North Carolina State University, Raleigh, NC, United States of America.
Phys Med Biol. 2023 Feb 23;68(5). doi: 10.1088/1361-6560/acba7a.
. Arterial viscosity is emerging as an important biomarker, in addition to the widely used arterial elasticity. This paper presents an approach to estimate arterial viscoelasticity using shear wave elastography (SWE).. While dispersion characteristics are often used to estimate elasticity from SWE data, they are not sufficiently sensitive to viscosity. Driven by this, we develop a full waveform inversion (FWI) methodology, based on directly matching predicted and measured wall velocity in space and time, to simultaneously estimate both elasticity and viscosity. Specifically, we propose to minimize an objective function capturing the correlation between measured and predicted responses of the anterior wall of the artery.. The objective function is shown to be well-behaving (generally convex), leading us to effectively use gradient optimization to invert for both elasticity and viscosity. The resulting methodology is verified with synthetic data polluted with noise, leading to the conclusion that the proposed FWI is effective in estimating arterial viscoelasticity.. Accurate estimation of arterial viscoelasticity, not just elasticity, provides a more precise characterization of arterial mechanical properties, potentially leading to a better indicator of arterial health.
动脉粘度正成为除广泛使用的动脉弹性之外的另一个重要生物标志物。本文提出了一种使用剪切波弹性成像（SWE）来估计动脉粘弹性的方法。虽然弥散特性常用于从 SWE 数据估计弹性，但它们对粘度的敏感性不够。受此启发，我们开发了一种全波形反演（FWI）方法，该方法基于直接在空间和时间上匹配预测和测量的壁速度，以同时估计弹性和粘度。具体来说，我们建议通过最小化目标函数来同时估计动脉弹性和粘度，该目标函数捕捉了动脉前壁测量和预测响应之间的相关性。
目标函数表现良好（通常是凸的），这使我们能够有效地使用梯度优化来反演弹性和粘度。该方法通过噪声污染的合成数据进行了验证，结论表明，所提出的 FWI 能够有效地估计动脉粘弹性。
准确估计动脉粘弹性（不仅仅是弹性）可以更精确地描述动脉的力学特性，可能成为更好的动脉健康指标。
