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.

心脏血流动力学分析在心脏病的诊断和治疗中发挥着越来越重要的作用，目前对作为心血管疾病血流动力学生物标志物的复杂参数进行常规评估很困难，但是，数值模型可以计算患者特定心脏的空间和时间解析信息。提出了各种建模方法来分析心脏功能，从简单的 0D 集总元件模型 (LEM) 到耦合电、结构和流体力学的非常复杂的 4D 模型，该项目的最终目标是允许患者特定。所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），从而将患者特定的几何形状描述为加权形状模式的叠加。因此，可以基于平均形状创建左心室的标准化模拟，然后通过调整网格节点来个性化，即使用 CT、MRI 和超声心动图来参数化模拟。使用规定的运动进行建模，这意味着收缩是从图像数据获取的，尽管打开的主动脉和二尖瓣小叶的形状也由形状模型描述，但它们的运动是通过机械有限元模拟来计算的，因为时间-精确的小叶分割通常是不可能的，或者与高度不确定性相关。此外，描述前负荷和后负荷的边界条件，特别是在肺静脉和主动脉处，是由个性化的 LEM 提供的。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精确诊断和治疗决策所需的信息水平，实现患者特定建模的完全自动化的潜力将提高可用性。并最大限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。该方法的可用性将通过使用 MRI 进行分析来展示。该项目的成功实现需要临床和工程科学家之间的密切合作，这在柏林夏里特医学大学心血管计算机辅助医学研究所得到了很好的支持。