Computational Fluid Dynamics Modelling of Blood Flow in Patients with Coronary Artery Disease

缺血性心脏病是一种冠状动脉血流量减少的疾病，是世界上导致死亡的主要原因，但在常规临床应用中没有测量冠状动脉血流量的方法。最近，我们发明、开发、验证了一种基于计算流体力学（CFD）的冠状动脉血流测量方法virtuQ，并获得了专利（Wellcome Trust Fellowship: 214567/Z/18/Z；英国专利号：1813170.6，验证论文：doi:10.1093/cvr/cvaa220）。virtuQ从基于x射线的血管造影投影（左图）生成冠状动脉的三维路径重建，但在这种模式下，关于横截面形状及其沿动脉变化（影响生理准确性）的数据受到强烈限制。此外，与人类心脏不同，CFD流动分析是稳态的，在这种简化中丢失了大量潜在的诊断信息。该项目将解决这两个关键问题，一个是通过解决上述模型限制，另一个是通过开发机器学习方法来解释分析工作流程的结果。由此产生的软件解决方案不仅将是世界上第一个，而且有非常强烈的工业兴趣，它们很可能被转化为现实世界的临床工具。

Ischaemic heart disease is a reduction in coronary blood flow and the leading cause of death in the world, yet there are no methods for measuring coronary flow in routine clinical use. Recently, we invented, developed, validated and patented a computational fluid dynamics (CFD) based method for measuring coronary flow called virtuQ (Wellcome Trust Fellowship: 214567/Z/18/Z; UK patent no:1813170.6, validation paper: doi:10.1093/cvr/cvaa220). virtuQ generates a reconstruction of the three-dimensional paths of the coronary arteries from the xray-based angiographic projections (left image) but data on the cross-sectional shape and its variation along the artery (which influences physiological accuracy), is strongly limited in this modality. In addition, unlike the human heart, the CFD flow analysis is steady-state, and a great deal of potentially diagnostic information is lost in this simplification. This project will address these two critical issues, one by addressing the above model limitations, and one by developing machine-learning methodologies to interpret the results of the analysis workflow. Not only will the resulting software solutions be a world first, but there is very strong industrial interest, and they are likely to be translated into real-world clinical tools.