Department of Biomedical Engineering, Tel Aviv University, Israel.
Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Cardiovascular Research Institute, National University of Singapore, Singapore; Christchurch Heart Institute, Department of Medicine, University of Otago, Christchurch, New Zealand.
J Mech Behav Biomed Mater. 2022 Feb;126:104937. doi: 10.1016/j.jmbbm.2021.104937. Epub 2021 Oct 28.
Numerical modeling of heart biomechanics can realistically capture morphological variations in diseases and has been helpful in advancing our understanding of the physiology. Subject-specific models require anatomic representation of medical images, and it is desirable to have a consistently repeatable models for any given morphology. In this study, we propose a novel and easily adaptable cardiac reconstruction algorithm by morphing an existing discretized mesh of an advanced finite element (FE) model, to match anatomies acquired from porcine cardiac magnetic resonance imaging (cMRI) scans. The morphing algorithm involves iterative FE simulations with visco-hyperelastic material properties. The living heart porcine model (LHPM) was chosen as the input baseline FE mesh, in order to preserve detailed anatomical features that cannot be captured in routine scans such as myofiber orientations and conduction pathways. The algorithm was demonstrated for the recreation of porcine hearts of a healthy subject and of a subject induced with heart failure with preserved ejection fraction (HFpEF) conditions, where there were substantial hypertrophy and anatomical alterations. We further used the morphed meshes for FE modeling of cardiac contraction and relaxation, thus demonstrating the applicability of the proposed algorithm in producing viable meshes. The results show that our algorithm can recreate the characteristic anatomical changes of cardiac remodeling, including heart muscle thickening, as well as replicate the reduction in ventricular volume. This algorithm allows for the creation of subject-specific models with the same mesh connectivity, thus enabling spatial comparison and analysis of pathologic progress.
心脏生物力学的数值建模可以真实地捕捉到疾病中的形态变化,有助于我们深入了解生理学。基于个体的模型需要对医学图像进行解剖学表示,并且期望为任何给定的形态提供一致的可重复模型。在这项研究中,我们提出了一种新颖且易于适应的心脏重建算法,通过变形现有的先进有限元 (FE) 模型的离散网格,以匹配从猪心脏磁共振成像 (cMRI) 扫描中获得的解剖结构。变形算法涉及具有粘弹性材料特性的迭代 FE 模拟。活体猪心脏模型 (LHPM) 被选为输入的基本 FE 网格,以保留常规扫描无法捕捉到的详细解剖特征,如肌纤维方向和传导途径。该算法用于再现健康受试者和射血分数保留的心力衰竭 (HFpEF) 受试者的猪心脏,这些受试者存在明显的肥大和解剖改变。我们进一步使用变形网格进行心脏收缩和松弛的 FE 建模,从而证明了所提出算法在生成可行网格方面的适用性。结果表明,我们的算法可以再现心脏重构的特征性解剖变化,包括心肌增厚,以及心室容积减小。该算法允许创建具有相同网格连接的基于个体的模型,从而能够对病理进展进行空间比较和分析。