Measuring arterial material properties using wave-based approaches with ultrasound and computational models

摘要/摘要 背景：动脉僵硬的增加与脑损伤的指标有关，包括 磁共振评估脑白质高信号、脑梗塞和脑萎缩的存在 成像(MRI)。当船只失去机械吸收脉动流影响的能力时， 脉动传递到大脑中的血管系统，导致脑组织的有害变化。 了解超声测量的中央管道的粘弹性机械性能的影响(例如， 颈动脉相对于MRI测量的脑健康指标可以导致非常重要的工具 预测和管理大脑功能的变化。这项研究项目旨在解决这些未满足和 迫切需要开发准确和可平移的超声测量技术 粘弹性动脉的机械特性，并评估与大脑结构变化的相关性。 方法：超声是血管评估的一线成像手段，但大多数临床扫描仪不能。 有能力准确地评估血管的弹性或粘弹性机械性能， 具有高时间分辨率的定量方式。在这笔赠款的第一个周期中，我们开发了一种超声波- 一种名为动脉弥散超声测振(ADUV)的方法，利用声辐射力 刺激动脉壁中的高频(200-1500赫兹)波，然后高帧频超声波 测量波动，用来表征动脉的粘弹性力学特性。 然而，我们的研究表明，在将ADUV用于 在诊所里每天都有。这些改进包括提高波动信噪比， 用超声波对血管几何形状进行精确测量，并改进我们的倒置和 分类框架。使用这些改进的ADUV方法，我们将评估粘弹性 根据磁共振脑成像的判断，颈动脉的特性与大脑的健康有关 形态数据。拥有强大的协作团队，包括心血管医学、放射学、 超声波工程，波导建模，反问题，数据归约和分类，我们将带来 ADUV更接近广泛翻译，具体目标如下： 目标1)优化ADUV以提高运动测量质量，从而更加准确和精确 力学性能估算。 目的2)开发用于估计动脉机械特性的高级数学模型 疾病状态的分类。 目的3)颈动脉粘弹性ADUV测量与脑MRI指标的相关性研究 病人的健康。

ABSTRACT/SUMMARY Background: Increased arterial stiffness has been associated with indicators of damage to the brain including presence of white matter hyperintensity, infarctions, and brain atrophy as assessed with magnetic resonance imaging (MRI). When vessels lose their ability to mechanically absorb the effects of pulsatile flow, that pulsatility is transmitted to the vasculature in the brain leading to deleterious changes in the brain tissue. Understanding the effect of ultrasound measured viscoelastic mechanical properties of central conduit (e.g., carotid) arteries relative to MRI measured brain health indicators could result in a very important tool for predicting and managing changes in brain function. This research project aims to address these unmet and critical needs to develop techniques for the accurate and translatable ultrasound measurement of viscoelastic arterial mechanical properties and evaluate associations with structural changes in the brain. Methods: Ultrasound is a first-line imaging modality for vascular evaluation, but most clinical scanners do not have the ability to evaluate the elastic or viscoelastic mechanical properties of vessels in an accurate, quantitative manner with high temporal resolution. In the first cycle of this grant, we developed an ultrasound- based method called arterial dispersion ultrasound vibrometry (ADUV) that utilizes acoustic radiation force to stimulate high-frequency (200-1500 Hz) waves in the arterial wall, followed by high frame rate ultrasound to measure the wave motion, which is used to characterize arterial viscoelastic mechanical properties. However, our research revealed that several aspects of ADUV could be further improved before being used on a daily basis in the clinic. Among these improvements are increasing the wave motion signal-to-noise ratio, making precise measurements of the vessel geometry with ultrasound, and improving our inversion and classification frameworks. With these improved ADUV methods, we will evaluate how the viscoelastic properties of the carotid artery are associated with the health of the brain as judged using MRI brain morphology data. With the strong collaborative team including expertise in cardiovascular medicine, radiology, ultrasound engineering, waveguide modeling, inverse problems, data reduction and classification, we will bring ADUV closer to widespread translation with the following Specific Aims: Aim 1) Optimize ADUV to enhance motion measurement quality for more accurate and precise mechanical property estimation. Aim 2) Develop advanced mathematical models for estimation of arterial mechanical properties and classification of disease state. Aim 3) Correlate ADUV measurements of carotid artery viscoelasticity with MRI indicators of brain health in patients.