Showing papers by "Bradley E. Treeby published in 2022"

Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

Abstract: Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston operating at 500 kHz), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross-comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons.

Classical and Learned MR to Pseudo-CT Mappings for Accurate Transcranial Ultrasound Simulation

Abstract: Model-based treatment planning for transcranial ultrasound therapy typically involves mapping the acoustic properties of the skull from an X-ray computed tomography (CT) image of the head. Here, three methods for generating pseudo-CT (pCT) images from magnetic resonance (MR) images were compared as an alternative to CT. A convolutional neural network (U-Net) was trained on paired MR-CT images to generate pCT T images from either T1-weighted or zero-echo time (ZTE) MR images (denoted tCT and zCT, respectively). A direct mapping from ZTE to pCT was also implemented (denoted cCT). When comparing the pCT and ground-truth CT images for the test set, the mean absolute error was 133, 83, and 145 Hounsfield units (HU) across the whole head, and 398, 222, and 336 HU within the skull for the tCT, zCT, and cCT images, respectively. Ultrasound simulations were also performed using the generated pCT images and compared to simulations based on CT. An annular array transducer was used targeting the visual or motor cortex. The mean differences in the simulated focal pressure, focal position, and focal volume were 9.9%, 1.5 mm, and 15.1% for simulations based on the tCT images; 5.7%, 0.6 mm, and 5.7% for the zCT; and 6.7%, 0.9 mm, and 12.1% for the cCT. The improved results for images mapped from ZTE highlight the advantage of using imaging sequences, which improves the contrast of the skull bone. Overall, these results demonstrate that acoustic simulations based on MR images can give comparable accuracy to those based on CT.

Matching Layer Deposition for an Open-Source Ultrasound Tomography System: Inter-Element Variation in Frequency Response

Abstract: Progress towards fast accurate Ultrasound Tomog-raphy (UST) requires experimental validation of new methods, creating a need for low-cost UST hardware, which can be achieved using in-house manufacture. However, a key challenge for transducer manufacture is controlling the composition and thickness of matching layers. For this work, a new low-cost deposition technique was developed, which is part of the open-UST manufacturing framework. To assess the technique, 8 16-element UST transducer modules were built, and the inter-element variation in their electrical input impedance, impulse response, and transmit-receive response was measured. The acoustic performance was highly uniform with no defective elements. The −40 dB transmit-receive bandwidth was 146 %, with a mean SNR of 60.5 dB, and the standard deviation in amplitude at the 1.21 MHz fundamental frequency, was very low (σ= ± 7.1 %, without using normalisation. The high uniformity is significant, because it means that the elements can be assumed to be identical during image reconstruction, which simplifies the assumptions required, and removes the need for extensive hy-drophone calibration. The open-UST manufacturing framework could therefore lower the barrier to entry for researchers, and accelerate preliminary UST research.

Transcranial ultrasound simulation with uncertainty estimation.

Abstract: Transcranial ultrasound simulations are increasingly used to predict in situ exposure parameters for ultrasound therapies in the brain. However, there can be considerable uncertainty in estimating the acoustic medium properties of the skull and brain from computed tomography (CT) images. This paper shows how the resulting uncertainty in the simulated acoustic field can be predicted in a computationally efficient way using linear uncertainty propagation. Results for a representative transcranial simulation using a focused bowl transducer at 500 kHz show good agreement with unbiased uncertainty estimates obtained using Monte Carlo.

A Learned Born Series for Highly-Scattering Media

Abstract: A new method for solving the wave equation is presented, called the learned Born series (LBS), which is derived from a convergent Born series but its components are found through training. The LBS is shown to be significantly more accurate than the convergent Born series for the same number of iterations, in the presence of high contrast scatterers, while maintaining a comparable computational complexity. The LBS is able to generate a reasonable prediction of the global pressure field with a small number of iterations, and the errors decrease with the number of learned iterations.

Experiments and simulations demonstrating the rapid ultrasonic rewarming of frozen tissue cryovials.

Abstract: The development of methods to safely rewarm large cryopreserved biological samples remains a barrier to the widespread adoption of cryopreservation. Here, experiments and simulations were performed to demonstrate that ultrasound can increase rewarming rates relative to thermal conduction alone. An ultrasonic rewarming setup based on a custom 444 kHz tubular piezoelectric transducer was designed, characterized, and tested with 2 ml cryovials filled with frozen ground beef. Rewarming rates were characterized in the -20 °C to 5 °C range. Thermal conduction-based rewarming was compared to thermal conduction plus ultrasonic rewarming, demonstrating a tenfold increase in rewarming rate when ultrasound was applied. The maximum recorded rewarming rate with ultrasound was 57° C/min, approximately 2.5 times faster than with thermal conduction alone. Coupled acoustic and thermal simulations were developed and showed good agreement with the heating rates demonstrated experimentally and were also used to demonstrate spatial heating distributions with small (<3° C) temperature differentials throughout the sample when the sample was below 0° C. The experiments and simulations demonstrate the potential for ultrasonic cryovial rewarming with a possible application to large volume rewarming, as faster rewarming rates may improve the viability of cryopreserved tissues and reduce the time needed for cells to regain normal function.

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

Abstract: This article presents a method to calculate the average acoustic intensity during ultrasound simulation using a new approach that exploits compression of intermediate results. 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. 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. From the standpoint of supercomputers, the new approach is significantly more economical. 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.

Binary volume acoustic holograms

Abstract: Acoustic holograms or phase conjugate acoustic lenses are a simple inexpensive method for forming complex acoustic fields. They are 3D printable phase plates that can map an incident field onto a pre-defined phase distribution such that it diffracts to form a desired field. These phase plates areanalogues of thin optical holograms with a thickness d ≅ λ the design wavelength. Another class of optical holograms are “thick” or “volume” holograms, composed of weak periodic variations in the refractive index, for which d ⪢ λ. These volume holograms are significantly more selective to the wavelength and direction of the incident field allowing for greater ability to multiplex patterns within a single hologram. In this work, we explore the generation of volume acoustic holograms using multi-material 3-D printing. First, we numerically assess the impact of sound speed contrast, absorption, and quantisation on efficiency. A greedy optimization approach is then introduced for the design of a volumetric hologram from a desired set of input/output fields. We then validate the approach experimentally using test samples printed on an Objet Connex 350. Several holograms are fabricated demonstrating both spatial and frequency multiplexing of different patterns in a single volume.