High-intensity focused ultrasound (HIFU) is one of the noninvasive treatment for tumors. Visualizing the treated area inside the human body is necessary to control the HIFU exposure. Localized motion imaging (LMI) using ultrasound to induce and detect tissue deformation is one technique to detect a change in tissue stiffness caused by thermal coagulation. In experiments with porcine liver, LMI has shown to detect deformation with less than 20% accuracy. We have developed a prototype feedback control system using real-time LMI. In this system, coagulation size was measured every 1 s and controlled to correspond to a targeted size. The typical size error was reduced to 14% from 35%. LMI displacements in normal and coagulated tissues were sufficiently different to discriminate between coagulated areas and noncoagulated ones after HIFU sonication and to visualize treated areas after HIFU treatment.

Visualizing an area subjected to high-intensity focused ultrasound (HIFU) therapy is necessary for controlling the amount of HIFU exposure. One of the promising monitoring methods is localized motion imaging (LMI), which estimates coagulation length by detecting the change in stiffness. In this study, we improved the accuracy of our previous LMI by dynamic cross-correlation window (DCCW) and maximum vibration amount (MVA) methods. The DCCW method was used to increase the accuracy of estimating vibration amplitude, and the MVA method was employed to increase signal–noise ratio of the decrease ratio at the coagulated area. The qualitative comparison of results indicated that the two proposed methods could suppress the effect of noise. Regarding the results of the quantitative comparison, coagulation length was estimated with higher accuracy by the improved LMI method, and the root-mean-square error (RMSE) was reduced from 2.51 to 1.69 mm.

High intensity focused ultrasound (HIFU) is a minimally invasive treatment modality for cancerous tumors. The monitoring of HIFU treatment is extremely important. Localized motion imaging (LMI) is a HIFU monitoring method basing on Harmonic motion method (HMI). It estimates the coagulation length by detecting the change of tissue stiffness. However, the previous LMI is not robust to noise, thus two techniques are employed to improve its noise robustness in this study. First, dynamic cross correlation window (DCCW) is used to obtain vibration amplitude with noise suppression. Second, vibrationfrequency band pass filter (VBPF) is employed to calculate the amount of vibration with expected frequency. The qualitative evaluation indicates that the two techniques are able to suppress the affection of noise on the vibration amplitude and vibration amount, respectively. Furthermore, the quantitative comparison demonstrates that the improved LMI is able to give higher accuracy of coagulation length estimation than the previous LMI, and it reduces the root mean square error (RMSE) from 2.52 to 1.84 mm. In this article, an improved noise robust LMI is proposed for monitoring HIFU treatment.

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Background/introductionUltrasound imaging provides real-time feedback for highly accurate positioning and dosing control. In addition, spatial restriction of high-intensity focused ultrasound (HIFU) transducer position in the ultrasound image-guided system is less than that in the case of MRI-guided system. Therefore, wider beam approaching path can be used in the ultrasound image-guided system. To shorten the total treatment time, reducing the cooling time between sonication intervals is essential. Using a wide approach path promotes a reduction in both the cooling time and the risk of heat deposition to the body surface. The array in our preclinical HIFU system is supported by a 5-axis robotic system that enables motion with a pivot fixed at the focal point. In this report, we describe a HIFU beam imaging system that provides highly accurate pivoting motion and coagulation monitoring in real-time for dose control during HIFU treatment. MethodsA 256-element concave array HIFU operating at 2 MHz was supported by a parallel link robot in a water tank. A 5-MHz linear imaging array was fixed in a hole in the center of the HIFU array. The HIFU beam was affected by acoustic inhomogeneous media. Beam refraction during pivoting motions can cause focal shift and reductions in average focal intensity. We thus developed an HIFU beam imaging method capable of adjusting the focal point in varying approach paths. In the HIFU beam imaging process, backscattered echoes of ultrasound pulses transmitted from the HIFU transducer were received by the imaging array, and an HIFU beam profile was visualized. The imaging array was connected to an ultrasound imaging scanner with a radio frequency (RF) data acquisition system and a ring buffer memory. The ring buffer memory made it possible for the signal processing operations to access the RF data during the acquiring and recording process. Thermal coagulation was able to be detected based on changes in stiffness of the focal tissue. In this prototype system, stiffness change could be monitored based on observation of focal tissue oscillation caused by the modulated HIFU radiation force. Results and conclusionsThe accuracy of the pivoting motion in our prototype system was evaluated by measuring the precessional radius of the focal point. The motion error was sufficiently-smaller than the width of the HIFU beam. To increase the positioning accuracy of the focal point estimated by the visualized HIFU beam, extraction method of HIFU beam from the distribution of scatter points was tested. For this purpose, the HIFU focal point was scanned and the fixed pattern noise reflecting scatters was strongly suppressed. In coagulation monitoring, the maximum and mean computation times for stiffness estimations from tissue oscillation caused by the acoustic radiation force were 0.85 s and 0.6 s, respectively. To measure tissue oscillation, 26 frames of data were obtained within 0.1 s; therefore, tissue coagulation monitoring with a sampling rate of 1 s was achieved in our prototype system. This sam...