shaping algorithms.The offline processing results indicated that the average peak base width of the output-shaped pulses obtained using the proposed algorithm was reduced compared with that obtained using the traditional Gaussian pulse-shaping algorithm.Experimental results also demonstrated that signal-to-noise ratios and energy resolutions were improved,particularly for pulses with a low energy.The energy resolution was improved by 0.1–0.2%while improving the counting rate.