Ultrashort echo‐time MRI versus CT for skull aberration correction in MR‐guided transcranial focused ultrasound: <i>In vitro</i> comparison on human calvaria

Miller, G. Wilson; Eames, Matthew; Snell, John; Aubry, Jean‐François

doi:10.1118/1.4916656

Cited by 55 publications

(58 citation statements)

References 47 publications

(42 reference statements)

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“…[9][10][11][12] In finite difference methods, partial derivatives are calculated using a linear combination of function values at neighboring grid points. The finite difference approximations are derived by combining local Taylor series expansions truncated to a fixed number of terms.…”

Section: Numerical Methods For Ultrasound Propagationmentioning

confidence: 99%

“…Beam steering capabilities are determined primarily by hardware, and are not considered here. Modeling of the skull as a single homogeneous layer in this way was recently validated for low frequency modeldriven TR by Miller et al 10 The influence of reverberations within the head is considered when necessary, with each reverberation consisting of 2 cm propagation through bone, and 20 cm propagation through brain tissue. The combined effects of these numerical inaccuracies and the validity of the established sampling criteria are then examined through convergence testing of fully simulated two-dimensional (2D) and three-dimensional (3D) TR protocols.…”

Section: A Overviewmentioning

confidence: 99%

“…9 In model-driven TR, numerical models simulate the propagation of ultrasound from a target area to a virtual transducer using acoustic property maps of the head derived from CT or MRI images. 9,10 The pressure time series at the simulated transducer surface is then time-reversed, and used to generate drive signals for a multi-element acoustic transducer array. For high-intensity thermal applications, model-driven TR may be combined with MRI thermometry for treatment verification.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Accurate simulation of transcranial ultrasound propagation for ultrasonic neuromodulation and stimulation

Robertson

Cox

Jaroš

et al. 2017

The Journal of the Acoustical Society of America

115

108

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Non-invasive, focal neurostimulation with ultrasound is a potentially powerful neuroscientific tool that requires effective transcranial focusing of ultrasound to develop. Time-reversal (TR) focusing using numerical simulations of transcranial ultrasound propagation can correct for the effect of the skull, but relies on accurate simulations. Here, focusing requirements for ultrasonic neurostimulation are established through a review of previously employed ultrasonic parameters, and consideration of deep brain targets. The specific limitations of finite-difference time domain (FDTD) and k-space corrected pseudospectral time domain (PSTD) schemes are tested numerically to establish the spatial points per wavelength and temporal points per period needed to achieve the desired accuracy while minimizing the computational burden. These criteria are confirmed through convergence testing of a fully simulated TR protocol using a virtual skull. The k-space PSTD scheme performed as well as, or better than, the widely used FDTD scheme across all individual error tests and in the convergence of large scale models, recommending it for use in simulated TR. Staircasing was shown to be the most serious source of error. Convergence testing indicated that higher sampling is required to achieve fine control of the pressure amplitude at the target than is needed for accurate spatial targeting.

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Section: Numerical Methods For Ultrasound Propagationmentioning

confidence: 99%

Section: A Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Accurate simulation of transcranial ultrasound propagation for ultrasonic neuromodulation and stimulation

Robertson

Cox

Jaroš

et al. 2017

The Journal of the Acoustical Society of America

115

108

View full text Add to dashboard Cite

show abstract

“…1. MRI based methods, including segmentation [15], and morphological adaptation of virtual CT images have also been examined [16].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of simulated transcranial ultrasound fields to acoustic medium property maps

et al. 2017

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Abstract.High intensity transcranial focused ultrasound is an FDA approved treatment for essential tremor, while low-intensity applications such as neurostimulation and opening the blood brain barrier are under active research. Simulations of transcranial ultrasound propagation are used both for focusing through the skull, and predicting intracranial fields. Maps of the skull acoustic properties are necessary for accurate simulations, and can be derived from medical images using a variety of methods. The skull maps range from segmented, homogeneous models, to fully heterogeneous models derived from medical image intensity. In the present work, the impact of uncertainties in the skull properties is examined using a model of transcranial propagation from a single element focused transducer. The impact of changes in bone layer geometry and the sound speed, density, and acoustic absorption values is quantified through a numerical sensitivity analysis. Sound speed is shown to be the most influential acoustic property, and must be defined with less than 4% error to obtain acceptable accuracy in simulated focus pressure, position, and volume. Changes in the skull thickness of as little as 0.1 mm can cause an error in peak intracranial pressure of greater than 5%, while smoothing with a 1 mm 3 kernel to imitate the effect of obtaining skull maps from low resolution images causes an increase of over 50% in peak pressure. The numerical results are confirmed experimentally through comparison with sonications made through 3D printed and resin cast skull bone phantoms.

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“…These include acoustic methods, which typically rely on the presence of a small hydrophone [4, 5, 6, 7] or source ( e.g. transducer [8] or microbubble [9, 10, 11, 12, 13, 14]) near the desired focal point or involve analysis of the backscattered [15, 16] or transmitted [17, 18] signals, magnetic resonance (MR) acoustic radiation force imaging-based techniques [19, 20, 21, 22, 23], as well as approaches that use cranial morphology obtained from either MR imaging [24, 25, 26] or computed tomography (CT) [27, 28] scans of the head to calculate the required aberration corrections. The existing clinical devices used for focused ultrasound brain treatments apply CT-based focusing on transmit [29, 30, 31] using an analytic, ray-tracing approximation [32], which can rapidly (on the order of seconds) compute element corrections.…”

Section: Introductionmentioning

confidence: 99%

Comparison of analytical and numerical approaches for CT-based aberration correction in transcranial passive acoustic imaging

Jones

Hynynen

2015

Phys. Med. Biol.

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Computed tomography (CT)-based aberration corrections are employed in transcranial ultrasound both for therapy and imaging. In this study, analytical and numerical approaches for calculating aberration corrections based on CT data were compared, with a particular focus on their application to transcranial passive imaging. Two models were investigated: a three-dimensional full-wave numerical model [Connor and Hynynen, IEEE Trans. Biomed. Eng. 51, 1693–1706 (2004)] based on the Westervelt equation, and an analytical method [Clement and Hynynen, Ultrasound Med. Biol. 28, 617–624 (2002)] similar to that currently employed by commercial brain therapy systems. Trans-skull time delay corrections calculated from each model were applied to data acquired by a sparse hemispherical (30 cm diameter) receiver array (128 piezoceramic discs: 2.5 mm diameter, 612 kHz center frequency) passively listening through ex vivo human skullcaps (n = 4) to emissions from a narrow-band, fixed source emitter (1 mm diameter, 516 kHz center frequency). Measurements were taken at various locations within the cranial cavity by moving the source around the field using a three-axis positioning system. Images generated through passive beamforming using CT-based skull corrections were compared with those obtained through an invasive source-based approach, as well as images formed without skull corrections, using the main lobe volume, positional shift, peak sidelobe ratio, and image signal-to-noise ratio as metrics for image quality. For each CT-based model, corrections achieved by allowing for heterogeneous skull acoustical parameters in simulation outperformed the corresponding case where homogeneous parameters were assumed. Of the CT-based methods investigated, the full-wave model provided the best imaging results at the cost of computational complexity. These results highlight the importance of accurately modeling trans-skull propagation when calculating CT-based aberration corrections. Although presented in an imaging context, our results may also be applicable to the problem of transmit focusing through the skull.

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Ultrashort echo‐time MRI versus CT for skull aberration correction in MR‐guided transcranial focused ultrasound: In vitro comparison on human calvaria

Cited by 55 publications

References 47 publications

Accurate simulation of transcranial ultrasound propagation for ultrasonic neuromodulation and stimulation

Accurate simulation of transcranial ultrasound propagation for ultrasonic neuromodulation and stimulation

Sensitivity of simulated transcranial ultrasound fields to acoustic medium property maps

Comparison of analytical and numerical approaches for CT-based aberration correction in transcranial passive acoustic imaging

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