Full modelling of high-intensity focused ultrasound and thermal heating in the kidney using realistic patient models

Objective: High-intensity focused ultrasound (HIFU) therapy can be used for non-invasive treatment of kidney (renal) cancer, but the clinical outcomes have been variable. In this study, the efficacy of renal HIFU therapy was studied using nonlinear acoustic and thermal simulations in three patients. Methods: The acoustic simulations were conducted with and without refraction in order to investigate its effect on the shape, size and pressure distribution at the focus. The values for the attenuation, sound speed, perfusion and thermal conductivity of the kidney were varied over the reported ranges to determine the effect of variability on heating. Furthermore, the phase aberration was studied in order to quantify the underlying phase shifts using a second order polynomial function. Results: The ultrasound field intensity was found to drop on average 11.1 dB with refraction and 6.4 dB without refraction. Reflection at tissue interfaces was found to result in a loss less than 0.1 dB. Focal point splitting due to refraction significantly reduced the heating efficacy. Perfusion did not have a large effect on heating during short sonication durations. Small changes in temperature were seen with varying attenuation and thermal conductivity, but no visible changes were present with sound speed variations. The aberration study revealed an underlying trend in the spatial distribution of the phase shifts. Conclusion: The results show that the efficacy of HIFU therapy in the kidney could be improved with aberration correction. Significance: A method is proposed by which patient specific pre-treatment calculations could be used to overcome the aberration and therefore make ultrasound treatment possible.Comment: Journal paper, IEEE Transactions on Biomedical Engineering (2018

On-the-Fly Calculation of Time-Averaged Acoustic Intensity in Time-Domain Ultrasound Simulations Using a k-Space Pseudospectral Method

OBJECTIVE: This paper presents a method to calculate the average acoustic intensity during ultrasound simulation using a new approach that exploits compression of intermediate results. METHODS: One of the applications of high-intensity focused ultrasound (HIFU) simulations is the calculation of the thermal dose, which indicates the amount of tissue destroyed using a state-of-the-art k-space pseudospectral method. The thermal simulation is preceded by the calculation of the average intensity within the acoustic simulation. Due to the time staggering between the particle velocity and the acoustic pressure used in such simulations, the average intensity calculation is typically executed offline after the acoustic simulation consuming both disk space and time (the data can spread over terabytes). Our new approach calculates the average intensity during the acoustic simulation using the output coefficients of a new compression method which enables resolving the time staggering on-the-fly with huge disk space savings. To reduce RAM requirements, the article also presents a new 40-bit method for encoding compression complex coefficients. RESULTS: Experimental numerical simulations with the proposed method have shown that disk space requirements are up to 99 % lower. The simulation speed was not significantly affected by the approach and the compression error did not affect the prediction accuracy of the thermal dose. CONCLUSION: From the standpoint of supercomputers, the new approach is significantly more economical. SIGNIFICANCE: Saving computing resources increases the chances of real use of acoustic simulations in practice. The method can be applied to signals of a similar character, e.g., for electromagnetic radio waves

The effect of tissue physiological variability on transurethral ultrasound therapy of the prostate

Therapeutic ultrasound is an investigational modality which could potentially be used for minimally invasive treatment of prostate cancer. Computational simulations were used to study the effect of natural physiological variations in tissue parameters on the efficacy of therapeutic ultrasound treatment in the prostate. The simulations were conducted on a clinical ultrasound therapy system using patient computed tomography (CT) data. The values of attenuation, perfusion, specific heat capacity and thermal conductivity were changed within their biological ranges to determine their effect on peak temperature and thermal dose volume. Increased attenuation was found to have the biggest effect on peak temperature with a 6.9% rise. The smallest effect was seen with perfusion with +-0.2% variation in peak temperature. Thermal dose was mostly affected by specific heat capacity which showed a 20.7% increase in volume with reduced heat capacity. Thermal conductivity had the smallest effect on thermal dose with up to 2.1% increase in the volume with reduced thermal conductivity. These results can be used to estimate the interpatient variation during the therapeutic ultrasound treatment of the prostate.Comment: Conference proceedin

Representing arbitrary acoustic source and sensor distributions in Fourier collocation methods

Accurately representing acoustic source distributions is an important part of ultrasound simulation. This is challenging for grid-based collocation methods when such distributions do not coincide with the grid points, for instance when the source is a curved, two-dimensional surface embedded in a three-dimensional domain. Typically, grid points close to the source surface are defined as source points, but this can result in "staircasing" and substantial errors in the resulting acoustic fields. This paper describes a technique for accurately representing arbitrary source distributions within Fourier collocation methods. The method works by applying a discrete, band-limiting convolution operator to the continuous source distribution, after which source grid weights can be generated. This allows arbitrarily shaped sources, for example, focused bowls and circular pistons, to be defined on the grid without staircasing errors. The technique is examined through simulations of a range of ultrasound sources, and comparisons with analytical solutions show excellent accuracy and convergence rates. Extensions of the technique are also discussed, including application to initial value problems, distributed sensors, and moving sources

Multi-GPU island-based genetic algorithm for solving the knapsack problem

This paper introduces a novel implementation of the genetic algorithm exploiting a multi-GPU cluster. The proposed implementation employs an island-based genetic algorithm where every GPU evolves a single island. The individuals are processed by CUDA warps, which enables the solution of large knapsack instances and eliminates undesirable thread divergence. The MPI interface is used to exchange genetic material among isolated islands and collect statistical data. The characteristics of the proposed GAs are investigated on a two-node cluster composed of 14 Fermi GPUs and 4 six-core Intel Xeon processors. The overall GPU performance of the proposed GA reaches 5.67 TFLOPS

A fair comparison of modern CPUs and GPUs running the genetic algorithm under the knapsack benchmark

The paper introduces an optimized multicore CPU implementation of the genetic algorithm and compares its performance with a fine-tuned GPU version. The main goal is to show the true performance relation between modern CPUs and GPUs and eradicate some of myths surrounding GPU performance. It is essential for the evolutionary community to provide the same conditions and designer effort to both implementations when benchmarking CPUs and GPUs. Here we show the performance comparison supported by architecture characteristics narrowing the performance gain of GPUs

Use of multiple GPUs on shared memory multiprocessors for ultrasound propagation simulations

This paper outlines our effort to migrate a compute intensive application of ultrasound propagation being developed in Matlab to a cluster computer where each node has seven GPUs. Our goal is to perform realistic simulations in hours and minutes instead of weeks and days. In order to reach this goal we investigate architecture characteristics of the target system focusing on the PCI-Express subsystem and new features proposed in CUDA version 4.0, especially simultaneous host to device, device to host and peer-to-peer transfers that the application is going to highly benefit from. We also present the results from a CPU based implementation and discuss future directions to exploit multiple GPUs