Ultrasound Monitoring of Simultaneous high-intensity focused ultrasound (HIFU) therapy using minimum-peak-sidelobe coded excitation.

Bipolar sequences can be readily transmitted by ultrasound (US) pulser hardware with the full driving voltage to boost the echo magnitude in B-mode monitoring of HIFU treatment. In this study, a novel single-transmit bipolar sequence with minimum-peak-sidelobe (MPS) level is developed not only to restore the image quality of US monitoring but also remove acoustic interference from simultaneous HIFU transmission. The proposed MPS code is designed with an equal number of positive and negative bits and the bit duration should be an integer multiple of the period of the HIFU waveform. In addition, different permutations of code sequence are searched in order to obtain the optimal encoding. The received imaging echo is firstly decoded by matched filtering to cancel HIFU interference and to enhance the echo magnitude of US monitoring. Then, Wiener filtering is applied as the second-stage pulse compression to improve the final image quality. Simulations and phantom experiments are performed to compare the single-transmit MPS decoding with conventional two-transmit methods such as pulse-inversion subtraction (PIS) and Golay decoding for their performance in simultaneous US monitoring of HIFU treatment. Results show that the MPS decoding effectively removes HIFU interference even in the presence of tissue motion. The image quality of PIS and Golay decoding, on the other hand, is compromised by the uncancelled HIFU components due to tissue motion. Simultaneous US monitoring of tissue ablation using the proposed MPS decoding has also demonstrated to be feasible in ex-vivo experiments. Compared to the notch filtering that also allows single-transmit HIFU elimination, the MPS decoding is preferrable because it does not suffer from the tradeoff between residual HIFU and speckle deterioration in US monitoring images.

Suppressing HIFU interference in ultrasound images using 1D U-Net-based neural networks.

Objective.One big challenge with high-intensity focused ultrasound (HIFU) is that the intense acoustic interference generated by HIFU irradiation overwhelms the B-mode monitoring images, compromising monitoring effectiveness. This study aims to overcome this problem using a one-dimensional (1D) deep convolutional neural network.Approach. U-Net-based networks have been proven to be effective in image reconstruction and denoising, and the two-dimensional (2D) U-Net has already been investigated for suppressing HIFU interference in ultrasound monitoring images. In this study, we propose that the one-dimensional (1D) convolution in U-Net-based networks is more suitable for removing HIFU artifacts and can better recover the contaminated B-mode images compared to 2D convolution.Ex vivoandinvivoHIFU experiments were performed on a clinically equivalent ultrasound-guided HIFU platform to collect image data, and the 1D convolution in U-Net, Attention U-Net, U-Net++, and FUS-Net was applied to verify our proposal.Main results.All 1D U-Net-based networks were more effective in suppressing HIFU interference than their 2D counterparts, with over 30% improvement in terms of structural similarity (SSIM) to the uncontaminated B-mode images. Additionally, 1D U-Nets trained usingex vivodatasets demonstrated better generalization performance ininvivoexperiments.Significance.These findings indicate that the utilization of 1D convolution in U-Net-based networks offers great potential in addressing the challenges of monitoring in ultrasound-guided HIFU systems.

Numerical studies on shortening the duration of HIFU ablation therapy and their experimental validation.

High Intensity Focused Ultrasound (HIFU) is used in clinical practice for thermal ablation of malignant and benign solid tumors located in various organs. One of the reason limiting the wider use of this technology is the long treatment time resulting from i.a. the large difference between the size of the focal volume of the heating beam and the size of the tumor. Therefore, the treatment of large tumors requires scanning their volume with a sequence of single heating beams, the focus of which is moved in the focal plane along a specific trajectory with specific time and distance interval between sonications. To avoid an undesirable increase in the temperature of healthy tissues surrounding the tumor during scanning, the acoustic power and exposure time of each HIFU beam as well as the time intervals between sonications should be selected in such a way as to cover the entire volume of the tumor with necrosis as quickly as possible. This would reduce the costs of treatment. The aim of this study was to quantitatively evaluate the hypothesis that selecting the average acoustic power and exposure time for each individual heating beam, as well as the temporal intervals between sonications, can significantly shorten treatment time. Using 3D numerical simulations, the dependence of the duration of treatment of a tumor with a diameter of 5 mm or 9 mm (requiring multiple exposure to the HIFU beam) on the sonication parameters (acoustic power, exposure time) of each single beam capable of delivering the threshold thermal dose (CEM43 = 240 min) to the treated tissue volume was examined. The treatment duration was determined as the sum of exposure times to individual beams and time intervals between sonications. The tumor was located inside the ex vivo tissue sample at a depth of 12.6 mm. The thickness of the water layer between the HIFU transducer and the tissue was 50 mm. The sonication and scanning parameters selected using the developed algorithm shortened the duration of the ablation procedure by almost 14 times for a 5-mm tumor and 20 times for a 9-mm tumor compared to the duration of the same ablation plan when a HIFU beam was used of a constant acoustic power, constant exposure time (3 s) and constant long time intervals (120 s) between sonications. Results of calculations of the location and size of the necrotic lesion formed were experimentally verified on ex vivo pork loin samples, showing good agreement between them. In this way, it was proven that the proper selection of sonication and scanning parameters for each HIFU beam allows to significantly shorten the time of HIFU therapy.

Monitoring MR-guided high intensity focused ultrasound therapy using transient supersonic shear wave MR-elastography.

Objective.The aim of the paper is to propose an all-in-one method based on magnetic resonance-supersonic shear wave imaging (MR-SSI) and proton resonance frequency shift (PRFS) to monitor high intensity focused ultrasound (HIFU) thermal ablations.Approach.Mechanical properties have been shown to be related to tissue damage induced by thermal ablations. Monitoring elasticity in addition to temperature changes may help in ensuring the efficacy and the accuracy of HIFU therapies. For this purpose, an MR-SSI method has been developed where the ultrasonic transducer is used for both mechanical wave generation and thermal ablation. Transient quasi-planar shear waves are generated using the acoustic radiation force, and their propagation is monitored in motion-sensitized phase MR images. Using a single-shot gradient-echo echo-planar-imaging sequence, MR images can be acquired at a sufficiently high temporal resolution to provide an update of PRFS thermometry and MR-SSI elastography maps in real time.Main results.The proposed method was first validated on a calibrated elasticity phantom, in which both the possibility to detect inclusions with different stiffness and repeatability were demonstrated. The standard deviation between the 8 performed measurements was 2% on the background of the phantom and 11%, at most, on the inclusions. A second experiment consisted in performing a HIFU heating in a gelatin phantom. The temperature increase was estimated to be 9 °C and the shear modulus was found to decrease from 2.9 to 1.8 kPa, reflecting the gel softening around the HIFU focus, whereas it remained steady in non-heated areas.Significance.The proposed MR-SSI technique allows monitoring HIFU ablations using thermometry and elastography simultaneously, without the need for an additional external mechanical exciter such as those used in MR elastography.

Real-time and multimodality image-guided intelligent HIFU therapy for uterine fibroid.

Rationale: High-intensity focused ultrasound (HIFU) therapy represents a noninvasive surgical approach to treat uterine fibroids. The operation of HIFU therapy relies on the information provided by medical images. In current HIFU therapy, all operations such as positioning of the lesion in magnetic resonance (MR) and ultrasound (US) images are manually performed by specifically trained doctors. Manual processing is an important limitation of the efficiency of HIFU therapy. In this paper, we aim to provide an automatic and accurate image guidance system, intelligent diagnosis, and treatment strategy for HIFU therapy by combining multimodality information. Methods: In intelligent HIFU therapy, medical information and treatment strategy are automatically processed and generated by a real-time image guidance system. The system comprises a novel multistage deep convolutional neural network for preoperative diagnosis and a nonrigid US lesion tracking procedure for HIFU intraoperative image-assisted treatment. In the process of intelligent therapy, the treatment area is determined from the autogenerated lesion area. Based on the autodetected treatment area, the HIFU foci are distributed automatically according to the treatment strategy. Moreover, an image-based unexpected movement warning and other physiological monitoring are used during the intelligent treatment procedure for safety assurance. Results: In the experiment, we integrated the intelligent treatment system on a commercial HIFU treatment device, and eight clinical experiments were performed. In the clinical validation, eight randomly selected clinical cases were used to verify the feasibility of the system. The results of the quantitative experiment indicated that our intelligent system met the HIFU clinical tracking accuracy and speed requirements. Moreover, the results of simulated repeated experiments confirmed that the autodistributed HIFU focus reached the level of intermediate clinical doctors. Operations performed by junior- or middle-level operators with the assistance of the proposed system can reach the level of operation performed by senior doctors. Various experiments prove that our proposed intelligent HIFU therapy process is feasible for treating common uterine fibroid cases. Conclusion: We propose an intelligent HIFU therapy for uterine fibroid which integrates multiple medical information processing procedures. The experiment results demonstrated that the proposed procedures and methods can achieve monitored and automatic HIFU diagnosis and treatment. This research provides a possibility for intelligent and automatic noninvasive therapy for uterine fibroid.

Robot-assisted ultrasound navigation platform for 3D HIFU treatment planning: Initial evaluation for conformal interstitial ablation.

Interstitial Ultrasound-guided High Intensity Focused Ultrasound (USgHIFU) therapy has the potential to deliver ablative treatments which conform to the target tumor. In this study, a robot-assisted US-navigation platform has been developed for 3D US guidance and planning of conformal HIFU ablations. The platform was used to evaluate a conformal therapeutic strategy associated with an interstitial dual-mode USgHIFU catheter prototype (64 elements linear-array, measured central frequency f = 6.5 MHz), developed for the treatment of HepatoCellular Carcinoma (HCC). The platform included a 3D navigation environment communicating in real-time with an open research dual-mode US scanner/HIFU generator and a robotic arm, on which the USgHIFU catheter was mounted. 3D US-navigation was evaluated in vitro for guiding and planning conformal HIFU ablations using a tumor-mimic model in porcine liver. Tumor-mimic volumes were then used as targets for evaluating conformal HIFU treatment planning in simulation. Height tumor-mimics (ovoid- or disc-shaped, sizes: 3-29 cm3) were created and visualized in liver using interstitial 2D US imaging. Robot-assisted spatial manipulation of these images and real-time 3D navigation allowed reconstructions of 3D B-mode US images for accurate tumor-mimic volume estimation (relative error: 4 ± 5%). Sectorial and full-revolution HIFU scanning (angular sectors: 88-360°) could both result in conformal ablations of the tumor volumes, as soon as their radii remained ≤ 24 mm. The presented US navigation-guided HIFU procedure demonstrated advantages for developing conformal interstitial therapies in standard operative rooms. Moreover, the modularity of the developed platform makes it potentially useful for developing other HIFU approaches.

The Correction of Focal Point Displacement Caused by the Refraction of the Beams in High-Intensity Focused Ultrasound.

Nowadays, high-intensity focused ultrasound (HIFU) as nonionizing radiation is used for cancer treatment. Basically, the function of HIFU is similar to conventional ultrasound. Ultrasound beams are perverted when crossing the border of different environments. This decreases the beam's focus within the tumor and may induce damage to the normal tissues. In this study, we aim to develop appropriate algorithms for correcting the focal point displacement duced by the beam's refraction. First, the level of displacement due to difference in two specific tissues was calculated for one element of the transducer and, then, it extended to all of the elements. Finally, a new focal point was calculated, which is considered as a desired focal point of the transducer in which the maximum temperature occurs. Designed algorithms were implemented in MATLAB software. A HIFU simulator (by the Food and Drug Administration of US) was used to simulate HIFU therapy. The proposed algorithm was tested on four models with two layers of tissue. Results illustrated the use of proposed algorithm results for 78% correction in the focal point displacement. In addition, it was noted that a part of this displacement was caused by the absorption of the beam in the tissues. The proposed algorithm can significantly correct the focal point displacement in HIFU therapy and consequently prevent damage to the normal tissues.