Alzhanov Nursultan, Ng Eddie Y K, Su Xiaohui, Zhao Yong
Mechanical and Aerospace Engineering Department, School of Engineering, Nazarbayev University, Asana 010000, Kazakhstan.
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore.
Bioengineering (Basel). 2023 Feb 28;10(3):309. doi: 10.3390/bioengineering10030309.
A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA was based on an extension of Murray's law and additional inlet conditions prescribed iteratively and was implemented in OpenFOAM v1912 for testing and validation. 3D models of CATs were created using CT scans and computational meshes, and the results were compared to invasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between the calculated and experimental FFR was within 2.33-5.26% in the steady-state and transient simulations, respectively, when convergence was reached. The PBA was a reliable and physiologically sound technique compared to a current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for convergence. The accuracy of the PBA method was further confirmed using an FDA nozzle, which demonstrated good alignment with the CFD-validated values.
提出并开发了一种基于生理学的新型算法（PBA），用于使用计算流体动力学（CFD）计算冠状动脉树（CAT）中的血流储备分数（FFR）。PBA基于默里定律的扩展以及迭代规定的附加入口条件，并在OpenFOAM v1912中实现以进行测试和验证。使用CT扫描和计算网格创建CAT的三维模型，并将结果与侵入性冠状动脉造影（ICA）数据进行比较，以验证PBA的准确性和有效性。当达到收敛时，在稳态和瞬态模拟中，计算得到的FFR与实验FFR之间的差异分别在2.33%-5.26%以内。与当前基于经验缩放相关性且需要非线性迭代计算以实现收敛的集总参数模型（LPM）相比，PBA是一种可靠且符合生理学原理的技术。使用FDA喷嘴进一步证实了PBA方法的准确性，该喷嘴与CFD验证值显示出良好的一致性。
