In-stent restenosis in coronary arteries - in silico investigations based on patient-specific data and meta modeling

该拟议项目的临床动机是成功进行药物洗脱冠状动脉支架植入术的需要。一个严重的问题是所谓的支架内再狭窄（ISR），这是由于生物材料的病理性生长而发生的。如果尽可能考虑到患者特定的情况，如病变动脉的几何形状和状况、钙化区域以及生长因子和细胞迁移的演变，则临床干预是最有效的。长期目标是开发一种计算机模拟工具，使心脏病专家能够对心脏病治疗的重要参数做出足够快的决定。其中包括支架几何形状和洗脱的药物量。为了实现这一目标，已经成立了一个由三个学科的科学家组成的团队。来自心脏病学的沃格特教授提供了患者特定数据，并提供了有关ISR相关生化过程的数据和关键医学知识。Reese教授从固体力学中获得了这些信息，以模拟动脉壁中相关因子（生长因子，平滑肌细胞以及细胞外基质）的演变。后一个过程发生在细胞水平，通过使应变张量依赖于平滑肌细胞密度而耦合到连续介质水平。支架-血流、支架-动脉以及动脉-血流界面的建模与流体力学的Behr教授一起处理。他的工作还致力于计算血流和壁切应力，这些应力被认为对ISR有重要影响。 通过数值方法，如适当的正交分解，分层张量近似，人工神经网络，所有三个合作伙伴的Meta模型的发展作出贡献。从长远来看，该模型应转化为适用于心脏病学的模拟工具。根据患者特定输入参数，它将预测特定患者和支架植入手术的ISR过程。

The proposed project is clinically motivated by the need to successfully perform coronary stenting with drug elution. A severe problem is the so-called in-stent restenosis (ISR), which occurs due to pathological growth of biological material. The clinical intervention is most effective if the patient-specific situation with respect to geometry and condition of the diseased artery, calcified domains, as well as evolution of growth factors and cell migration is taken into account as well as possible. The long-term goal is to develop an in silico simulation tool which enables the cardiologist to make sufficiently quick decisions about important parameters of the cardiological treatment. Among these are the stent geometry and the amount of drug eluted. To reach this goal, a team of scientists from three disciplines has been formed. Prof. Vogt from cardiology provides patient-specific data as well as contributes data and the crucial medical knowledge about the bio-chemical processes accompanying ISR. This information is taken up by Prof. Reese from solid mechanics to model the evolution of the relevant agents (growth factors, smooth muscle cells as well as extracellular matrix) in the arterial wall. The latter process, taking place at the cellular level, is coupled to the continuum level by making the strain tensor dependent on the smooth muscle cell density. The modeling of the interfaces stent-blood flow, stent-artery, as well as artery-blood flow is tackled together with Prof. Behr from fluid mechanics. His work is also devoted to the computation of the blood flow and the wall shear stresses which are assumed to have an important influence on ISR. By means of numerical methods such as proper orthogonal decomposition, hierarchical tensor approximation, and artificial neural networks, all three partners contribute to the development of a meta model. In the long run, this model shall be transferred into a simulation tool applicable in cardiology. Based on the patient-specific input parameters, it will give a forecast about the ISR process for a specific patient and stent implantation procedure.