Ebrahimi Nejad Shiva, Carey Jason P, McMurtry M Sean, Hahn Jin-Oh
Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada.
Department of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.
Biomech Model Mechanobiol. 2017 Apr;16(2):549-560. doi: 10.1007/s10237-016-0836-8. Epub 2016 Sep 21.
In this study, we developed and examined the feasibility of a model-based system identification approach to cardiovascular disease diagnosis. The basic premise of the approach is that it may be possible to diagnose cardiovascular disease from disease-induced alterations in the arterial mechanical properties manifested in the proximal and distal arterial blood pressure waveforms. It first individualizes the lumped-parameter model of wave propagation and reflection in the artery using the measurement of proximal and distal arterial blood pressure waveforms. Then, it employs a diagnosis logic, in the form of disease-specific patterns in model parameters, referred as [Formula: see text] and pulse transit time. The longitudinal change in these parameters is used to diagnose the presence of peripheral artery disease and arterial stiffening. We illustrated the feasibility of the proposed approach by testing it in a full-scale in-silico arterial tree simulation. The results showed that the approach exhibited superior sensitivity to ankle-brachial index and convenience to carotid-femoral pulse wave velocity: The model parameters [Formula: see text] and [Formula: see text] responded with up to 100 and 40 % changes to peripheral artery disease with up to 50 % arterial blockage whereas the change in ankle-brachial index was [Formula: see text]; the same parameters responded with up to 300 and 40 % changes to up to 100 % arterial stiffening while pulse transit time changed by up to 24 %. Together with the development of more convenient techniques for the measurement of arterial blood pressure waveforms, the proposed approach may evolve into a viable alternative to the state-of-the-art techniques for cardiovascular disease diagnosis.
在本研究中，我们开发并检验了一种基于模型的系统识别方法用于心血管疾病诊断的可行性。该方法的基本前提是，有可能从近端和远端动脉血压波形中所表现出的疾病引起的动脉力学特性改变来诊断心血管疾病。它首先利用近端和远端动脉血压波形的测量结果，对动脉中波传播和反射的集总参数模型进行个体化。然后，它采用一种诊断逻辑，以模型参数中疾病特异性模式的形式呈现，称为[公式：见原文]和脉搏传输时间。这些参数的纵向变化用于诊断外周动脉疾病和动脉僵硬度的存在。我们通过在全尺寸的计算机模拟动脉树中对其进行测试，说明了所提出方法的可行性。结果表明，该方法对踝臂指数表现出更高的敏感性，对颈股脉搏波速度表现出更高的便利性：对于高达50%动脉阻塞的外周动脉疾病，模型参数[公式：见原文]和[公式：见原文]的变化分别高达100%和40%，而踝臂指数的变化为[公式：见原文]；对于高达100%的动脉僵硬度，相同参数的变化分别高达300%和40%，而脉搏传输时间的变化高达24%。随着测量动脉血压波形的更便捷技术的发展，所提出的方法可能会演变成一种替代心血管疾病诊断现有技术的可行方法。
