Computational Analysis of the Pulmonary Arteries in Congenital Heart Disease: A Review of the Methods and Results.
Computational Analysis of the Pulmonary Arteries in Congenital Heart Disease: A Review of the Methods and Results.
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DOI：
10.1155/2021/2618625
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发表时间：
2021
影响因子：
--
通讯作者：
Krings GJ
中科院分区：
文献类型：
--
作者：
Conijn M;Krings GJ
借助计算流体动力学（CFD），可以详细研究肺动脉（PA）的血液动力学，并模拟不同的生理环境和治疗方案。这为改善双室先天性心脏病（CHD）PA狭窄的诊断和治疗提供了机会。本综述的目的是评价双室冠心病PA的计算研究方法和数值结果的验证水平。共有34篇原创研究论文入选。文献显示了各种各样的使用方法（重建）的几何形状以及边界条件和数值设置的定义。确定了10种不同的方法来定义入口边界条件和17种出口边界条件。共有9篇论文通过将结果与临床数据进行比较或通过实验模拟循环验证了其CFD结果。所用方法的多样性和结果的低水平验证导致数值研究可靠性的不确定性。这限制了CFD在CHD PA血流研究中的当前临床效用。因此，建议对这些方法进行标准化和验证。
With the help of computational fluid dynamics (CFD), hemodynamics of the pulmonary arteries (PA's) can be studied in detail and varying physiological circumstances and treatment options can be simulated. This offers the opportunity to improve the diagnostics and treatment of PA stenosis in biventricular congenital heart disease (CHD). The aim of this review was to evaluate the methods of computational studies for PA's in biventricular CHD and the level of validation of the numerical outcomes. A total of 34 original research papers were selected. The literature showed a great variety in the used methods for (re) construction of the geometry as well as definition of the boundary conditions and numerical setup. There were 10 different methods identified to define inlet boundary conditions and 17 for outlet boundary conditions. A total of nine papers verified their CFD outcomes by comparing results to clinical data or by an experimental mock loop. The diversity in used methods and the low level of validation of the outcomes result in uncertainties regarding the reliability of numerical studies. This limits the current clinical utility of CFD for the study of PA flow in CHD. Standardization and validation of the methods are therefore recommended.
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影响因子：
--
作者：
Chern MJ;Wu MT;Her SW
通讯作者：
Her SW
影响因子：
--
作者：
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通讯作者：
Yaku, Hitoshi
DOI：
10.1115/1.4029429
发表时间：
2015-03-01
影响因子：
1.7
作者：
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10.9
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3.8
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