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通过量化超声多次散射来表征随机复杂生物介质

Characterizing random complex biological media by quantifying ultrasound multiple scattering.

作者信息

Yousefian Omid, Dashti Azadeh, Geithner Haley, Karbalaeisadegh Yasamin, Yao Shanshan, Blackwell John, Ali Mir, Montgomery Stephanie, Zhu Yong, Egan Thomas, Muller Marie

机构信息

Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, United States.

Surgery, University of North Carolina, Chapel Hill, NC, United States.

出版信息

Front Acoust. 2025;3. doi: 10.3389/facou.2025.1545057. Epub 2025 Apr 8.

Abstract

INTRODUCTION

In this , , and study, we propose metrics for the characterization of highly scattering media using backscattered acoustic waves in the MHz range, for application to the characterization of biological media.

METHODS

Multi-element array transducers are used to record the ultrasonic Inter element Response Matrix (IRM) of scattering phantoms and of lung tissue in rodent models of pulmonary fibrosis. The distribution of singular values of the IRM in the frequency domain is then studied to quantify the multiple scattering contribution. Numerical models of scattering media, as well as gelatin-glass bead and polydimethylsiloxane phantoms with different scatterer densities, are used as a first step to demonstrate the proof of concept.

RESULTS

The results show that changes in microstructure of a complex random medium affect parameters associated with the distribution of singular values. Two metrics are proposed: (), which is the expected value of the singular value distribution, and , the maximum value of the probability density function of the singular value distribution, i.e., the most represented singular value. After validation of the methods and in phantoms, we show that these metrics are relevant to evaluate pulmonary fibrosis in an rodent study on six control rats and eighteen rats with varying degrees of severity of pulmonary fibrosis. In rats, a moderate correlation was found between the severity of pulmonary fibrosis and metrics () and .

DISCUSSION

These results suggest that such parameters could be used as metrics to estimate the amount of multiple scattering in highly heterogeneous media, and that these parameters could contribute to the evaluation of structural changes in lung microstructure.

摘要

引言

在本[具体内容缺失]研究中,我们提出了利用兆赫兹范围内的反向散射声波来表征高散射介质的指标,以应用于生物介质的表征。

方法

使用多元素阵列换能器记录散射体模以及肺纤维化啮齿动物模型中肺组织的超声阵元间响应矩阵(IRM)。然后研究IRM在频域中的奇异值分布,以量化多次散射贡献。作为概念验证的第一步,使用散射介质的数值模型以及具有不同散射体密度的明胶 - 玻璃珠和聚二甲基硅氧烷体模。

结果

结果表明,复杂随机介质微观结构的变化会影响与奇异值分布相关的参数。提出了两个指标:([具体指标名称缺失]),即奇异值分布的期望值,以及[具体指标名称缺失],奇异值分布概率密度函数的最大值,即最具代表性的奇异值。在体模中对这些方法进行验证后,我们表明这些指标与在一项针对六只对照大鼠和十八只不同程度肺纤维化严重程度大鼠的啮齿动物研究中评估肺纤维化相关。在大鼠中,发现肺纤维化严重程度与指标([具体指标名称缺失])和[具体指标名称缺失]之间存在中度相关性。

讨论

这些结果表明,此类参数可作为估计高度异质介质中多次散射量的指标,并且这些参数有助于评估肺微观结构的结构变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee6d/12068836/76ae9bee682d/nihms-2078166-f0001.jpg

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