Isogeometric finite element-based simulation of the aortic heart valve: Integration of neural network structural material model and structural tensor fiber architecture representations.
Isogeometric finite element-based simulation of the aortic heart valve: Integration of neural network structural material model and structural tensor fiber architecture representations.
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DOI：
10.1002/cnm.3438
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发表时间：
2021-04
影响因子：
2.1
通讯作者：
Sacks MS
中科院分区：
文献类型：
--
作者：
Zhang W;Rossini G;Kamensky D;Bui-Thanh T;Sacks MS
自体和替换性主动脉瓣的功能复杂性是众所周知的，包括时变的非线性各向异性软组织力学行为、几何非线性、复杂的多表面时变接触以及流固耦合等物理现象。因此，很明显，计算模拟对于理解AV功能以及为设计其替代物提供合理的基础是至关重要的。然而，这种方法仍然受到纳入组织纤维结构、高保真材料模型和瓣膜几何形状的特别方法的限制。为此，我们开发了一种基于等几何分析(IGA)框架的集成三叶阀管道。提出了一种基于高阶结构张量(HOST)的方法来有效地存储二维纤维结构数据并将其映射到瓣膜三维几何结构上。然后，我们开发了一个神经网络(NN)材料模型，该模型学习了外源交联性平面软组织的详细细观结构模型的响应。神经网络材料模型不仅再现了完全各向异性的力学响应，而且由于它在一系列可实现的纤维结构上进行训练，因此效率也有了显著的提高。然后进行了参数模拟的结果，以及基于群体的二尖瓣主动脉瓣纤维结构，证明了本方法的有效性和稳健性。总之，本方法集成了宿主和神经网络材料模型，为模拟天然和替代的三叶瓣提供了一个有效的计算分析框架，增加了物理和功能上的真实感。
The functional complexity of native and replacement aortic heart valves are well known, incorporating such physical phenomenons as time-varying non-linear anisotropic soft tissue mechanical behavior, geometric non-linearity, complex multi-surface time varying contact, and fluid-structure interactions to name a few. It is thus clear that computational simulations are critical in understanding AV function and for the rational basis for design of their replacements. However, such approaches continued to be limited by ad-hoc approaches for incorporating tissue fibrous structure, high-fidelity material models, and valve geometry. To this end, we developed an integrated tri-leaflet valve pipeline built upon an isogeometric analysis (IGA) framework. A high-order structural tensor (HOST) based method was developed for efficient storage and mapping the two-dimensional fiber structural data onto the valvular 3D geometry. We then developed a neural network (NN) material model that learned the responses of a detailed meso-structural model for exogenously cross-linked planar soft tissues. The NN material model not only reproduced the full anisotropic mechanical responses but also demonstrated a considerable efficiency improvement, as it was trained over a range of realizable fibrous structures. Results of parametric simulations were then performed, as well as population based bicuspid aortic heart valve fiber structure, that demonstrated the efficiency and robustness of the present approach. In summary, the present approach that integrates HOST and NN material model provides an efficient computational analysis framework with increased physical and functional realism for the simulation of native and replacement tri-leaflet heart valves.
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影响因子：
3.8
作者：
Aggarwal, Ankush;Ferrari, Giovanni;Joyce, Erin;Daniels, Michael J.;Sainger, Rachana;Gorman, Joseph H., III;Gorman, Robert;Sacks, Michael S.
通讯作者：
Sacks, Michael S.
影响因子：
3.8
作者：
Amini, Rouzbeh;Eckert, Chad E.;Koomalsingh, Kevin;McGarvey, Jeremy;Minakawa, Masahito;Gorman, Joseph H.;Gorman, Robert C.;Sacks, Michael S.
通讯作者：
Sacks, Michael S.
影响因子：
4.1
作者：
Hsu MC;Kamensky D;Xu F;Kiendl J;Wang C;Wu MC;Mineroff J;Reali A;Bazilevs Y;Sacks MS
通讯作者：
Sacks MS
影响因子：
2.6
作者：
LANIR, Y
通讯作者：
LANIR, Y
影响因子：
2.4
作者：
CHANDRAN, KB;KIM, SH;HAN, G
通讯作者：
HAN, G