Suppr超能文献

基于稳健波束形成的超声神经调制分辨率对脑组织声速的计算敏感性评估

Computational sensitivity evaluation of ultrasound neuromodulation resolution to brain tissue sound speed with robust beamforming.

作者信息

Fan Boqiang, Goodman Wayne, Sheth Sameer A, Bouchard Richard R, Aazhang Behnaam

机构信息

Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA.

Department of Psychiatry and Behavioral Science, Baylor College of Medicine, Houston, TX, 77030, USA.

出版信息

Sci Rep. 2025 Apr 2;15(1):11251. doi: 10.1038/s41598-025-95396-x.

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 [Formula: see text] on average and up to [Formula: see text], 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.

摘要

低强度聚焦超声(LIFU)神经调节需要相控阵换能器和波束形成实现精确靶向和高分辨率。然而,聚焦优化通常依赖于体模测量或具有不准确声学特性的模拟,从而降低神经调节分辨率。因此,本研究分析了以非靶标激活区域(OTAA)衡量的神经调节分辨率对脑组织声速的敏感性。提出了一种鲁棒最优分辨率(ROR)波束形成方法,以在声速不准确和用偏离声速估计的传播信息受限的情况下,将最坏情况下的OTAA最小化。传播估计模型利用等效源法(ESM)在不同声学参数集之间映射声场。在人体头部模型中的仿真验证了所提出的传播估计模型的有效性,并表明ROR波束形成方法与基准方法相比,平均可将最坏情况下的OTAA显著降低[公式:见原文],最高可达[公式:见原文],提高了刺激的鲁棒性并解决了敏感性问题。这使得在潜在临床应用中能够进行可靠的高分辨率神经调节,同时减少用于聚焦优化的传播测量的侵入性采集。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f61d/11965375/be8464b8f56b/41598_2025_95396_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验