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

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.

Transcranial ultrasound simulation with uncertainty estimation.

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.

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.

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

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.

3-D Microvascular Imaging Using High Frame Rate Ultrasound and ASAP Without Contrast Agents: Development and Initial In Vivo Evaluation on Nontumor and Tumor Models.

Three-dimensional imaging is valuable to noninvasively assess angiogenesis given the complex 3-D architecture of vascular networks. The emergence of high frame rate (HFR) ultrasound, which can produce thousands of images per second, has inspired novel signal processing techniques and their applications in structural and functional imaging of blood vessels. Although highly sensitive vascular mapping has been demonstrated using ultrafast Doppler, the detectability of microvasculature from the background noise may be hindered by the low signal-to-noise ratio (SNR) particularly in the deeper region and without the use of contrast agents. We have recently demonstrated a coherence-based technique, acoustic subaperture imaging (ASAP), for super-contrast vascular imaging and illustrated the contrast improvement using HFR contrast-enhanced ultrasound. In this work, we provide a feasibility study for microvascular imaging using ASAP without contrast agents, and extend its capability from 2-D to volumetric vascular mapping. Using an ultrasound research system and a preclinical probe, we demonstrated the improved visibility of microvascular mapping using ASAP in comparison to ultrafast power Doppler (PD) on a mouse kidney, liver, and tumor without contrast agent injection. The SNR of ASAP images improves in average by 10 dB when compared to PD. In addition, directional velocity mappings were also demonstrated by combining ASAP with the phase information extracted from lag-1 autocorrelation. The 3-D vascular and velocity mapping of the mouse kidney, liver, and tumor were demonstrated by stacking the ASAP images acquired using 2-D ultrasound imaging and a trigger-controlled linear translation stage. The 3-D results depicted clear microvasculature morphologies and functional information in terms of flow direction and velocity in two nontumor models and a tumor model. In conclusion, we have demonstrated a new 3-D in vivo ultrasound microvascular imaging technique with significantly improved SNR over existing ultrafast Doppler.

ASAP: Super-Contrast Vasculature Imaging Using Coherence Analysis and High Frame-Rate Contrast Enhanced Ultrasound.

The very high frame rate afforded by ultrafast ultrasound, combined with microbubble contrast agents, opens new opportunities for imaging tissue microvasculature. However, new imaging paradigms are required to obtain superior image quality from the large amount of acquired data while allowing real-time implementation. In this paper, we report a technique-acoustic sub-aperture processing (ASAP)-capable of generating very high contrast/signal-to-noise ratio (SNR) images of macro-and microvessels, with similar computational complexity to classical power Doppler (PD) imaging. In ASAP, the received data are split into subgroups. The reconstructed data from each subgroup are temporally correlated over frames to generate the final image. As signals in subgroups are correlated but the noise is not, this substantially reduces the noise floor compared to PD. Using a clinical imaging probe, the method is shown to visualize vessels down to $200~\mu \text{m}$ with a SNR of 10 dB higher than PD and to resolve microvascular flow/perfusion information in rabbit kidneys noninvasively in vivo at multiple centimeter depths. With careful filter design, the technique also allows the estimation of flow direction and the separation of fast flow from tissue perfusion. ASAP can readily be implemented into hardware/firmware for real-time imaging and can be applied to contrast enhanced and potentially noncontrast imaging and 3-D imaging.

Optically and acoustically triggerable sub-micron phase-change contrast agents for enhanced photoacoustic and ultrasound imaging.

We demonstrate a versatile phase-change sub-micron contrast agent providing three modes of contrast enhancement: 1) photoacoustic imaging contrast, 2) ultrasound contrast with optical activation, and 3) ultrasound contrast with acoustic activation. This agent, which we name 'Cy-droplet', has the following novel features. It comprises a highly volatile perfluorocarbon for easy versatile activation, and a near-infrared optically absorbing dye chosen to absorb light at a wavelength with good tissue penetration. It is manufactured via a 'microbubble condensation' method. The phase-transition of Cy-droplets can be optically triggered by pulsed-laser illumination, inducing photoacoustic signal and forming stable gas bubbles that are visible with echo-ultrasound in situ. Alternatively, Cy-droplets can be converted to microbubble contrast agents upon acoustic activation with clinical ultrasound. Potentially all modes offer extravascular contrast enhancement because of the sub-micron initial size. Such versatility of acoustic and optical 'triggerability' can potentially improve multi-modality imaging, molecularly targeted imaging and controlled drug release.

Differential Intensity Projection for Visualisation and Quantification of Plaque Neovascularisation in Contrast-Enhanced Ultrasound Images of Carotid Arteries.

Studies have reported that intraplaque neovascularisation (IPN) is closely correlated with plaque vulnerability. In this study, a new image processing approach, differential intensity projection (DIP), was developed to visualise and quantify IPN in contrast-enhanced non-linear ultrasound image sequences of carotid arteries. DIP used the difference between the local temporal maximum and the local temporal average signals to identify bubbles against tissue non-linear artefact and noise. The total absolute and relative areas occupied by bubbles within each plaque were calculated to quantify IPN. In vitro measurements on a laboratory phantom were made, followed by in vivo measurements in which 24 contrast-enhanced non-linear ultrasound image sequences of carotid arteries from 48 patients were selected and motion corrected. The results using DIP were compared with those obtained by maximum intensity projection (MIP) and visual assessment. The results indicated that DIP can significantly reduce non-linear propagation tissue artefacts and is much more specific in detecting bubble signals than MIP, being able to reveal microbubble signals that are buried in tissue artefacts in the corresponding MIP image. A good correlation was found between microvascular area (MVA) (r = 0.83, p < 0.001)/microvascular density (r = 0.77, p < 0.001) obtained using DIP and the corresponding expert visual grades, comparing favourably to r = 0.26 and 0.23 obtained using MIP on the same data. In conclusion, the proposed method exhibits great potential in quantification of IPN in contrast-enhanced ultrasound images of carotid arteries.