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血流的频谱分解及不同严重程度狭窄处声音信号的特征分析

Spectral Decomposition of the Flow and Characterization of the Sound Signals through Stenoses with Different Levels of Severity.

作者信息

Khalili Fardin, Gamage Peshala T, Taebi Amirtahà, Johnson Mark E, Roberts Randal B, Mitchell John

机构信息

Department of Mechanical Engineering, Embry-Riddle Aeronautical University, 1 Aerospace Boulevard, Daytona Beach, FL 32114, USA.

Department of Biomedical and Chemical Engineering and Sciences, Florida Institute of Technology, 2930 Science Cir., Melbourne, FL 32901, USA.

出版信息

Bioengineering (Basel). 2021 Mar 19;8(3):41. doi: 10.3390/bioengineering8030041.

DOI:10.3390/bioengineering8030041
PMID:33808744
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8003520/
Abstract

Treatments of atherosclerosis depend on the severity of the disease at the diagnosis time. Non-invasive diagnosis techniques, capable of detecting stenosis at early stages, are essential to reduce associated costs and mortality rates. We used computational fluid dynamics and acoustics analysis to extensively investigate the sound sources arising from high-turbulent fluctuating flow through stenosis. The frequency spectral analysis and proper orthogonal decomposition unveiled the frequency contents of the fluctuations for different severities and decomposed the flow into several frequency bandwidths. Results showed that high-intensity turbulent pressure fluctuations appeared inside the stenosis for severities above 70%, concentrated at plaque surface, and immediately in the post-stenotic region. Analysis of these fluctuations with the progression of the stenosis indicated that (a) there was a distinct break frequency for each severity level, ranging from 40 to 230 Hz, (b) acoustic spatial-frequency maps demonstrated the variation of the frequency content with respect to the distance from the stenosis, and (c) high-energy, high-frequency fluctuations existed inside the stenosis only for severe cases. This information can be essential for predicting the severity level of progressive stenosis, comprehending the nature of the sound sources, and determining the location of the stenosis with respect to the point of measurements.

摘要

动脉粥样硬化的治疗取决于诊断时疾病的严重程度。能够在早期检测到狭窄的非侵入性诊断技术对于降低相关成本和死亡率至关重要。我们使用计算流体动力学和声学分析,广泛研究了通过狭窄处的高湍流脉动流产生的声源。频谱分析和本征正交分解揭示了不同严重程度下脉动的频率成分,并将流动分解为几个频率带宽。结果表明,对于严重程度超过70%的情况,高强度湍流压力脉动出现在狭窄内部,集中在斑块表面,并紧接着出现在狭窄后区域。随着狭窄程度的进展对这些脉动进行分析表明:(a) 每个严重程度级别都有一个明显的转折频率,范围从40到230赫兹;(b) 声学空间频率图显示了频率成分相对于距狭窄距离的变化;(c) 仅在严重病例中,狭窄内部存在高能、高频脉动。这些信息对于预测进行性狭窄的严重程度级别、理解声源的性质以及确定狭窄相对于测量点的位置可能至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/128d/8003520/e0b8eef1c516/bioengineering-08-00041-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/128d/8003520/5cb4aa539177/bioengineering-08-00041-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/128d/8003520/c807d1ee7d4b/bioengineering-08-00041-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/128d/8003520/e0b8eef1c516/bioengineering-08-00041-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/128d/8003520/02836645535d/bioengineering-08-00041-g004.jpg
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Cardiovasc Eng Technol. 2021 Jun;12(3):286-299. doi: 10.1007/s13239-021-00519-w. Epub 2021 Jan 19.
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Numerical investigation of wall pressure fluctuations downstream of concentric and eccentric blunt stenosis models.
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Bioengineering (Basel). 2022 Apr 1;9(4):149. doi: 10.3390/bioengineering9040149.
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Med Biol Eng Comput. 2019 Aug;57(8):1737-1752. doi: 10.1007/s11517-019-01995-y. Epub 2019 Jun 8.
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High-Frequency Fluctuations in Post-stenotic Patient Specific Carotid Stenosis Fluid Dynamics: A Computational Fluid Dynamics Strategy Study.狭窄后患者特异性颈动脉狭窄流体动力学中的高频波动:一项计算流体动力学策略研究。
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