Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming
Abstract Low-intensity focused ultrasound (LIFU) neuromodulation requires precise targeting and high resolution enabled by phased array transducers and beamforming. However, focusing optimization usually relies on phantom measurements or simulations with inaccurate acoustic properties to degrade neu...
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-95396-x |
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| author | Boqiang Fan Wayne Goodman Sameer A. Sheth Richard R. Bouchard Behnaam Aazhang |
| author_facet | Boqiang Fan Wayne Goodman Sameer A. Sheth Richard R. Bouchard Behnaam Aazhang |
| author_sort | Boqiang Fan |
| collection | DOAJ |
| description | Abstract Low-intensity focused ultrasound (LIFU) neuromodulation requires precise targeting and high resolution enabled by phased array transducers and beamforming. However, focusing optimization usually relies on phantom measurements or simulations with inaccurate acoustic properties to degrade neuromodulation resolution. Therefore, this work analyzes the sensitivity of neuromodulation resolution, measured by off-target activation area (OTAA), to brain tissue sound speed. A Robust Optimal Resolution (ROR) beamforming method is proposed to minimize the worst-case OTAA with restricted sound speed inaccuracy and propagation information estimated with deviated sound speed. The propagation estimation model utilizes equivalent source method (ESM) to map sound field between different acoustic parameter sets. Simulation in a human head model validates the effectiveness of the proposed propagation estimation model, and shows that ROR beamforming method can significantly reduce the worst-case OTAA compared to benchmark methods by $$78.0 \%$$ on average and up to $$90.0 \%$$ , improving the robustness of stimulation and addressing the sensitivity issue. This allows reliable high-resolution neuromodulation in potential clinical applications with reduced invasive acquisition of propagation measurements for focusing optimization. |
| format | Article |
| id | doaj-art-00efd84bb76c4e10b154c4f492f9ccdd |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-00efd84bb76c4e10b154c4f492f9ccdd2025-08-20T01:54:29ZengNature PortfolioScientific Reports2045-23222025-04-0115111310.1038/s41598-025-95396-xComputational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamformingBoqiang Fan0Wayne Goodman1Sameer A. Sheth2Richard R. Bouchard3Behnaam Aazhang4Department of Electrical and Computer Engineering, Rice UniversityDepartment of Electrical and Computer Engineering, Rice UniversityDepartment of Electrical and Computer Engineering, Rice UniversityDepartment of Imaging Physics, University of Texas MD Anderson Cancer CenterDepartment of Electrical and Computer Engineering, Rice UniversityAbstract Low-intensity focused ultrasound (LIFU) neuromodulation requires precise targeting and high resolution enabled by phased array transducers and beamforming. However, focusing optimization usually relies on phantom measurements or simulations with inaccurate acoustic properties to degrade neuromodulation resolution. Therefore, this work analyzes the sensitivity of neuromodulation resolution, measured by off-target activation area (OTAA), to brain tissue sound speed. A Robust Optimal Resolution (ROR) beamforming method is proposed to minimize the worst-case OTAA with restricted sound speed inaccuracy and propagation information estimated with deviated sound speed. The propagation estimation model utilizes equivalent source method (ESM) to map sound field between different acoustic parameter sets. Simulation in a human head model validates the effectiveness of the proposed propagation estimation model, and shows that ROR beamforming method can significantly reduce the worst-case OTAA compared to benchmark methods by $$78.0 \%$$ on average and up to $$90.0 \%$$ , improving the robustness of stimulation and addressing the sensitivity issue. This allows reliable high-resolution neuromodulation in potential clinical applications with reduced invasive acquisition of propagation measurements for focusing optimization.https://doi.org/10.1038/s41598-025-95396-x |
| spellingShingle | Boqiang Fan Wayne Goodman Sameer A. Sheth Richard R. Bouchard Behnaam Aazhang Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming Scientific Reports |
| title | Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming |
| title_full | Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming |
| title_fullStr | Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming |
| title_full_unstemmed | Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming |
| title_short | Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming |
| title_sort | computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming |
| url | https://doi.org/10.1038/s41598-025-95396-x |
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