Graduate School of Frontier Sciences, The University of Tokyo, 178-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan.
Next-Generation Healthcare Innovation Center, Fujitsu Ltd, 1-17-25 Shin-kamata, Ohta-ku, Tokyo, 144-8588, Japan.
Int J Numer Method Biomed Eng. 2016 Jul;32(7). doi: 10.1002/cnm.2753. Epub 2015 Nov 2.
In this paper, we propose an algorithm that optimizes the ventricular fiber structure of the human heart. A number of histological studies and diffusion tensor magnetic resonance imaging analyses have revealed that the myocardial fiber forms a right-handed helix at the endocardium. However, the fiber formation changes its orientation as a function of transmural depth, becoming a left-handed helix at the epicardium. To determine how nature can construct such a structure, which obtains surprising pumping performance, we introduce macroscopic modeling of the branching structure of cardiac myocytes in our finite element ventricular model and utilize this in an optimization process. We put a set of multidirectional fibers around a central fiber orientation at each point of the ventricle walls and simulate heartbeats by generating contraction forces along each of these directions. We examine two optimization processes using the workloads or impulses measured in these directions to update the central fiber orientation. Both processes improve the pumping performance towards an optimal value within several tens of heartbeats, starting from an almost-flat fiber orientation. However, compared with the workload optimization, the impulse optimization produces better agreement with experimental studies on transmural changes of fiber helix angle, streamline patterns of characteristic helical structures, and temporal changes in strain. Furthermore, the impulse optimization is robust under geometrical changes of the heart and tends to homogenize various mechanical factors such as the stretch and stretch rate along the fiber orientation, the contraction force, and energy consumption. Copyright © 2015 John Wiley & Sons, Ltd.
在本文中,我们提出了一种优化人心室纤维结构的算法。许多组织学研究和扩散张量磁共振成像分析表明,心肌纤维在内膜处形成右手螺旋。然而,纤维的形成随着心壁深度的变化而改变其方向,在心外膜处形成左手螺旋。为了确定大自然如何构建这种能够获得惊人泵送性能的结构,我们在有限元心室模型中引入了心脏肌细胞分支结构的宏观建模,并在优化过程中利用了这一模型。我们在心室壁的每个点周围放置一组多方向纤维,并沿着这些方向中的每一个产生收缩力来模拟心跳。我们使用在这些方向上测量的工作量或冲量检查了两种优化过程,以更新中央纤维方向。这两个过程都在几十次心跳内将泵送性能朝着最优值改进,从几乎平坦的纤维方向开始。然而,与工作量优化相比,冲量优化在纤维螺旋角的透壁变化、特征螺旋结构的流线模式以及应变的时间变化等方面与实验研究的吻合度更好。此外,在心脏的几何形状发生变化时,冲量优化具有更强的鲁棒性,并且倾向于使纤维方向上的各种机械因素(如拉伸和拉伸率、收缩力和能量消耗)均匀化。版权所有 © 2015 年 John Wiley & Sons, Ltd.