Flow-induced hemolysis in blood-carrying medical devices – a data-based mechanistic approach

带血医疗器械为患有严重心血管和呼吸系统疾病的患者提供了拯救生命的解决方案，这些疾病是全球第一和第三大最常见的死亡原因，2017年共有2170万人死亡。尽管在过去的几十年中，患者的生存率和整体生活质量有了巨大的改善，但器械引起的血液创伤和损伤仍然是并发症的主要来源。红细胞膜的损伤和随后血红蛋白的释放被称为溶血，是与死亡率增加相关的决定性并发症之一。溶血导致器官供氧减少，并在其他血液相关现象（如血小板活化和血栓形成）中起核心作用。使用实验和数值方法更好地理解机械诱导溶血对于改进当前载血医疗器械的设计是必要的。在这方面，计算流体动力学（CFD）已成为一种广泛使用的工具，用于捕获血流动力学和器械诱导溶血的复杂现象。然而，目前的数值模拟方法缺乏定量预测的潜力，由于实验数据的基础上的缺陷和可重复的方法稀缺的建议的首要目标是提高数值溶血模型的预测潜力。首先，将测量不同剪切速率和暴露时间下的血液损伤，并对数据进行各种数据分析和质量控制技术，以确保数据集可重复使用。在下一步中，将创建具有所有现有溶血模型的基准设置，并将包括测量数据集。最后，将开发新的实验方法来模拟旋转血泵中红细胞的瞬态损伤历史，并扩展现有的溶血数值模型，以更好地描述发生的血液损伤机制。最终，基准和血液损伤数据集将通过在线平台提供，以允许项目范围以外的其他研究小组重复使用。拟议的项目将主要专注于标准化、再现性和数据整合，以解决溶血的内在复杂性和现有数值模型的多样性。它专注于血液携带医疗设备的核心问题，并提供许多临床应用，如机械心脏支持系统或体外肺支持（ECMO）。

Blood-carrying medical devices have provided life-saving solutions for patients with severe cardiovascular and respiratory diseases which are the first and third most frequent causes of mortality worldwide with a total of 21.7 million deaths in 2017. Despite the tremendous improvements in patient survival and overall quality of life over the last decades, device induced blood traumatization and damage is still a major source for complications. The damage of the red blood cell membrane and the subsequent release of hemoglobin is called hemolysis and is one of the decisive complications associated with increased mortality. Hemolysis leads to a reduced oxygen supply of organs and plays a central role in other blood related phenomena such as platelet activation and thrombus formation. A better understanding of mechanically induced hemolysis using experimental and numerical methods is necessary to improve the design of current blood-carrying medical devices. On this front, computational fluid dynamics (CFD), has become a widely used tool to capture the complex phenomena of blood flow dynamics and the device induced hemolysis. However, current numerical modeling approaches lack quantitative prediction potential due to shortcomings in the experimental data basis and a scarcity of reproducible methods.The overarching goal of the proposal is to improve the prediction potential of numerical hemolysis models. At first, blood damage at various shear rates and exposure times will be measured and the data will undergo various data analysis and quality control techniques to ensure a reusable dataset. In the next step, a benchmarking setup with all existing hemolysis models will be created and the measured dataset will be included. Lastly, new experimental methods to model the transient damage history of red blood cells in rotary blood pumps will be developed and existing numerical models of hemolysis will be expanded to better describe the occurring blood damage mechanisms.Ultimately the benchmarks and the blood damage dataset will be presented via an online platform to allow reusability by other research groups beyond the scope of the project.The proposed project puts a major focus on standardization, reproducibility and data integration in order to tackle the intrinsic complexity of hemolysis and the diversity of existing numerical models. It focuses on a central problem in blood-carrying medical devices and offers many clinical applications such as mechanical heart support systems or extracorporeal lung support (ECMO).