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Xu P, Wu H, Shen G. Characterization of weakly nonlinear effects in relationship to transducer parameters in focused ultrasound therapy. Med Phys 2024; 51:7619-7631. [PMID: 38935266 DOI: 10.1002/mp.17270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 06/04/2024] [Accepted: 06/13/2024] [Indexed: 06/28/2024] Open
Abstract
BACKGROUND Focused ultrasound therapy has been widely used for the treatment of various diseases, employing different types of transducers. The focused ultrasound pressure fields inevitably exhibit nonlinear effects, which can influence the ablation region. However, the nonlinear effects exhibit noticeable variations across different applications. The characterization of the nonlinear pressure fields of ultrasound is important for the effective implementation of focused ultrasound therapy. PURPOSE The traditional angular spectrum method (ASM) was extended to accurately and efficiently simulate the propagation of weakly nonlinear ultrasound in heterogeneous mediums of clinical model. The nonlinear effects were further analyzed in relationship to the transducer parameters that are different in various applications. METHODS The pressure fields were simulated using the extended ASM, incorporating calculations for phase aberration in the frequency domain and magnitude compensation in the spatial domain to account for heterogeneous acoustic impedance mismatch. Validation was performed by comparison to k-Wave simulation results using two simplified clinical models, an abdominal soft tissue and a transcranial skull model. The nonlinear effects were then analyzed in relation to the transducer parameters of f-number and effective source area based on the same acoustic output power. The analysis of nonlinear effects was conducted under both homogeneous medium and the clinical models. RESULTS The simulation results demonstrated a maximum error of 3.93% in the calculated harmonic pressure of the abdominal model, and a maximum error of 4.89% within the transcranial model when comparing the extended ASM simulation results to those obtained from k-Wave simulations. The characterization of the nonlinear effects reveals a strong correlation with the transducer parameters. Specifically, the results indicate that the nonlinear effects intensify with an increase in the effective source area and f-number, under the same acoustic output power of the transducer. However, the clinical model also showed an influence on the nonlinear effects in relation to the f-number. CONCLUSION The extended ASM was demonstrated as an accurate and efficient simulation tool, and the simulation results provide a reference for evaluating the intensity of nonlinear effects in various transducer designs.
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Affiliation(s)
- Peng Xu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Hao Wu
- Shanghai Shende Green Medical Era Healthcare Technology Co., Ltd, Shanghai, People's Republic of China
| | - Guofeng Shen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
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Dagommer M, Daneshzand M, Nummemnaa A, Guerin B. Robust deep learning estimation of cortical bone porosity from MR T1-weighted images for individualized transcranial focused ultrasound planning. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.18.24310644. [PMID: 39072036 PMCID: PMC11275664 DOI: 10.1101/2024.07.18.24310644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Objective Transcranial focused ultrasound (tFUS) is an emerging neuromodulation approach that has been demonstrated in animals but is difficult to translate to humans because of acoustic attenuation and scattering in the skull. Optimal dose delivery requires subject-specific skull porosity estimates which has traditionally been done using CT. We propose a deep learning (DL) estimation of skull porosity from T1-weighted MRI images which removes the need for radiation-inducing CT scans. Approach We evaluate the impact of different DL approaches, including network architecture, input size and dimensionality, multichannel inputs, data augmentation, and loss functions. We also propose back-propagation in the mask (BIM), a method whereby only voxels inside the skull mask contribute to training. We evaluate the robustness of the best model to input image noise and MRI acquisition parameters and propagate porosity estimation errors in thousands of beam propagation scenarios. Main results Our best performing model is a cGAN with a ResNet-9 generator with 3D 64×64×64 inputs trained with L1 and L2 losses. The model achieved a mean absolute error of 6.9% in the test set, compared to 9.5% with the pseudo-CT of Izquierdo et al. (38% improvement) and 9.4% with the generic pixel-to-pixel image translation cGAN pix2pix (36% improvement). Acoustic dose distributions in the thalamus were more accurate with our approach than with the pseudo-CT approach of both Burgos et al. and Izquierdo et al, resulting in near-optimal treatment planning and dose estimation at all frequencies compared to CT (reference). Significance Our DL approach porosity estimates with ~7% error, is robust to input image noise and MRI acquisition parameters (sequence, coils, field strength) and yields near-optimal treatment planning and dose estimates for both central (thalamus) and lateral brain targets (amygdala) in the 200-1000 kHz frequency range.
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Affiliation(s)
- Matthieu Dagommer
- École Supérieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI), Paris France
| | - Mohammad Daneshzand
- Harvard Medical School, Boston MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown MA
| | - Aapo Nummemnaa
- Harvard Medical School, Boston MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown MA
| | - Bastien Guerin
- Harvard Medical School, Boston MA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown MA
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Daneshzand M, Guerin B, Kotlarz P, Chou T, Dougherty DD, Edlow BL, Nummenmaa A. Model-based navigation of transcranial focused ultrasound neuromodulation in humans: Application to targeting the amygdala and thalamus. Brain Stimul 2024; 17:958-969. [PMID: 39094682 PMCID: PMC11367617 DOI: 10.1016/j.brs.2024.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 07/22/2024] [Accepted: 07/29/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Transcranial focused ultrasound (tFUS) neuromodulation has shown promise in animals but is challenging to translate to humans because of the thicker skull that heavily scatters ultrasound waves. OBJECTIVE We develop and disseminate a model-based navigation (MBN) tool for acoustic dose delivery in the presence of skull aberrations that is easy to use by non-specialists. METHODS We pre-compute acoustic beams for thousands of virtual transducer locations on the scalp of the subject under study. We use the hybrid angular spectrum solver mSOUND, which runs in ∼4 s per solve per CPU yielding pre-computation times under 1 h for scalp meshes with up to 4000 faces and a parallelization factor of 5. We combine this pre-computed set of beam solutions with optical tracking, thus allowing real-time display of the tFUS beam as the operator freely navigates the transducer around the subject' scalp. We assess the impact of MBN versus line-of-sight targeting (LOST) positioning in simulations of 13 subjects. RESULTS Our navigation tool has a display refresh rate of ∼10 Hz. In our simulations, MBN increased the acoustic dose in the thalamus and amygdala by 8-67 % compared to LOST and avoided complete target misses that affected 10-20 % of LOST cases. MBN also yielded a lower variability of the deposited dose across subjects than LOST. CONCLUSIONS MBN may yield greater and more consistent (less variable) ultrasound dose deposition than transducer placement with line-of-sight targeting, and thus could become a helpful tool to improve the efficacy of tFUS neuromodulation.
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Affiliation(s)
- Mohammad Daneshzand
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Bastien Guerin
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Parker Kotlarz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Tina Chou
- Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - Darin D Dougherty
- Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - Brian L Edlow
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
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Sallam A, Shahab S. Nonlinear Acoustic Holography With Adaptive Sampling. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2023; 70:1516-1526. [PMID: 37703162 DOI: 10.1109/tuffc.2023.3315011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
Accurate and efficient numerical simulation of highly nonlinear ultrasound propagation is essential for a wide range of therapeutic and physical ultrasound applications. However, due to large domain sizes and the generation of higher harmonics, such simulations are computationally challenging, particularly in 3-D problems with shock waves. Current numerical methods are based on computationally inefficient uniform meshes that resolve the highest harmonics across the entire spatial domain. To address this challenge, we present an adaptive numerical algorithm for computationally efficient nonlinear acoustic holography. At each propagation step, the algorithm monitors the harmonic content of the acoustic signal and adjusts its discretization parameters accordingly. This enables efficient local resolution of higher harmonics in areas of high nonlinearity while avoiding unnecessary resolution elsewhere. Furthermore, the algorithm actively adapts to the signal's nonlinearity level, eliminating the need for prior reference simulations or information about the spatial distribution of the harmonic content of the acoustic field. The proposed algorithm incorporates an upsampling process in the frequency domain to accommodate the generation of higher harmonics in forward propagation and a downsampling process when higher harmonics are decimated in backward propagation. The efficiency of the algorithm was evaluated for highly nonlinear 3-D problems, demonstrating a significant reduction in computational cost with a nearly 50-fold speedup over a uniform mesh implementation. Our findings enable a more rapid and efficient approach to modeling nonlinear high-intensity focused ultrasound (HIFU) wave propagation.
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Aubry JF, Bates O, Boehm C, Butts Pauly K, Christensen D, Cueto C, Gélat P, Guasch L, Jaros J, Jing Y, Jones R, Li N, Marty P, Montanaro H, Neufeld E, Pichardo S, Pinton G, Pulkkinen A, Stanziola A, Thielscher A, Treeby B, van 't Wout E. Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2022; 152:1003. [PMID: 36050189 DOI: 10.5281/zenodo.6020543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
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.
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Affiliation(s)
- Jean-Francois Aubry
- Physics for Medicine Paris, National Institute of Health and Medical Research (INSERM) U1273, ESPCI Paris, Paris Sciences and Lettres University, French National Centre for Scientific Research (CNRS) UMR 8063, Paris, France
| | - Oscar Bates
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Christian Boehm
- Institute of Geophysics, Swiss Federal Institute of Technology (ETH) Zürich, Sonneggstrasse 5, 8092 Zürich, Switzerland
| | - Kim Butts Pauly
- Department of Radiology, Stanford University, Stanford, California 94305, USA
| | - Douglas Christensen
- Department of Biomedical Engineering and Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah 84112, USA
| | - Carlos Cueto
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Pierre Gélat
- Department of Surgical Biotechnology, Division of Surgery and Interventional Science, University College London, London NW3 2PF, United Kingdom
| | - Lluis Guasch
- Earth Science and Engineering Department, Imperial College London, London, United Kingdom
| | - Jiri Jaros
- Centre of Excellence IT4Innovations, Faculty of Information Technology, Brno University of Technology, Bozetechova 2, Brno 612 00, Czech Republic
| | - Yun Jing
- Graduate Program in Acoustics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Rebecca Jones
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA and North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Ningrui Li
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
| | - Patrick Marty
- Institute of Geophysics, Swiss Federal Institute of Technology (ETH) Zürich, Sonneggstrasse 5, 8092 Zürich, Switzerland
| | - Hazael Montanaro
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Samuel Pichardo
- Radiology and Clinical Neurosciences Departments, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Gianmarco Pinton
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA and North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Aki Pulkkinen
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Antonio Stanziola
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom
| | | | - Bradley Treeby
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom
| | - Elwin van 't Wout
- Institute for Mathematical and Computational Engineering, School of Engineering and Faculty of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile
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Aubry JF, Bates O, Boehm C, Butts Pauly K, Christensen D, Cueto C, Gélat P, Guasch L, Jaros J, Jing Y, Jones R, Li N, Marty P, Montanaro H, Neufeld E, Pichardo S, Pinton G, Pulkkinen A, Stanziola A, Thielscher A, Treeby B, van 't Wout E. Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2022; 152:1003. [PMID: 36050189 PMCID: PMC9553291 DOI: 10.1121/10.0013426] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
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.
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Affiliation(s)
- Jean-Francois Aubry
- Physics for Medicine Paris, National Institute of Health and Medical Research (INSERM) U1273, ESPCI Paris, Paris Sciences and Lettres University, French National Centre for Scientific Research (CNRS) UMR 8063, Paris, France
| | - Oscar Bates
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Christian Boehm
- Institute of Geophysics, Swiss Federal Institute of Technology (ETH) Zürich, Sonneggstrasse 5, 8092 Zürich, Switzerland
| | - Kim Butts Pauly
- Department of Radiology, Stanford University, Stanford, California 94305, USA
| | - Douglas Christensen
- Department of Biomedical Engineering and Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, Utah 84112, USA
| | - Carlos Cueto
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Pierre Gélat
- Department of Surgical Biotechnology, Division of Surgery and Interventional Science, University College London, London NW3 2PF, United Kingdom
| | - Lluis Guasch
- Earth Science and Engineering Department, Imperial College London, London, United Kingdom
| | - Jiri Jaros
- Centre of Excellence IT4Innovations, Faculty of Information Technology, Brno University of Technology, Bozetechova 2, Brno 612 00, Czech Republic
| | - Yun Jing
- Graduate Program in Acoustics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Rebecca Jones
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA and North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Ningrui Li
- Department of Electrical Engineering, Stanford University, Stanford, California 94305, USA
| | - Patrick Marty
- Institute of Geophysics, Swiss Federal Institute of Technology (ETH) Zürich, Sonneggstrasse 5, 8092 Zürich, Switzerland
| | - Hazael Montanaro
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Samuel Pichardo
- Radiology and Clinical Neurosciences Departments, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Gianmarco Pinton
- Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA and North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Aki Pulkkinen
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Antonio Stanziola
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom
| | | | - Bradley Treeby
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom
| | - Elwin van 't Wout
- Institute for Mathematical and Computational Engineering, School of Engineering and Faculty of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile
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Yuldashev PV, Karzova MM, Kreider W, Rosnitskiy PB, Sapozhnikov OA, Khokhlova VA. "HIFU Beam:" A Simulator for Predicting Axially Symmetric Nonlinear Acoustic Fields Generated by Focused Transducers in a Layered Medium. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2021; 68:2837-2852. [PMID: 33877971 PMCID: PMC8486313 DOI: 10.1109/tuffc.2021.3074611] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
"HIFU beam" is a freely available software tool that comprises a MATLAB toolbox combined with a user-friendly interface and binary executable compiled from FORTRAN source code (HIFU beam. (2021). Available: http://limu.msu.ru/node/3555?language=en). It is designed for simulating high-intensity focused ultrasound (HIFU) fields generated by single-element transducers and annular arrays with propagation in flat-layered media that mimic biological tissues. Numerical models incorporated in the simulator include evolution-type equations, either the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation or one-way Westervelt equation, for radially symmetric ultrasound beams in homogeneous and layered media with thermoviscous or power-law acoustic absorption. The software uses shock-capturing methods that allow for simulating strongly nonlinear acoustic fields with high-amplitude shocks. In this article, a general description of the software is given along with three representative simulation cases of ultrasound transducers and focusing conditions typical for therapeutic applications. The examples illustrate major nonlinear wave effects in HIFU fields including shock formation. Two examples simulate propagation in water, involving a single-element source (1-MHz frequency, 100-mm diameter, 90-mm radius of curvature) and a 16-element annular array (3-MHz frequency, 48-mm diameter, and 35-mm radius of curvature). The third example mimics the scenario of a HIFU treatment in a "water-muscle-kidney" layered medium using a source typical for abdominal HIFU applications (1.2-MHz frequency, 120-mm diameter, and radius of curvature). Linear, quasi-linear, and shock-wave exposure protocols are considered. It is intended that "HIFU beam" can be useful in teaching nonlinear acoustics; designing and characterizing high-power transducers; and developing exposure protocols for a wide range of therapeutic applications such as shock-based HIFU, boiling histotripsy, drug delivery, immunotherapy, and others.
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Li M, Gu J, Vu T, Sankin G, Zhong P, Yao J, Jing Y. Time-Resolved Passive Cavitation Mapping Using the Transient Angular Spectrum Approach. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2021; 68:2361-2369. [PMID: 33635787 PMCID: PMC8269954 DOI: 10.1109/tuffc.2021.3062357] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
Passive cavitation mapping (PCM), which generates images using bubble acoustic emission signals, has been increasingly used for monitoring and guiding focused ultrasound surgery (FUS). PCM can be used as an adjunct to magnetic resonance imaging to provide crucial information on the safety and efficacy of FUS. The most widely used algorithm for PCM is delay-and-sum (DAS). One of the major limitations of DAS is its suboptimal computational efficiency. Although frequency-domain DAS can partially resolve this issue, such an algorithm is not suitable for imaging the evolution of bubble activity in real time and for cases in which cavitation events occur asynchronously. This study investigates a transient angular spectrum (AS) approach for PCM. The working principle of this approach is to backpropagate the received signal to the domain of interest and reconstruct the spatial-temporal wavefield encoded with the bubble location and collapse time. The transient AS approach is validated using an in silico model and water bath experiments. It is found that the transient AS approach yields similar results to DAS, but it is one order of magnitude faster. The results obtained by this study suggest that the transient AS approach is promising for fast and accurate PCM.
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Gu J, Jing Y. mSOUND: An Open Source Toolbox for Modeling Acoustic Wave Propagation in Heterogeneous Media. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2021; 68:1476-1486. [PMID: 33444136 PMCID: PMC8101065 DOI: 10.1109/tuffc.2021.3051729] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
mSOUND is an open-source toolbox written in MATLAB. This toolbox is intended for modeling linear/ nonlinear acoustic wave propagation in media (primarily biological tissues) with arbitrary heterogeneities, in which, the speed of sound, density, attenuation coefficient, power-law exponent, and nonlinear coefficient are all spatially varying functions. The computational model is an iterative one-way model based on a mixed domain method. In this article, a general guideline is given along with three representative examples to illustrate how to set up simulations using mSOUND. The first example uses the transient mixed-domain method (TMDM) forward projection to compute the transient acoustic field for a given source defined on a plane. The second example uses the frequency-specific mixed-domain method (FSMDM) forward projection to rapidly obtain the pressure distribution directly at the frequencies of interest, assuming linear or weakly nonlinear wave propagation. The third example demonstrates how to use TMDM backward projection to reconstruct the initial acoustic pressure field to facilitate photoacoustic tomography (PAT). mSOUND (https://m-sound.github.io/mSOUND/home) is designed to be complementary to existing ultrasound modeling toolboxes and is expected to be useful for a wide range of applications in medical ultrasound including treatment planning, PAT, transducer design, and characterization.
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Treeby BE, Wise ES, Kuklis F, Jaros J, Cox BT. Nonlinear ultrasound simulation in an axisymmetric coordinate system using a k-space pseudospectral method. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2020; 148:2288. [PMID: 33138501 DOI: 10.1121/10.0002177] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
A full-wave model for nonlinear ultrasound propagation through a heterogeneous and absorbing medium in an axisymmetric coordinate system is developed. The model equations are solved using a nonstandard or k-space pseudospectral time domain method. Spatial gradients in the axial direction are calculated using the Fourier collocation spectral method, and spatial gradients in the radial direction are calculated using discrete trigonometric transforms. Time integration is performed using a k-space corrected finite difference scheme. This scheme is exact for plane waves propagating linearly in the axial direction in a homogeneous and lossless medium and significantly reduces numerical dispersion in the more general case. The implementation of the model is described, and performance benchmarks are given for a range of grid sizes. The model is validated by comparison with several analytical solutions. This includes one-dimensional absorption and nonlinearity, the pressure field generated by plane-piston and bowl transducers, and the scattering of a plane wave by a sphere. The general utility of the model is then demonstrated by simulating nonlinear transcranial ultrasound using a simplified head model.
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Affiliation(s)
- Bradley E Treeby
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom
| | - Elliott S Wise
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom
| | - Filip Kuklis
- Centre of Excellence IT4Innovations, Faculty of Information Technology, Brno University of Technology, Božetěchova 2, Brno, 612 00, Czech Republic
| | - Jiri Jaros
- Centre of Excellence IT4Innovations, Faculty of Information Technology, Brno University of Technology, Božetěchova 2, Brno, 612 00, Czech Republic
| | - B T Cox
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London WC1E 6BT, United Kingdom
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