心肌生物力学功能评估中主动应力波的量化与可视化研究。

Computing in cardiology Pub Date : 2019-09-01 Epub Date: 2020-02-24 DOI:10.22489/cinc.2019.425
Niels F Otani, Dylan Dang, Christopher Beam, Fariba Mohammadi, Brian Wentz, S M Kamrul Hasan, Suzanne M Shontz, Karl Q Schwarz, Sabu Thomas, Cristian A Linte
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引用次数: 0

摘要

估计和可视化心肌活动应力波模式对于了解心脏的机械活动至关重要,并提供了一种潜在的非侵入性方法来评估心肌功能。这些模式可以通过分析使用医学成像获得的2D和/或3D组织位移数据来重建。在这里,我们描述了一个利用三维有限元公式从位移数据重建活动应力的应用程序。作为概念证明,一个简单的立方网格被用来表示心肌组织“样本”,该样本由10 × 10 × 10的节点晶格组成,这些节点具有不同的纤维方向,随深度旋转,模拟心脏的横向各向同性。在正演模型中,使用具有模拟心肌收缩力的主动应力的测试波来产生组织变形。将生成的变形场作为反演模型的输入,重建原始活动应力分布。我们在健康组织中数值模拟了功能失调的组织区域(经历有限的收缩性和主动应力)。我们还通过在正演模型产生的变形场中加入噪声来评估模型的灵敏度。原始和重建的活应力分布差图表明,该模型从组织变形数据中准确估计出活应力,具有较高的信噪比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Toward Quantification and Visualization of Active Stress Waves for Myocardial Biomechanical Function Assessment.

Toward Quantification and Visualization of Active Stress Waves for Myocardial Biomechanical Function Assessment.

Toward Quantification and Visualization of Active Stress Waves for Myocardial Biomechanical Function Assessment.

Toward Quantification and Visualization of Active Stress Waves for Myocardial Biomechanical Function Assessment.

Estimating and visualizing myocardial active stress wave patterns is crucial to understanding the mechanical activity of the heart and provides a potential non-invasive method to assess myocardial function. These patterns can be reconstructed by analyzing 2D and/or 3D tissue displacement data acquired using medical imaging. Here we describe an application that utilizes a 3D finite element formulation to reconstruct active stress from displacement data. As a proof of concept, a simple cubic mesh was used to represent a myocardial tissue "sample" consisting of a 10 × 10 × 10 lattice of nodes featuring different fiber directions that rotate with depth, mimicking cardiac transverse isotropy. In the forward model, tissue deformation was generated using a test wave with active stresses that mimic the myocardial contractile forces. The generated deformation field was used as input to an inverse model designed to reconstruct the original active stress distribution. We numerically simulated malfunctioning tissue regions (experiencing limited contractility and hence active stress) within the healthy tissue. We also assessed model sensitivity by adding noise to the deformation field generated using the forward model. The difference image between the original and reconstructed active stress distribution suggests that the model accurately estimates active stress from tissue deformation data with a high signal-to-noise ratio.

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