Fluid-Structure-Interaction Modelling of the Heart Hemodynamics using Statistical Shape Models

使用统计形状模型对心脏血流动力学进行流固耦合建模

• 批准号: 465178743
• 负责人: Professor Dr.-Ing. Leonid Goubergrits
• 金额: --
• 依托单位: Institut für Kardiovaskuläre Computer-assistierte Medizin (CVK)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/465178743?language=en
• 关键词: Fluid; Structure; Interaction; Modelling; Heart

Analysis of cardiac hemodynamics plays an increasing role in diagnosis and treatment of heart diseases. A routine assessment of complex parameters proposed as hemodynamic biomarkers for cardiovascular diseases is currently difficult. However, numerical modeling allows calculation of spatially and temporally resolved information of patient-specific heart function. Various modelling approaches are proposed for analysis of heart function, ranging from simple 0D Lumped Element Models (LEM) to very complex 4D models coupling electro-, structural, and fluid mechanics. The final aim of this project is to allow patient-specific simulations under clinical conditions and thus support physicians during clinical routine. The proposed numerical approach will combine computational fluid dynamics (CFD) and statistical shape models (SSM). SSM allow the description of patient-specific geometries as a superposition of weighted shape modes. It is therefore possible to create a standardized simulation of the left ventricle based on an average shape, which is then personalized by adjusting mesh nodes. Different imaging modalities, namely CT, MRI and echocardiography, are used to parameterize the simulation. The ventricular contraction is modelled using a prescribed motion, meaning the contraction is acquired from image data. Although the shape of the opened aortic and mitral valve leaflets is also described by a shape model, their motion is calculated by means of mechanical finite element simulations, since a time-resolved segmentation of leaflets is often not possible or associated with high uncertainty. Furthermore, the boundary conditions describing pre- and afterload, specifically at the pulmonary veins and aorta, are provided by a personalized LEM. The proposed CFD-SSM numerical approach is flexible and allows identification of an optimal model complexity: simple enough to be applicable in a clinical setting and complex enough to provide required level of information for precise diagnosis and treatment decision. The approach should enable robust and fast simulation of cardiac hemodynamics for clinicians. It has the potential to allow complete automation of patient-specific modelling. Automation will improve usability and minimize all user-related errors. The initial clinical focus of the project are heart valve diseases. The usability of the approach will be shown using in-vitro experiments using MRI for an analysis of hemodynamics in phantom models. The successful realization of the project requires close cooperation between clinical and engineering scientists, which is well established at the Institute of Cardiovascular Computer-assisted Medicine at Charité – Universitätsmedizin Berlin.

心脏血液动力学的分析在诊断和心脏病治疗中起着越来越多的作用。目前困难地对作为心血管疾病的血液动力学生物标志物进行的复杂参数进行常规评估。但是，数值建模允许计算患者特异性心脏功能的空间和临时解决信息。提出了各种建模方法，以分析心脏功能，从简单的0D集团元素模型（LEM）到非常复杂的4D模型耦合电，结构和流体机制。该项目的最终目的是允许在临床条件下进行特定于患者的模拟，从而在临床常规过程中支持医生。提出的数值方法将结合计算流体动力学（CFD）和统计形状模型（SSM）。 SSM允许将患者特异性的几何形状描述为加权形状模式的叠加。因此，可以根据平均形状对左心室进行标准化模拟，然后通过调整网格节点来个性化。不同的成像方式，即CT，MRI和超声心动图，用于参数化模拟。心室收缩是使用规定运动对其进行建模的，这意味着收缩是从图像数据中获取的。尽管开放的主动脉和二尖瓣小叶的形状也通过形状模型来描述，但它们的运动是通过机械有限元模拟的方式计算的，因为通常无法使用时间分辨的小叶分割，或者与高不确定性相关。此外，个性化的LEM提供了描述前和后负荷的边界条件，特别是在肺静脉和主动脉处的边界条件。所提出的CFD-SSM数值方法是灵活的，并允许识别最佳模型复杂性：足够简单以适用于临床环境，并且足够复杂，以提供所需的信息水平，以进行精确的诊断和治疗决策。该方法应为临床医生的心脏血流动力学做出稳健而快速的模拟。它有可能允许患者特异性建模的完全自动化。自动化将提高可用性并最大程度地减少所有与用户相关的错误。该项目的最初临床重点是心脏瓣膜疾病。该方法的可用性将使用使用MRI进行体外实验来显示幻影模型中的血液动力学分析。该项目的成功现实需要在临床和工程科学家之间进行密切合作，这在Charité的心血管计算机辅助医学研究所 - 柏林Universitätsmedizinberlin。