[论文解读] A Practical Computational Hemolysis Model Incorporating Biophysical Properties of the Red Blood Cell Membrane

Nico Dirkes, Marek Behr|arXiv (Cornell University)|Jan 27, 2026

Blood properties and coagulation被引用 0

一句话总结

论文提出一个实用的欧拉血红蛋白溶解（hemolysis）模型，将黏弹性红细胞膜行为与孔形成导致的血红蛋白释放相结合，在FDA基准案例中使用简单的应变基方法获得准确预测。它比较了应变基与应力基的红细胞模型以及CFD工作流中的两种释放机制。

ABSTRACT

Purpose: Hemolysis is a key issue in the design of blood-handling medical devices. Computational prediction of this phenomenon is challenging due to the complex multiscale nature of blood. As a result, conventional approaches often fail to predict hemolysis accurately, commonly showing deviations of multiple orders of magnitude compared to experimental data. More accurate models are typically computationally expensive and thus impractical for real-world applications. This work aims to fill this gap by presenting accurate yet simple and efficient computational hemolysis models. Methods: Hemolysis modeling relies on two key components: a red blood cell model and a hemoglobin release model. In this work, we compare three red blood cell models: a common stress-based model (Bludszuweit), a simple strain-based model based on the Kelvin-Voigt constitutive law, and a more complex tensor-based model (TTM). Further, we compare two hemoglobin release models: the widely used power-law approach and a biophysical pore formation model. Results: We evaluate these models in two benchmark cases: the FDA blood pump and the FDA nozzle. In both benchmarks, the simple strain-based model combined with the pore formation model achieves absolute predictions of hemolysis within the standard deviation of experimental measurements. In contrast, stress-based power law models deviate by several orders of magnitude. Conclusion: The strain-based pore modeling approach takes into account the biophysical properties of red blood cell membranes, in particular their viscoelastic deformation behavior and hemoglobin release through membrane pores. This leads to significantly improved hemolysis predictions in a framework that can easily be integrated into common CFD workflows.

研究动机与目标

• 改进、计算高效的血液处理设备溶血预测。
• 在欧拉框架中融入生物物理膜特性（黏弹形变）。
• 将孔形成的血红蛋白释放与经验幂律方法进行对比评估。
• 提供易于整合入CFD工作流的模块化建模框架。

提出的方法

• 以不可压缩牛顿流体作为CFD基础，提取速度场和速度梯度场。
• 比较三种红细胞变形模型：Bludszuweit（应力基）、Kelvin-Voigt（KV，黏弹性应变基）、Tank-Treading Model（TTM，滚动-拉伸）模型。
• 采纳两种血红蛋白释放模型：幂律经验模型和生物物理孔形成模型（Vitale 等简化版）。
• 从红细胞模型推导有效剪切率 G_eff，以驱动溶血度量，独立于粘度。
• 以全球量量 IH 与 MIH 来表征溶血，MIH 将 IH 在装置出口场景上积分。
• 以欧拉形式实现（Dφ/Dt = F(φ, ∇u)），配合适用于三维流动的边界条件与初始条件。

实验结果

研究问题

• RQ1 应变基的黏弹性红细胞模型结合孔形成释放机制，是否比应力基和纯经验方法在溶血预测上更准确？
• RQ2 在三维应力状态和红细胞取向（TTM）影响下，预测的溶血与简化的剪切仅公式相比有何差异？
• RQ3 将所提模型整合入标准CFD工作流，在代表性的FDA基准（如转泵和喷嘴）上是否仍然准确？
• RQ4 对红细胞模型选择和释放机制的敏感性如何？

主要发现

• 应变基KV模型结合孔形成释放模型在FDA基准问题中实现了绝对溶血预测，与实验标准差一致。
• 应力基幂律模型在同一基准中相对于实验数据存在数量级的偏差。
• 在拉伸流动中，TTM预测的变形大于KV，凸显了三维应力效应。
• 该方法将生物物理的红细胞膜特性整合到适用于大规模CFD仿真的高效欧拉框架中。
• 孔形成为基础的释放，与 G_eff 和膜应变相关，提供了红细胞变形与Hb释放之间的机制联系。
• 该框架设计易于在现有CFD求解器中实现，适用于一般三维流动。