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

冠状动脉支架内再狭窄 - 基于患者特定数据和元模型的计算机研究

• 批准号: 465213526
• 负责人: Professor Marek Behr, Ph.D.
• 金额: --
• 依托单位: Klinik für Kardiologie, Angiologie und Internistische Intensivmedizin (Med. Klinik I)
• 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/465213526?language=en
• 关键词: stent; restenosis; coronary; arteries; silico

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.

该项目的临床动机是需要在药物洗脱的情况下成功进行冠状动脉支架置入术。一个严重的问题是所谓的支架内再狭窄(ISR)，它是由于生物材料的病理性生长而发生的。如果考虑到患者的具体情况，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，临床干预是最有效的。长期目标是开发一种电子模拟工具，使心脏病专家能够足够迅速地对心脏病治疗的重要参数做出决定。其中包括支架的几何形状和药物洗脱量。为了实现这一目标，组建了一支由三个学科的科学家组成的团队。来自心脏病学的Vogt教授提供患者特定的数据，并提供有关ISR伴随的生化过程的数据和关键的医学知识。Reese教授从固体力学中获取了这些信息，以模拟动脉壁中相关介质(生长因子、平滑肌细胞和细胞外基质)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体水平。与流体力学的贝尔教授一起研究支架-血流、支架-动脉以及动脉-血液流动界面的建模。他的工作还致力于血流和壁面剪应力的计算，这被认为是对ISR有重要影响的。通过适当的正交分解、分层张量近似和人工神经网络等数值方法，所有这三个合作伙伴都为元模型的开发做出了贡献。从长远来看，这一模型应转化为适用于心脏病学的模拟工具。根据患者特定的输入参数，它将对特定患者的ISR过程和支架植入过程进行预测。