School of Aerospace and Mechanical Engineering, The University of Oklahoma, 865 Asp Ave., Felgar Hall, Rm. 219C, Norman, OK, 73019, USA.
Department of Biomedical Engineering, Center for Cardiovascular Simulation, Institute for Computational Engineering and Sciences, The University of Texas at Austin, 201 East 24th St, POB 5.236, 1 University Station, C0200, Austin, TX, 78712, USA.
Biomech Model Mechanobiol. 2017 Oct;16(5):1613-1632. doi: 10.1007/s10237-017-0908-4. Epub 2017 Apr 20.
There continues to be a critical need for developing data-informed computational modeling techniques that enable systematic evaluations of mitral valve (MV) function. This is important for a better understanding of MV organ-level biomechanical performance, in vivo functional tissue stresses, and the biosynthetic responses of MV interstitial cells (MVICs) in the normal, pathophysiological, and surgically repaired states. In the present study, we utilized extant ovine MV population-averaged 3D fiducial marker data to quantify the MV anterior leaflet (MVAL) deformations in various kinematic states. This approach allowed us to make the critical connection between the in vivo functional and the in vitro experimental configurations. Moreover, we incorporated the in vivo MVAL deformations and pre-strains into an enhanced inverse finite element modeling framework (Path 1) to estimate the resulting in vivo tissue prestresses [Formula: see text] and the in vivo peak functional tissue stresses [Formula: see text]. These in vivo stress estimates were then cross-verified with the results obtained from an alternative forward modeling method (Path 2), by taking account of the changes in the in vitro and in vivo reference configurations. Moreover, by integrating the tissue-level kinematic results into a downscale MVIC microenvironment FE model, we were able to estimate, for the first time, the in vivo layer-specific MVIC deformations and deformation rates of the normal and surgically repaired MVALs. From these simulations, we determined that the placement of annuloplasty ring greatly reduces the peak MVIC deformation levels in a layer-specific manner. This suggests that the associated reductions in MVIC deformation may down-regulate MV extracellular matrix maintenance, ultimately leading to reduction in tissue mechanical integrity. These simulations provide valuable insight into MV cellular mechanobiology in response to organ- and tissue-level alternations induced by MV disease or surgical repair. They will also assist in the future development of computer simulation tools for guiding MV surgery procedure with enhanced durability and improved long-term surgical outcomes.
目前仍然迫切需要开发数据驱动的计算建模技术,以便能够对二尖瓣 (MV) 功能进行系统评估。这对于更好地理解 MV 器官水平的生物力学性能、MV 间质细胞 (MVIC) 在正常、病理生理和手术修复状态下的体内功能组织应力和生物合成反应非常重要。在本研究中,我们利用现有的绵羊 MV 群体平均 3D 基准标记数据来量化各种运动状态下 MV 前瓣 (MVAL) 的变形。这种方法使我们能够在体内功能和体外实验配置之间建立关键联系。此外,我们将体内 MVAL 变形和预应变纳入增强的逆有限元建模框架 (Path 1) 中,以估计体内组织预应力 [公式:见正文] 和体内峰值功能组织应力 [公式:见正文]。通过考虑体外和体内参考配置的变化,将这些体内应力估计与另一种正向建模方法 (Path 2) 的结果进行交叉验证。此外,通过将组织水平的运动学结果整合到一个降尺度 MVIC 微环境 FE 模型中,我们能够首次估计正常和手术修复的 MVAL 的体内特定 MVIC 变形和变形率。从这些模拟中,我们确定环缩术的放置极大地以特定于层的方式降低了 MVIC 变形的峰值水平。这表明 MVIC 变形的相关减少可能会下调 MV 细胞外基质的维持,最终导致组织机械完整性的降低。这些模拟为 MV 疾病或手术修复引起的器官和组织水平改变后 MVIC 的细胞力学生物学提供了有价值的见解。它们还将有助于未来开发计算机模拟工具,以指导具有增强耐久性和改善长期手术结果的 MV 手术程序。