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

Aubry, Jean‐François; Bates, Oscar; Boehm, Christian; Pauly, Kim Butts; Christensen, Douglas A.; Cueto, Carlos Antonio Navarrete; Gélat, Pierre; Guasch, Lluís; Jaroš, Jiří; Yun, Jimmy; Jones, Rebecca L.; Li, Ningrui; Marty, Patrick; Montanaro, Hazael; Neufeld, Esra; Pichardo, Samuel; Pinton, Gianmarco; Pulkkinen, Aki; Stanziola, Antonio; Thielscher, Axel; Treeby, Bradley E.; Wout, Elwin van ’t

doi:10.48550/arxiv.2202.04552

Cited by 5 publications

(5 citation statements)

References 69 publications

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“…The best results were obtained when using the zCT images for motor targets, where the equivalent differences were 3.7 %, 0.5 mm, and 3.9 %. These values compare well with the differences observed in experimental repeatability [64] and numerical intercomparison [61] studies. For reference, the focal volume simulated in water is 3.9 mm wide and 24 mm long.…”

Section: B Acoustic Simulationssupporting

confidence: 87%

“…The transducer was modelled using a staircasefree formulation [60] using nominal values for the radius of curvature (63.2 mm) and element aperture diameters (32.8, 46, 55.9, 64 mm). Simulations were run at 6 points per wavelength (PPW) in water and 60 points per period (PPP), which was sufficient to reproduce the relevant benchmark results (PH1-BM7-SC1) reported in [61] with less than 0.2 % difference in the maximum pressure and no difference in the focal position. The transducer was driven using a continuous sinusoidal driving signal at 500 kHz until steady state was reached.…”

Section: E Ultrasound Simulations Using K-wavementioning

confidence: 99%

“…The calculated acoustic pressure fields for each CT/pCT pair were compared using the focal metrics outlined in [61] using the code available from [62]. Briefly, the magnitude and position of the spatial peak pressure within the brain were compared, along with the -6 dB focal volume.…”

Section: E Ultrasound Simulations Using K-wavementioning

confidence: 99%

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

Miscouridou

Pineda‐Pardo

Stagg

et al. 2022

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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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 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 pseudo-CT images from either T1-weighted or zero-echo time (ZTE) MR images (denoted tCT and zCT, respectively). A direct mapping from ZTE to pseudo-CT was also implemented (denoted cCT). When comparing the pseudo-CT 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 pseudo-CT 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 improve 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.

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Section: B Acoustic Simulationssupporting

confidence: 87%

Section: E Ultrasound Simulations Using K-wavementioning

confidence: 99%

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

Miscouridou

Pineda‐Pardo

Stagg

et al. 2022

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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“…The acoustic properties of sound speed, density, alpha coefficient, and alpha power, as well as the thermal properties of thermal conductivity and heat capacity, were assigned to the skull, scalp, and brain, as reported in Table 1 (Aubry et al, 2022;Hasgall et al, 2022).…”

Section: Simulationsmentioning

confidence: 99%

Auditory confounds can drive online effects of transcranial ultrasonic stimulation in humans

Kop

Oghli

Grippe

et al. 2023

Preprint

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Transcranial ultrasonic stimulation (TUS) is rapidly emerging as a promising non-invasive neuromodulation technique. TUS is already well-established in animal models, and now stimulation protocols that optimize neuromodulatory efficacy for human application are required. One promising protocol, pulsed at 1000 Hz, has consistently resulted in motor cortical inhibition. At the same time, a parallel research line has highlighted the potentially confounding influence of peripheral auditory stimulation arising from pulsing TUS at audible frequencies. Across four experiments, one preregistered, at three independent institutions, we employed tightly matched control conditions to disentangle direct neuromodulatory effects of TUS from those driven by the salient auditory confound in a combined transcranial ultrasonic and magnetic stimulation paradigm. We replicated motor cortical inhibition following TUS, but showed through both controls and manipulation of stimulation intensity, duration, and auditory masking conditions that this inhibition was driven by peripheral auditory stimulation rather than direct neuromodulation. This study highlights the substantial impact of the auditory confound, invites a reevaluation of prior findings, and calls for appropriate control conditions in future TUS work. Only when direct effects are disentangled from those driven by peripheral confounds can TUS fully realize its potential for neuroscientific research and clinical applications.

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“…The acoustic properties of the skull can then be input into acoustic solvers to simulate the resulting pressure field, temperature rise, or phase and amplitude compensation for a particular subject. There are a number of acoustic simulation tools available [36], [37], where the appropriate simulation method for an application involves a trade-off between simulation speed and accuracy. For transducer positioning methods outside the MR scanner, acoustic simulations have been included in studies to estimate in situ pressure, spatial extent, and heating [38].…”

mentioning

confidence: 99%

Generating Patient-Specific Acoustic Simulations for Transcranial Focused Ultrasound Procedures Based on Optical Tracking Information

Sigona,

Manuel,

Phipps

et al. 2023

IEEE Open J. Ultrason., Ferroelect., Freq. Contr.

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

Cited by 5 publications

References 69 publications

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

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

Auditory confounds can drive online effects of transcranial ultrasonic stimulation in humans

Generating Patient-Specific Acoustic Simulations for Transcranial Focused Ultrasound Procedures Based on Optical Tracking Information

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