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Li C, Xu G, Wang Y, Huang L, Cai F, Meng L, Jin B, Jiang Z, Sun H, Zhao H, Lu X, Sang X, Huang P, Li F, Yang H, Mao Y, Zheng H. Acoustic-holography-patterned primary hepatocytes possess liver functions. Biomaterials 2024; 311:122691. [PMID: 38996673 DOI: 10.1016/j.biomaterials.2024.122691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 06/03/2024] [Accepted: 06/26/2024] [Indexed: 07/14/2024]
Abstract
Acoustic holography (AH), a promising approach for cell patterning, emerges as a powerful tool for constructing novel invitro 3D models that mimic organs and cancers features. However, understanding changes in cell function post-AH remains limited. Furthermore, replicating complex physiological and pathological processes solely with cell lines proves challenging. Here, we employed acoustical holographic lattice to assemble primary hepatocytes directly isolated from mice into a cell cluster matrix to construct a liver-shaped tissue sample. For the first time, we evaluated the liver functions of AH-patterned primary hepatocytes. The patterned model exhibited large numbers of self-assembled spheroids and superior multifarious core hepatocyte functions compared to cells in 2D and traditional 3D culture models. AH offers a robust protocol for long-term in vitro culture of primary cells, underscoring its potential for future applications in disease pathogenesis research, drug testing, and organ replacement therapy.
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Affiliation(s)
- Changcan Li
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China; Department of General Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Gang Xu
- Liver Transplant Center, Organ Transplant Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yinhan Wang
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Laixin Huang
- Shenzhen Institute of Advanced Technology, And Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China
| | - Feiyan Cai
- Shenzhen Institute of Advanced Technology, And Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China
| | - Long Meng
- Shenzhen Institute of Advanced Technology, And Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China
| | - Bao Jin
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Zhuoran Jiang
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, OX3 7DQ, UK
| | - Hang Sun
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Haitao Zhao
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Xin Lu
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Xingting Sang
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China
| | - Pengyu Huang
- Institute of Biomedical Engineering, PUMC & Chinese Academy of Medical Sciences (CAMS), Tianjin, China
| | - Fei Li
- Shenzhen Institute of Advanced Technology, And Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China.
| | - Huayu Yang
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China.
| | - Yilei Mao
- Department of Liver Surgery, Peking Union Medical College (PUMC) Hospital, PUMC & Chinese Academy of Medical Sciences (CAMS), Beijing, China.
| | - Hairong Zheng
- Shenzhen Institute of Advanced Technology, And Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, Shenzhen, China.
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In A, Strohman A, Payne B, Legon W. Low-intensity focused ultrasound to the posterior insula reduces temporal summation of pain. Brain Stimul 2024; 17:911-924. [PMID: 39089647 DOI: 10.1016/j.brs.2024.07.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 07/24/2024] [Accepted: 07/29/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND The insula and dorsal anterior cingulate cortex (dACC) are core brain regions involved in pain processing and central sensitization, a shared mechanism across various chronic pain conditions. Methods to modulate these regions may serve to reduce central sensitization, though it is unclear which target may be most efficacious for different measures of central sensitization. OBJECTIVE/HYPOTHESIS Investigate the effect of low-intensity focused ultrasound (LIFU) to the anterior insula (AI), posterior insula (PI), or dACC on conditioned pain modulation (CPM) and temporal summation of pain (TSP). METHODS N = 16 volunteers underwent TSP and CPM pain tasks pre/post a 10 min LIFU intervention to either the AI, PI, dACC or Sham stimulation. Pain ratings were collected pre/post LIFU. RESULTS Only LIFU to the PI significantly attenuated pain ratings during the TSP protocol. No effects were found for the CPM task for any of the LIFU targets. LIFU pressure modulated group means but did not affect overall group differences. CONCLUSIONS LIFU to the PI reduced temporal summation of pain. This may, in part, be due to dosing (pressure) of LIFU. Inhibition of the PI with LIFU may be a future potential therapy in chronic pain populations demonstrating central sensitization. The minimal effective dose of LIFU for efficacious neuromodulation will help to translate LIFU for therapeutic options.
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Affiliation(s)
- Alexander In
- Virginia Tech Carilion School of Medicine, Roanoke, VA, 24016, USA
| | - Andrew Strohman
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA; Virginia Tech Carilion School of Medicine, Roanoke, VA, 24016, USA; Graduate Program in Translational Biology, Medicine, and Health, Virginia Polytechnic Institute and State University, Roanoke, VA, 24016, USA
| | - Brighton Payne
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA
| | - Wynn Legon
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA; Virginia Tech Carilion School of Medicine, Roanoke, VA, 24016, USA; Center for Human Neuroscience Research, Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA; Center for Health Behaviors Research, Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, 24016, USA; School of Neuroscience, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24016, USA; Graduate Program in Translational Biology, Medicine, and Health, Virginia Polytechnic Institute and State University, Roanoke, VA, 24016, USA; Department of Neurosurgery, Carilion Clinic, Roanoke, VA, 24016, USA.
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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 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] [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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Muller JW, Schwab HM, Wu M, Rutten MCM, van Sambeek MRHM, Lopata RGP. Enabling strain imaging in realistic Eulerian ultrasound simulation methods. ULTRASONICS 2023; 135:107127. [PMID: 37573737 DOI: 10.1016/j.ultras.2023.107127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 07/07/2023] [Accepted: 07/30/2023] [Indexed: 08/15/2023]
Abstract
Cardiovascular strain imaging is continually improving due to ongoing advances in ultrasound acquisition and data processing techniques. The phantoms used for validation of new methods are often burdensome to make and lack flexibility to vary mechanical and acoustic properties. Simulations of US imaging provide an alternative with the required flexibility and ground truth strain data. However, the current Lagrangian US strain imaging models cannot simulate heterogeneous speed of sound distributions and higher-order scattering, which limits the realism of the simulations. More realistic Eulerian modelling techniques exist but have so far not been used for strain imaging. In this research, a novel sampling scheme was developed based on a band-limited interpolation of the medium, which enables accurate strain simulation in Eulerian methods. The scheme was validated in k-Wave using various numerical phantoms and by a comparison with Field II. The method allows for simulations with a large range in strain values and was accurate with errors smaller than -60 dB. Furthermore, an excellent agreement with the Fourier theory of US scattering was found. The ability to perform simulations with heterogeneous speed of sound distributions was demonstrated using a pulsating artery model. The developed sampling scheme contributes to more realistic strain imaging simulations, in which the effect of heterogenous acoustic properties can be taken into account.
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Affiliation(s)
- Jan-Willem Muller
- Photoacoustics & Ultrasound Laboratory Eindhoven (PULS/e), Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Vascular Surgery, Catharina Hospital, Eindhoven, The Netherlands.
| | - Hans-Martin Schwab
- Photoacoustics & Ultrasound Laboratory Eindhoven (PULS/e), Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | - Min Wu
- Photoacoustics & Ultrasound Laboratory Eindhoven (PULS/e), Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | - Marcel C M Rutten
- Cardiovascular Biomechanics Group, Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
| | - Marc R H M van Sambeek
- Photoacoustics & Ultrasound Laboratory Eindhoven (PULS/e), Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Vascular Surgery, Catharina Hospital, Eindhoven, The Netherlands.
| | - Richard G P Lopata
- Photoacoustics & Ultrasound Laboratory Eindhoven (PULS/e), Dept. of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
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5
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Xu P, Wu N, Shen G. A rapid element pressure field simulation method for transcranial phase correction in focused ultrasound therapy. Phys Med Biol 2023; 68:235015. [PMID: 37934058 DOI: 10.1088/1361-6560/ad0a59] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 11/07/2023] [Indexed: 11/08/2023]
Abstract
Transcranial focused ultrasound ablation has emerged as a promising technique for treating neurological disorders. The clinical system exclusively employed the ray tracing method to compute phase aberrations induced by the human skull, taking into account computational time constraints. However, this method compromises slightly on accuracy compared to simulation-based methods. This study evaluates a fast simulation method that simulates the time-harmonic pressure field within the region of interest for effective phase correction. Experimental validation was carried out using a 512-element, 670 kHz hemispherical transducer for fourex vivoskulls. The ray tracing method achieved a restoration ratio of 64.81% ± 4.33% of acoustic intensity normalized to hydrophone measurements. In comparison, the rapid simulation method demonstrated improved results with a restoration ratio of 73.10% ± 7.46%, albeit slightly lower than the full-wave simulation which achieved a restoration ratio of 75.87% ± 5.40%. The rapid simulation methods exhibited computational times that were less than five minutes for parallel computation with 8 threads. The incident angle was calculated, and a maximum difference of 6.8 degrees was found when the fixed position of the skull was changed. Meanwhile, the restoration ratio of acoustic intensity was validated to be above 70% for different target positions away from the geometrical focus of the transducer. The favorable balance between time consumption and correction accuracy makes this method valuable for clinical treatment applications.
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Affiliation(s)
- Peng Xu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Nan 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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6
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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: 0.5] [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: 19] [Impact Index Per Article: 9.5] [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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Gu J, Jing Y. Corrections to "mSOUND: An Open Source Toolbox for Modeling Acoustic Wave Propagation in Heterogeneous Media". IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2021; 68:3257. [PMID: 34152984 DOI: 10.1109/tuffc.2021.3091311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
In the above article [1]>, the authors regret that there were some mistakes pertaining to (1)-(3) and (5).
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