从图像数据估计左心室舒张和收缩材料特性:左室力学挑战。

Adarsh Krishnamurthy, Christopher Villongco, Amanda Beck, Jeffrey Omens, Andrew McCulloch
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引用次数: 7

摘要

使用患者特定几何形状的心血管模拟可以帮助研究人员了解心脏在不同负荷或疾病条件下的机械行为。然而,为了准确地复制心脏的区域力学,必须可靠地估计非线性被动和主动材料的特性。在本文中,采用自动化方法来确定被动材料的性能,同时计算心室的卸载参考几何形状进行应力分析。两种不同的方法用于模拟收缩。首先,将基于生理的主动收缩模型[1]与血液动力学的三元素Windkessel循环模型相结合,模拟心室射血。在第二种情况下,在规定已知的收缩期末压力时,直接调整已发展的主动张力以匹配收缩期末的心室容积。这些方法在四只正常狗身上进行了测试,使用的是为LV力学挑战提供的数据[2]。将模拟得到的舒张末期和收缩末期几何形状与实测图像数据进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Left Ventricular Diastolic and Systolic Material Property Estimation from Image Data: LV Mechanics Challenge.

Cardiovascular simulations using patient-specific geometries can help researchers understand the mechanical behavior of the heart under different loading or disease conditions. However, to replicate the regional mechanics of the heart accurately, both the nonlinear passive and active material properties must be estimated reliably. In this paper, automated methods were used to determine passive material properties while simultaneously computing the unloaded reference geometry of the ventricles for stress analysis. Two different approaches were used to model systole. In the first, a physiologically-based active contraction model [1] coupled to a hemodynamic three-element Windkessel model of the circulation was used to simulate ventricular ejection. In the second, developed active tension was directly adjusted to match ventricular volumes at end-systole while prescribing the known end-systolic pressure. These methods were tested in four normal dogs using the data provided for the LV mechanics challenge [2]. The resulting end-diastolic and end-systolic geometry from the simulation were compared with measured image data.

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